diff --git a/.travis.yml b/.travis.yml index 25fbf76f..7d4853c6 100644 --- a/.travis.yml +++ b/.travis.yml @@ -44,7 +44,6 @@ sudo: false install: - make install - - make start # - sleep 2 # # Prepare env with Python version # - conda create -n raven python=$TRAVIS_PYTHON_VERSION @@ -59,9 +58,10 @@ install: before_script: # # Start WPS service on port 5000 on 0.0.0.0 # - raven start --daemon --bind-host 0.0.0.0 --port 5000 - - sleep 2 + - make start script: - make test + - make test_nb - if [[ $DOCS = true ]]; then make docs; fi - if [[ $PEP8 = true ]]; then make pep8; fi diff --git a/CHANGES.rst b/CHANGES.rst index 3241be74..ef859dba 100644 --- a/CHANGES.rst +++ b/CHANGES.rst @@ -9,6 +9,7 @@ Changes * Optimized memory usage in ReadTheDocs builds when using Sphinx autodoc by employing mock * Cleaner GeoJSON outputs for many subsetting processes * Employed ipyleaflets for notebook-based web-maps +* Run py.test on notebooks from local or remote server 0.7.x (2019-06-25) diff --git a/Dockerfile b/Dockerfile index b614a02a..8240f3a5 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,7 +1,7 @@ # vim:set ft=dockerfile: FROM continuumio/miniconda3 MAINTAINER https://github.com/huard/raven -LABEL Description="Raven WPS" Vendor="Birdhouse" Version="0.8.2-beta" +LABEL Description="Raven WPS" Vendor="Birdhouse" Version="0.8.3-beta" # Update Debian system RUN apt-get update && apt-get install -y \ diff --git a/Makefile b/Makefile index 5c501782..e69a8987 100644 --- a/Makefile +++ b/Makefile @@ -21,6 +21,9 @@ OSTRICH_SRC = $(CURDIR)/src/OSTRICH OSTRICH_TARGET = GCC # can be also MPI but requires mpi compiler; not tested UNAME_S := $(shell uname -s) DOWNLOAD_CACHE = /tmp/ +RAVEN_WPS_URL = http://localhost:9099 +FLYINGPIGEON_WPS_URL = http://localhost:8093 + ifeq "$(UNAME_S)" "Linux" FN := Miniconda3-latest-Linux-x86_64.sh @@ -50,6 +53,7 @@ help: @echo " clean to remove *all* files that are not controlled by 'git'. WARNING: use it *only* if you know what you do!" @echo "\nTesting targets:" @echo " test to run tests (but skip long running tests)." + @echo " test_nb to verify Jupyter Notebook test outputs are valid." @echo " testall to run all tests (including long running tests)." @echo " pep8 to run pep8 code style checks." @echo "\nSphinx targets:" @@ -167,6 +171,11 @@ test: @echo "Running tests (skip slow and online tests) ..." @bash -c "source $(ANACONDA_HOME)/bin/activate $(CONDA_ENV);pytest -v -m 'not slow and not online'" +.PHONY: test_nb +test_nb: + @echo "Running notebook-based tests" + @bash -c "source $(ANACONDA_HOME)/bin/activate $(CONDA_ENV);env RAVEN_WPS_URL=$(RAVEN_WPS_URL) FLYINGPIGEON_WPS_URL=$(FLYINGPIGEON_WPS_URL) pytest --nbval $(CURDIR)/docs/source/notebooks/ --sanitize-with $(CURDIR)/docs/source/output_sanitize.cfg --ignore $(CURDIR)/docs/source/notebooks/.ipynb_checkpoints" + .PHONY: test_pdb test_pdb: @echo "Running tests (skip slow and online tests) with --pdb ..." diff --git a/docs/source/conf.py b/docs/source/conf.py index 6b3c7fee..70f2da87 100755 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -82,7 +82,7 @@ # The short X.Y version. version = '' # The full version, including alpha/beta/rc tags. -release = '0.8.2-beta' +release = '0.8.3-beta' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. diff --git a/docs/source/notebooks/Delineation_workflow.ipynb b/docs/source/notebooks/Delineation_workflow.ipynb index f3c0bc43..feee6135 100644 --- a/docs/source/notebooks/Delineation_workflow.ipynb +++ b/docs/source/notebooks/Delineation_workflow.ipynb @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -21,9 +21,13 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import geopandas as gpd\n", + "import json\n", + "import os\n", + "\n", "\n", - "url = \"http://localhost:9099/wps\"\n", - "wps = WPSClient(url, progress=True)" + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", + "wps = WPSClient(url)" ] }, { @@ -37,27 +41,21 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "metadata": {}, "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "cdde303bcd684e179003a423ec25d59e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Processing:'), Button(button_style='danger'…" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] } ], "source": [ "# MANIC: lonlat_coordinate=\"(-68.724444, 50.646667)\"\n", "# St-Lawrence I guess is \"-75.724444, 44.646667\"? Returns 770 000 sq.km basin...\n", + "print(wps)\n", "r_select = wps.hydrobasins_select(location=\"-71.291660, 50.492758\", aggregate_upstream=False)\n", "\n", "#r_select = wps.hydrosheds_select(location=\"-68.724444, 50.646667\", aggregate_upstream=True)" @@ -65,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -74,39 +72,19 @@ "{\"geometry\": {\"coordinates\": [[[[-71.3592, 50.4196], [-71.3621, 50.4226], [-71.3625, 50.425], [-71.3629, 50.4358], [-71.3705, 50.4434], [-71.3712, 50.4566], [-71.3746, 50.4601], [-71.3754, 50.4642], [-71.3712, 50.4684], [-71.3705, 50.4733], [-71.367, 50.4767], [-71.3663, 50.4983], [-71.3629, 50.5017], [-71.3621, 50.5108], [-71.3587, 50.5142], [-71.3583, 50.5208], [-71.3561, 50.5203], [-71.348, 50.5131], [-71.3436, 50.5119], [-71.3382, 50.5078], [-71.3353, 50.5089], [-71.3299, 50.5131], [-71.3257, 50.5114], [-71.3243, 50.5009], [-71.3186, 50.4994], [-71.3146, 50.4963], [-71.3105, 50.4994], [-71.3061, 50.5006], [-71.2927, 50.5131], [-71.2883, 50.5115], [-71.2869, 50.5061], [-71.2839, 50.5022], [-71.2833, 50.4958], [-71.2833, 50.4917], [-71.2875, 50.4917], [-71.298, 50.4911], [-71.302, 50.4881], [-71.3105, 50.4869], [-71.3199, 50.4786], [-71.3214, 50.4728], [-71.3306, 50.4632], [-71.3366, 50.4609], [-71.3491, 50.4533], [-71.3488, 50.4529], [-71.3472, 50.4513], [-71.3461, 50.4439], [-71.3479, 50.4291], [-71.3535, 50.4237], [-71.3592, 50.4196]]]], \"type\": \"MultiPolygon\"}, \"id\": \"96929\", \"properties\": {\"COAST\": 0, \"DIST_MAIN\": 490.9, \"DIST_SINK\": 490.9, \"ENDO\": 0, \"HYBAS_ID\": 7120270182, \"LAKE\": 0, \"MAIN_BAS\": 7120034330, \"NEXT_DOWN\": 7120270181, \"NEXT_SINK\": 7120034330, \"ORDER\": 1, \"PFAF_ID\": 724089370000, \"SIDE\": \"R\", \"SORT\": 96929, \"SUB_AREA\": 29.0, \"UP_AREA\": 9419.6, \"gml_id\": \"USGS_HydroBASINS_lake_na_lev12.96929\"}, \"type\": \"Feature\"}" ] }, - "execution_count": 5, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get GeoJSON polygon of the delineated catchment.\n", + "# We can either get links to the files stored on the server, or get the data directly. \n", + "[feature_url, upstream_basins_url] = r_select.get(asobj=False)\n", "[feature, upstream_basins] = r_select.get(asobj=True)\n", "feature" ] }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'http://localhost:9099/outputs/7afbc50e-afca-11e9-bc82-484d7ef8d8d1/input.geojson'" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Get the links to the files on the server\n", - "feature_url, upstream_basins_url = r_select.get(asobj=False)\n", - "feature_url" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -116,22 +94,22 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -143,7 +121,8 @@ } ], "source": [ - "df = gpd.read_file(feature_url)\n", + "# df = gpd.read_file(feature_url)\n", + "df = gpd.GeoDataFrame.from_features([feature])\n", "df.plot()" ] }, @@ -151,56 +130,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "~~We can now plot the outline of the watershed using the `descartes` package and `matplotlib`.~~" + "Now that we have delineated a catchment, lets find the zonal statistics and other properties of the catchment. We can pass the catchment outline either as a link to a file (e.g. `feature_url`), or pass the data directly as a string. " ] }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 5, "metadata": {}, "outputs": [], - "source": [ - "# BLUE = '#6699cc'\n", - "# fig = plt.figure() \n", - "# ax = fig.gca() \n", - "# ax.add_patch(PolygonPatch(feature['geometry'], fc=BLUE, ec=BLUE, alpha=0.5, zorder=2 ))\n", - "# ax.axis('scaled')\n", - "# plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now that we have delineated a catchment, lets find the zonal statistics and other properties of the catchment." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "db381e90a60e4c209b36339631dc44b5", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Processing:'), Button(button_style='danger'…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], "source": [ "# Here we are using the geojson file created on the server in the last step as the input value to a process \n", "# computing watershed properties. \n", "#crs=4326\n", "#projected_crs=32198\n", - "resp = wps.shape_properties(shape=feature_url)" + "resp = wps.shape_properties(shape=json.dumps(feature))" ] }, { @@ -212,7 +155,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -232,7 +175,7 @@ " 'perimeter': 33017.42666655582}" ] }, - "execution_count": 9, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -263,24 +206,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "7335839f277540d8b7fc4c29ffdeb01d", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Processing:'), Button(button_style='danger'…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Use the geoserver to extract the land cover over the appropriate bounding box (automatic)\n", "resp = wps.nalcms_zonal_stats(shape=feature_url, select_all_touching=True, band=1, simple_categories=True)" @@ -288,14 +216,14 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{\"features\": [{\"geometry\": {\"coordinates\": [[[[1981874.096748117, 967399.0911914052], [1981560.4971648867, 967640.7996158176], [1981434.9369879127, 967882.7807668581], [1980961.2637742816, 969007.1294172165], [1980150.4532387636, 969613.136897321], [1979557.7882538023, 970982.0066178304], [1979190.993435453, 971263.6623110471], [1978968.9179589564, 971674.108712833], [1979068.7370289837, 972221.4986643237], [1978911.2766435912, 972753.8972656073], [1978998.5184324386, 973199.5400577396], [1978148.5360125287, 975486.0006584836], [1978229.0726735129, 975929.0688304713], [1977903.7424964204, 976905.0670857691], [1977984.1732537195, 977348.1154956503], [1977736.39888101, 978051.40082158], [1977900.4252855848, 978054.5035027583], [1978726.7671066807, 977503.1475924414], [1979063.162155457, 977488.4102143587], [1979585.086480826, 977194.4381107079], [1979728.31449522, 977383.3356572706], [1979905.6264661902, 977961.0506469918], [1980249.760065988, 977888.8221596053], [1980777.0205245588, 976821.6140084906], [1981210.6254241262, 976808.4123675763], [1981599.9652658133, 976584.1723129161], [1981738.2557495865, 977013.5474293529], [1981974.993178329, 977251.010851383], [1982328.0510653253, 978903.0377999832], [1982681.0729708741, 978846.538718968], [1982996.7907913027, 978315.0344648779], [1983354.3364343601, 977981.5895128745], [1983659.5600711212, 977324.8163370308], [1983830.0521372445, 976894.3229222285], [1983556.471153514, 976787.8376635303], [1982897.423789108, 976458.6876778962], [1982761.5084731434, 976042.3007405908], [1982257.5670965123, 975700.9204296736], [1981989.7596723628, 974591.1839045994], [1982132.8261994827, 973944.0859803229], [1981931.5999756719, 972702.8546073242], [1981635.8450955295, 972309.3457865227], [1981135.976983787, 971194.6244946554], [1981172.1313644364, 971160.2056112073], [1981342.8394163426, 971032.6586613981], [1981721.483719015, 970283.2595854887], [1982217.756235964, 968683.1417384447], [1982076.182758441, 967974.1057193918], [1981874.096748117, 967399.0911914052]]]], \"type\": \"MultiPolygon\"}, \"id\": \"0\", \"properties\": {\"COAST\": 0, \"Crops\": 0, \"DIST_MAIN\": 490.9, \"DIST_SINK\": 490.9, \"ENDO\": 0, \"Forest\": 19081, \"Grass\": 479, \"HYBAS_ID\": 7120270182, \"LAKE\": 0, \"MAIN_BAS\": 7120034330, \"NEXT_DOWN\": 7120270181, \"NEXT_SINK\": 7120034330, \"ORDER\": 1, \"Ocean\": 0, \"PFAF_ID\": 724089370000, \"SIDE\": \"R\", \"SORT\": 96929, \"SUB_AREA\": 29.0, \"Shrubs\": 10239, \"SnowIce\": 0, \"UP_AREA\": 9419.6, \"Urban\": 0, \"Water\": 3248, \"Wetland\": 21, \"count\": 33068, \"gml_id\": \"USGS_HydroBASINS_lake_na_lev12.96929\", \"id\": \"96929\", \"nan\": 0, \"nodata\": 8.0}, \"type\": \"Feature\"}], \"type\": \"FeatureCollection\"} \n", + "{'id': '96929', 'gml_id': 'USGS_HydroBASINS_lake_na_lev12.96929', 'HYBAS_ID': 7120270182, 'NEXT_DOWN': 7120270181, 'NEXT_SINK': 7120034330, 'MAIN_BAS': 7120034330, 'DIST_SINK': 490.9, 'DIST_MAIN': 490.9, 'SUB_AREA': 29.0, 'UP_AREA': 9419.6, 'PFAF_ID': 724089370000, 'SIDE': 'R', 'LAKE': 0, 'ENDO': 0, 'COAST': 0, 'ORDER': 1, 'SORT': 96929, '1': 13532, '2': 335, '5': 4367, '6': 847, '8': 10239, '10': 60, '12': 380, '14': 21, '16': 39, '18': 3248, 'count': 33068, 'nodata': 8.0, 'nan': 0, 'Ocean': 0, 'Forest': 19081, 'Shrubs': 10239, 'Grass': 479, 'Wetland': 21, 'Crops': 0, 'Urban': 0, 'Water': 3248, 'SnowIce': 0} \n", "\n", "\n", "[{'Ocean': 0, 'Forest': 19081, 'Shrubs': 10239, 'Grass': 479, 'Wetland': 21, 'Crops': 0, 'Urban': 0, 'Water': 3248, 'SnowIce': 0}]\n" @@ -303,11 +231,33 @@ } ], "source": [ - "feature, statistics = resp.get(asobj=True)\n", - "print(feature, '\\n\\n')\n", + "# Note that geojson needs to be installed for this to work. \n", + "# $ pip install -r requirements_extra.txt\n", + "features, statistics = resp.get(asobj=True)\n", + "print(features[0]['properties'], '\\n\\n')\n", "print(statistics)" ] }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{\"features\": [{\"geometry\": {\"coordinates\": [[[[1981874.096748, 967399.091191], [1981560.497165, 967640.799616], [1981434.936988, 967882.780767], [1980961.263774, 969007.129417], [1980150.453239, 969613.136897], [1979557.788254, 970982.006618], [1979190.993435, 971263.662311], [1978968.917959, 971674.108713], [1979068.737029, 972221.498664], [1978911.276644, 972753.897266], [1978998.518432, 973199.540058], [1978148.536013, 975486.000658], [1978229.072674, 975929.06883], [1977903.742496, 976905.067086], [1977984.173254, 977348.115496], [1977736.398881, 978051.400822], [1977900.425286, 978054.503503], [1978726.767107, 977503.147592], [1979063.162155, 977488.410214], [1979585.086481, 977194.438111], [1979728.314495, 977383.335657], [1979905.626466, 977961.050647], [1980249.760066, 977888.82216], [1980777.020525, 976821.614008], [1981210.625424, 976808.412368], [1981599.965266, 976584.172313], [1981738.25575, 977013.547429], [1981974.993178, 977251.010851], [1982328.051065, 978903.0378], [1982681.072971, 978846.538719], [1982996.790791, 978315.034465], [1983354.336434, 977981.589513], [1983659.560071, 977324.816337], [1983830.052137, 976894.322922], [1983556.471154, 976787.837664], [1982897.423789, 976458.687678], [1982761.508473, 976042.300741], [1982257.567097, 975700.92043], [1981989.759672, 974591.183905], [1982132.826199, 973944.08598], [1981931.599976, 972702.854607], [1981635.845096, 972309.345787], [1981135.976984, 971194.624495], [1981172.131364, 971160.205611], [1981342.839416, 971032.658661], [1981721.483719, 970283.259585], [1982217.756236, 968683.141738], [1982076.182758, 967974.105719], [1981874.096748, 967399.091191]]]], \"type\": \"MultiPolygon\"}, \"id\": \"0\", \"properties\": {\"1\": 13532, \"10\": 60, \"12\": 380, \"14\": 21, \"16\": 39, \"18\": 3248, \"2\": 335, \"5\": 4367, \"6\": 847, \"8\": 10239, \"COAST\": 0, \"Crops\": 0, \"DIST_MAIN\": 490.9, \"DIST_SINK\": 490.9, \"ENDO\": 0, \"Forest\": 19081, \"Grass\": 479, \"HYBAS_ID\": 7120270182, \"LAKE\": 0, \"MAIN_BAS\": 7120034330, \"NEXT_DOWN\": 7120270181, \"NEXT_SINK\": 7120034330, \"ORDER\": 1, \"Ocean\": 0, \"PFAF_ID\": 724089370000, \"SIDE\": \"R\", \"SORT\": 96929, \"SUB_AREA\": 29.0, \"Shrubs\": 10239, \"SnowIce\": 0, \"UP_AREA\": 9419.6, \"Urban\": 0, \"Water\": 3248, \"Wetland\": 21, \"count\": 33068, \"gml_id\": \"USGS_HydroBASINS_lake_na_lev12.96929\", \"id\": \"96929\", \"nan\": 0, \"nodata\": 8.0}, \"type\": \"Feature\"}], \"type\": \"FeatureCollection\"}" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "features" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -317,7 +267,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -334,7 +284,7 @@ " 'SnowIce': 0.0}" ] }, - "execution_count": 19, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -352,29 +302,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The next step will be to collect terrain data, such as elevation, slope and aspect. We will do this using the Terrain_Analysis WPS service:" + "The next step will be to collect terrain data, such as elevation, slope and aspect. We will do this using the `terrain_analysis` WPS service:" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 11, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "f1a3663bcf5e4026817f80f60999fe6f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Processing:'), Button(button_style='danger'…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "resp=wps.terrain_analysis(shape=feature_url, select_all_touching=True, projected_crs=3978)" ] @@ -383,12 +318,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Now let's extract the properties from the WPS response. Use asobj=True to have Birdy preprocess the data and return the data directly." + "Now let's extract the properties from the WPS response. Use `asobj=True` to have Birdy preprocess the data and return the data directly." ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -410,7 +345,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -430,19 +365,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**Note here that the shape of teh feature has changed since slope calculations require metres on the ground. This means that the DEM required a projection.** \n", + "Note here that while the feature outline is defined above in terms of geographic coordinates (latitude, longitude), the DEM is projected onto a 2D cartesion coordinate system (here NAD83, the Canada Atlas Lambert projection). This is necessary to perform slope calculations. \n", "\n", - "**For more information on this, see: https://en.wikipedia.org/wiki/Map_projection**" + "For more information on this, see: https://en.wikipedia.org/wiki/Map_projection" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -454,26 +389,25 @@ } ], "source": [ + "# NBVAL_SKIP\n", "import cartopy.crs as ccrs\n", "import rasterio\n", "from rasterio.plot import show\n", "import xarray as xr\n", + "import rasterio\n", + "from rasterio.io import MemoryFile\n", "\n", - "with rasterio.open(dem, 'r') as src:\n", - " crs = ccrs.epsg(src.crs.to_epsg())\n", - " da = xr.open_rasterio(dem)\n", - " da.name = 'Elevation'\n", - " da.attrs['units'] = 'm'\n", - " ax = plt.subplot(projection=crs)\n", - " da.where(da!=-32768).sel(band=1).plot.imshow(ax=ax, transform=crs)\n", - " plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### There we go! We have extracted the contours of a watershed along with a series of hydrologically relevant properties, all from the coordinates of a single location (outlet)!" + "with MemoryFile(dem) as mem:\n", + " with mem.open(driver='gtiff') as src:\n", + "\n", + "# with rasterio.open(dem) as src:\n", + " crs = ccrs.epsg(src.crs.to_epsg())\n", + " da = xr.open_rasterio(src)\n", + " da.name = 'Elevation'\n", + " da.attrs['units'] = 'm'\n", + " ax = plt.subplot(projection=crs)\n", + " da.where(da!=-32768).sel(band=1).plot.imshow(ax=ax, transform=crs)\n", + " plt.show()" ] } ], @@ -493,7 +427,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/Perform_Regionalization.ipynb b/docs/source/notebooks/Perform_Regionalization.ipynb index 81da93b8..9107c13d 100644 --- a/docs/source/notebooks/Perform_Regionalization.ipynb +++ b/docs/source/notebooks/Perform_Regionalization.ipynb @@ -24,9 +24,11 @@ "import numpy as np\n", "from matplotlib import pyplot as plt\n", "import json\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", - "wps = WPSClient(url,progress=True)" + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", + "wps = WPSClient(url)" ] }, { @@ -40,30 +42,30 @@ "text": [ "Help on method regionalisation in module birdy.client.base:\n", "\n", - "regionalisation(ts, properties, latitude, longitude, model_name=None, elevation=None, start_date=datetime.datetime(1, 1, 1, 0, 0), end_date=datetime.datetime(1, 1, 1, 0, 0), name='watershed', ndonors=5, min_nse=0.6, method='SP_IDW', area=None) method of birdy.client.base.WPSClient instance\n", + "regionalisation(ts, latitude, longitude, model_name, properties=None, elevation=None, start_date=datetime.datetime(1, 1, 1, 0, 0), end_date=datetime.datetime(1, 1, 1, 0, 0), name='watershed', ndonors=5, min_nse=0.6, method='SP_IDW', area=0.0) method of birdy.client.base.WPSClient instance\n", " Compute the hydrograph for an ungauged catchment using a regionalization method.\n", " \n", " Parameters\n", " ----------\n", " ts : ComplexData:mimetype:`application/x-netcdf`, :mimetype:`text/plain`, :mimetype:`application/x-zipped-shp`\n", " Files (text or netCDF) storingdaily liquid precipitation (pr), solid precipitation (prsn), minimum temperature (tasmin), maximum temperature (tasmax), potential evapotranspiration (evspsbl) and observed streamflow (qobs [m3/s]).\n", - " start_date : //www.w3.org/TR/xmlschema-2/#dateTime\n", + " start_date : dateTime\n", " Start date of the simulation (AAAA-MM-DD). Defaults to the start of the forcing file.\n", - " end_date : //www.w3.org/TR/xmlschema-2/#dateTime\n", + " end_date : dateTime\n", " End date of the simulation (AAAA-MM-DD). Defaults to the end of the forcing file.\n", - " latitude : //www.w3.org/TR/xmlschema-2/#float\n", + " latitude : float\n", " Watershed's centroid latitude\n", - " longitude : //www.w3.org/TR/xmlschema-2/#float\n", + " longitude : float\n", " Watershed's centroid longitude\n", - " name : //www.w3.org/TR/xmlschema-2/#string\n", + " name : string\n", " The name of the watershed the model is run for.\n", - " model_name : {'HMETS', 'GR4JCN', 'MOHYSE'}//www.w3.org/TR/xmlschema-2/#string\n", + " model_name : {'HMETS', 'GR4JCN', 'MOHYSE'}string\n", " Hydrological model identifier: {HMETS, GR4JCN, MOHYSE}\n", - " ndonors : //www.w3.org/TR/xmlschema-2/#integer\n", + " ndonors : integer\n", " Number of close or similar catchments to use to generate the representative hydrograph at the ungauged site.\n", - " min_nse : //www.w3.org/TR/xmlschema-2/#float\n", + " min_nse : float\n", " Minimum calibration NSE value required to be considered in the regionalization.\n", - " method : {'MLR', 'SP', 'PS', 'SP_IDW', 'PS_IDW', 'SP_IDW_RA', 'PS_IDW_RA'}//www.w3.org/TR/xmlschema-2/#string\n", + " method : {'MLR', 'SP', 'PS', 'SP_IDW', 'PS_IDW', 'SP_IDW_RA', 'PS_IDW_RA'}string\n", " Regionalisation method to use, one of MLR, SP, PS, SP_IDW,\n", " PS_IDW, SP_IDW_RA, PS_IDW_RA.\n", " \n", @@ -100,9 +102,9 @@ " is higher than 0.5 are replaced by the MLR-estimated value.\n", " properties : ComplexData:mimetype:`application/json`\n", " json string storing dictionary of properties. The available properties are: area (km2), longitude (dec.degrees), latitude (dec. degrees), gravelius, perimeter (m), elevation (m), slope(%), aspect, forest (%), grass (%), wetland (%), water (%), urban (%), shrubs (%), crops (%) and snowIce (%).\n", - " area : //www.w3.org/TR/xmlschema-2/#float\n", + " area : float\n", " Watershed area (km2)\n", - " elevation : //www.w3.org/TR/xmlschema-2/#float\n", + " elevation : float\n", " Watershed's mean elevation (m)\n", " \n", " Returns\n", @@ -124,22 +126,7 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "3db2c64c79fa4645a34c0ce78295fdcd", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Processing:'), Button(button_style='danger'…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Forcing files. This file should only contain weather data (tmin, tmax, rain, snow, pet (if desired), etc. \n", "# No streamflow is required. This is a link to a string, but you can submit a string to your netcdf file directly.\n", @@ -162,16 +149,19 @@ " )\n", "\n", "# Let's call the model with the timeseries, model parameters and other configuration parameters\n", - "resp = wps.regionalisation(ts=ts, **config)\n" + "resp = wps.regionalisation(ts=ts, **config)\n", + "\n", + "# # Wait for results to come in\n", + "# from time import sleep\n", + "# sleep(5)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ - "\n", "# And get the response\n", "# With `asobj` set to False, only the reference to the output is returned in the response. \n", "# Setting `asobj` to True will retrieve the actual files and copy the locally. \n", @@ -187,7 +177,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -202,15 +192,15 @@ " [ 22.912411],\n", " [ 22.475852]])\n", "Coordinates:\n", - " * time (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2002-01-01\n", " basin_name (nbasins) object ...\n", + " * time (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2002-01-01\n", "Dimensions without coordinates: nbasins\n", "Attributes:\n", " units: m**3 s**-1\n", " long_name: Simulated outflows" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -221,34 +211,22 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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KRVGU7MGrQgmISA1wGXDIFzLG4u7lBbZCaQ+RxiGRnuhSC0VRlCzCq0L5EfA0sMEY846ITAbWp0+s7KK7sNHSKCX5AcIRQ3OGJzd2qIWiKEoW4bU55KPGmAecFXuS4qXpESn7cM9DgZ4t7IvzcjIlllooiqJkFV4VygoR2QW8CrwCvG6MaUifWNmFY6H44iiUsWUZEgqNoSiKkl14cnkZYw4DPgG8B1wELBORpekULJuIGPdUeSjNtyY1HmjNbGDeneWV6XiOoiiKJwtFRMYCJwGnAHOBlcBraZQrK3FcXuVFlkLZ25LZNmZdLgulIxQhL8efQWkURRnueHV5bQXeAf7XGPPFNMqTlbi7DQOUF1oKZV9zR/wXDBJuC6WjSxWKoiiZxWuW11HAPcDlIvKmiNwjIp9Lo1xZRXdQ3lIpIwpyEYF9GbZQOlwKpT0UzqAkiqIo3ic2LhORjcBGLLfXp4AFwB1plC1riLVQ/D6hrCA3C1xe3XGT9i5VKIqiZBavMZRFQBB4Ayt2ssAYsyWdgmUTsZXyACMLczNuofRweWkKsaIoGcZrDOV8Y8yw7ZHunofiMLIwGywUl8tLLRRFUTKM1xhKp4jcJCKL7OVGESlNq2RZROw8FICKolz2Zjoo30OhqIWiKEpm8apQ7gSasHp5XQY0AnelS6hsI16FR/a5vNRCURQls3hVKFOMMdcbYzbZyw+ByakURETyRGShiCwTkZUi8kN7+yQReVtE1ovIP0Qk194etNc32PsnplKeHsSNoQQ50NZFOJK5gkL3udVCURQl03hVKG0icrKzIiInAW0plqUDOMMYMxc4EjhPRI4Hfg7cbIyZCuwHnHTlzwH77Sr+m+3j0kJs2jBYtSjGwP7WzFkpoYhaKIqiZA9eg/JfAu624yYC7AOujD1IRD7s4b3ajTFPxG40VqCi2V7NsRcDnAFcbm+/G/gBcBtwsf0c4EHgdyIiJg09SGJ7eYHl8gKrFqWiKJjqU3oiFFYLRVGU7MFrHcpSYK6IlNjrjQkO/RPwMLjSoXqzAOilUABExA8sBg4DbsWqezlgjHH6xNcCY+znY4BttjwhEWkAyoE9Xj5Tf4jEtK8HV/uV5k6oTvUZvRGKGIIBHx2hiGZ5KYqScfpUKCLytQTbATDGxI4BftIY8x9J3vOvifYZY8LAkSIyAngImBHvMOet+tjnPt9VwFUA48eP70u0hMS2rwcoL7Sskr0tmcv06gpHKAoG6Ah1ah2KoigZJ1kMpTjJ0gNjzKeSndDjMQeAl4DjgREi4ii+scAO+3ktMA7A3l+K5YqLfa/bjTHzjTHzKysrk506gTzWo1uDuV1emSIcMRQGra9GLRRFUTJNMpdXgTHmWyLyUfeArYEgImcbY57tY38l0GWMOSAi+Vgz638OvAh8BPg7cAWWSw3gEXv9TXv/C+mIn4DL7HFplLKCHHwCe5oyaaEYCnKthpAdqlAURckwySyUC0QkB7guBedK1verBnhRRJZjdTZ+1hjzGPAt4GsisgErRuK8zx1Aub39a8C1KZAxPk5ho0ujBPw+KoqC7GxsT9tpkxGORMgN+KJxFEVRlEySzEJ5CivIXSgi7kC8YCVmlbgPFpFHEryPYCmDhBhjlmN1NY7dvgk4Ns72duCjfUqfIqJBm5iozajSPHY2Zs5CCUUMfp+Ql+NXl5eiKBmnT4VijPkm8E0RedgYc7GH93M6ETfHbBfiKIWhQrwYCkB1SR7b9rUOujwOXeEIOT4feTk+TRtWFCXjeK1DWRO7QUR+boz5Vszmt4BWY8zLcY5fOwD5soLuXl49Vcqokjze2dwrD2DQCEcMAZ+PomCApo7MjiNWFEXxWil/dpxt58duMMacb4x5Md4bGGMW9EewbCJRnnJ1SZADrV0Zczd1hQ0Bv1Can0NDmyoURVEyS58KRUS+JCLvAdNFZLlreR9Y7uUEInJRKgTNJPHmoYDl8gLYlaHAfDhiyPH7KMnPobEtlPwFiqIoaSSZy+s+4Engp/TMomoyxnj19fwIeGwAsmUN8eahgBWUB9jV2MGE8sJBlsqKofh9QnFugE31LYN+fkVRFDfJgvINQIOIxMZKikSkyBiz1cM5+mrDMiQwCaLyo2wLJVOpw6GIIcd2eTW2q8tLUZTM4jUo/zjWjboAecAkYC0wy8Nr/3NgomUfvhiFUuW4vBoy5/Ly+3yU5OXQ2NZFJGLwxQqpKIoySHgKyhtj5hhjjrAfp2KlAL8W71gR+bH9+CP7tQtTJWymiCTI8irJC5Cf48+YhWKlDQtlhblEDBqYVxQlo3jN8uqBMeZd4JgEu98RkVuBRQOWKstIVIciIowqzctoUD7gF6pLrEaVuzPYBkZRFMWTyyum67APmAfUxznuemAk8AkgJCJHGmN+lApBM0miSnmAmtI8th9I9awxb3SFLZdXVXF3ttnho3r17FQURRkUvFoo7g7DQayYSq/KeXs0MMAJ9vqQVybgtlB6a5RxZQVs25cZhRKKRMhxWSiZspQURVHA+4AtZ757sbVqYluruLnTGLNWRO5MhYDZQLx5KA7jRuazp7mDts4w+Xbn38EiHLYq5R0LRV1eiqJkEk8WiojMFpElwApgpYgsFpHZCQ53GjZemgoBs4G+muKPG1kAQO3+we/p1RWJEPAL+bl+ivMC7FYLRVGUDOLV5XU78DVjzARjzATg6/a2eBxyQXmH+BaKpVC2ZqBJZFfYELDThKtL8tRCURQlo3hVKIXuHl3GmJeAXqXhdlD+DKyg/Jki8v1UCJlpTJx5KA7jyiyFMthdh0PhCOGIIS/HcrNVFQc1hqIMGk3tXazY3pBpMZQsw6tC2SQi3xORifbyXeD92IMO+aB8HAuloiiX/Bw/2/YPbmC+M2y1qw8GrD+hWijKYHLFnQu56LevEYmkZUiqMkTxqlD+A6gE/mUvFcBnExx7F3AE8E8AEfmuiPxLROYdpKwZI1G3YbBqUcaNzB90l1dHV0+FUlUSZHdjR3ebGEVJI+9uPQCgk0KVHnjN8toP/LfHY5eKyD3GmCNE5GTgXOBXwG3AcQOWNIN0Wyjx25pYqcODrFDsf+Rg1OWVR2c4QkNbFyMKcgdVFmX40hEa/OxGJXsZUKW8B5wBIRcCtxljHgaG7FUumjacYP+4kZZCGSzroL6pg1N+8QLgdnk5tSjq9lIGD50UqrhJl0LZLiJ/BC4DnhCRYBrPlXb6iqEATK4spKUzPGgX86dW7qQrbAkVDHRbKKDFjcrg0hHKzHA5JTtJ10X+MuBp4DxjzAGsdizfTNO50k6iEcAOh1UWAbBhd1/1nqmjKNjtYoi1UDQwrwwmaqEobvqMoYjIb+mOSffCGBM3rmKMacUK3jvrdUDdAGXMOIbE1gnAYVWOQmni5KkVaZcnP8elUHLsoLxaKEoGUAtFcZPMQlkELMaagTIPWG8vR9IdJznkMabvKWGVxUGK8wJsqB8cC8WdWeO4vJxq+Xq1UJRBRC0UxU2fCsUYc7cx5m5gKnC6Mea3xpjfAmdiKZVhgcEkdHeB5QqbWlU0aC6v9q5uXe64vMCqRVELJfXsbe7got++ypa9OmY5FrVQFDdeYyijsToNOxTZ24YFySwUsNxeG3YPzgXHfVfouLzAqpbXGErqefy9OlZsb+RPr27KtChZh1ooihuvCuVnwBIR+bOI/Bl4F/jftEmVZSSLoYClUPY0d3CgtTPt8rgtlIBv+FoobZ1hFm3el/bzOBl17u96OBN2VcerhaK48ToC+C6sosSH7OUE2xU2LLAslL41ytQqy4Bbtyv9bi/3XWFJfndehWOhDMVq+d8+v55rHlzWr1Ye3/n3e3zkD2+m3NXY3BGitTMUXQ/ZbW6cRpzDnVCk+/enForixmv7egHOAuY6RYoicmwqBRGRcSLyooisFpGVIvIVe/tIEXlWRNbbj2WOTCJyi4hsEJHl6WztYkju85o5ugSAVTvS3zCvPRQm1+9j2ffPiWZ3AVSV5NEZirC/dejNlr/x2XXcv6iW9f1QDi+vtYaGPrd6V0plmX390xz3k+ej6y0dlnLxqUIBIBRWC0WJj1cb/vdYDR8/Ya83AbemWJYQ8HVjzAzgeOBqEZkJXAs8b4yZCjxvrwOcj5UsMBW4Cqu1S3rwEEOpKg5SURRkxY7GtInh0N4VJpjjo7Qgp8f2GTWWlbTw/fS7gdJFU7t3Zeg0yKxLwwjmpo5uC2Vvi+XGbGoPJTp8WOFWKGqhKG68KpTjjDFXA+0Q7e2V0lYqxpg6Y8y79vMmYDUwBmvUsONeuxu4xH5+MXCPsXgLGCEiNamUKSobyWMoIsLsMSWD0tK7vSsSbVvv5piJI6ksDvKb59enXYZ00dzh7aLd3hWOXuD3NHeyZW8LZ930Mk+t2JlymZzzNPZD2R3KuF1eaqEobrwqlC4R8WMXOYpIJZC2WxMRmQgcBbwNVNuFkU6BZJV92Bhgm+tltfa2lGOMSRpDAZg9upT1u5t7BM3TQXtXmLyc3n+6HL+Py48dz+q6Rto6h+Y/uleF4q63qW/u4K7XN7NhdzPXP7IiZTEkR4E48ZTGNlUoAKGIWihKfLwqlFuwgvFVIvIT4DXgp+kQSESKsFrff9UY05f/KN4VvteVRESuEpFFIrKovr5+QDIZk9xCAZg9poRwxLBmZ9OAzuOV9q4weYH4HV4nVVhzz7YfGPwJksn40l8Xc0sC6ynHb33BLR4VipMeXZjrZ09zB0u2We3UdzV2sGnPwNO33RlMdQfabZks5dw6RJV0qglplpeSAK9ZXvcC12ApkTrgEmPM/akWRkRysJTJvcYYp3XLLseVZT/utrfXAuNcLx8L7Igj++3GmPnGmPmVlZUDkssAPg8aZdboUgDeS7Pby7JQ4iuUsWX5AIM+8CsZkYjhyRU7uenZdXH35/qtn2Jzh7cLlGOhzKgpYU9TB2t3NnLMxDIANh5E1leLK7trR4P1HToWildld6jjZL1B91weRQHvWV5/McasMcbcaoz5nTFmtYj8JZWC2JlkdwCrjTE3uXY9AlxhP78CeNi1/TN2ttfxQIPjGks1EWM8OLysi3lFUS5Ltu5PhxhR2rsiPfp59ZTBGklcm2GFsmpHI//zj6V02m1iticJnOfaFf/NHgPf9U2W9TBzdAmN7SHauyLMG28plJ0HUYvjDrxHLZROtVDcqIWiJMLTgC1glnvFjqccnWJZTgI+DbwnIkvtbd/GKqq8X0Q+B2wFPmrvewK4ANgAtJJ4guRBYwzJ07ywAvPzJ4xk0eY0K5RQmKJg/D9dVXGQHL9Quz+zLq+v/mMJ63Y1c+m8sZw8tSLpADLnGuW2EPqivqkDn8C06u4GDjNHlxDwCTsbBq5Q3Art2w+9R0tHKGqZtHqU7VBHs7yURCTrNnwd1kU9X0Qa6b6sdgK3p1IQY8xrJL5snxnneANcnUoZ+sJrBcL8iWU8tXInuxrbqS7JS/6CAdDeFaGiKL6F4vMJY0bkZ9xCce7mn1xRx8lTK3qk4cajy3ajeE3N3d3UQXlRsMd3PHpEPtUleQenUDp6Bt5/8sRq1z5VKND9twK1UJSeJGsO+VNjTDHwS2NMiTGm2F7KjTHXDZKMGceYvptDujlm4kgA3kljS5COPmIoYLm9HIVyx2vvc9/bW9MmSyKcRKsHFteyu7G9R/wh3p2+c5HyGqeo3d/GqJI8Koq6s9dHleQxqjSPuoNQKI5C++0njuIXHzmix/u3d0V6BO2HK2HN8lIS4DUof52IlInIsSKywFnSLVy24KUOxWHm6BLyc/xpdXu1dYXJCyT+040ty2e77fK64bFVfPuh99jfkroeYy+vq2d3U98X7fauMEdPKKMzFOHV9Xt6KIp9MbIYY6L9srwoFGMMK3Y0MGt0CZMriqLbx4zIZ1RpXkpiKNNHFXPZ/HHMqLE6IDiKRd1eQ6MOZSi2HzoU8BqU/zzwCtYUxh/ajz9In1jZhZduww45fh9HTyjjjY170iZPX1leYCmUPc2dPWpRUuUCa2zv4oo7F3LVPYv7PK6tKxyt3N/Z2N4jeytWobiDvMlcY2ClBh9o7WLW6JIe3QJ8PqHGdnkN9ILiuLWK86z3PcoO9F9ypFXipIH57hiKT7LTQvn+hU0tAAAgAElEQVTCPYv48G1vZFqMYYnXOpSvAMcAW4wxp2MVHQ6sqGMIkmweSiwLplWwblczdQ3piWNYlfJ9WShWppe7FiVVXYjfq7VSojf1MUzMGENbV5iyglzKCnKoa2jr00Jx++STWSjbD7Tx6TveBmDcSOtz3nDxLH724TkAjCrNo60rTGPbwCwJJyhflGeFF//r9MN45Zunc+T4EQDsH4Ru0tmOcwNQGAykvYh3IDy7ahdLth5g9zDqvJ0teFUo7caYdgARCRpj1gCHp0+s7KI/FgrAgmlWvcur61JvpRhjaA+FE6YNQ3ctypa93QolVXNSNtqKxLmDj0dHKIIxkJfjZ1RpPnUH2ntkb/VSKKFuayJZ4Pv6h1dEG0iOGWF9zk+fMJGPHzsesBQKQF3jwJR5U3sXIlBgf7+5AR/jywuiwf9djTpvxlEoJXk5Wd2RIbbA9eV19Xz2roVs3Zt9Rb+HCl4VSq2IjAD+DTwrIg8Tp4jwUKU/MRSAw6uLqS4J8vL61BtxnWHrYh1MEpQHWLuru2I/VRbKAbuTcVsfd6bOXWt+jp8aO0je0hGiINeSOVahdPbDQnErxhpbobipcRTKAAPzB9q6KAoGenUWHuUolIMI+B8qOIWNFUW5HMjidjTbY9y8D71by4tr63l+TWq7UyvdeA3Kf8gYc8AY8wPge1gFiJf0/apDB8sd712jiAgLplby2vo9Pdw5qcC5I+zLQnFqUdbUdSuUVFkoTj+rfS2dCQOyjrLJz/VHg+RN7SFqSvPw+yShy6skL5DUQnHXQMSrxak+iAt/W2eYh5Zsj1o+biqLg9b7qhslaqFUFgc50NrZrxk26cYppAXYFlOL5dy41OtU07TRp0KxZ5H0WID3sHp5FfX12kML0y8LBeCsmdU0tHXx9qbUpg87VduJChuhuxZldV13K7RU+ZMbXHekTiV5LG6lV1OSx76WTp5csZOa0nzKCnJ7xSEcJVFZHKS9K9KnG6XJrhP555dOiLu/qjgPkYFZKK9v2ENTe4ivnT2t1768HD/VJcGD6hN2qOD+e0VMdrX1d48/WLerZ0+9/S3WPh2TnT6SWSiLgUX2Y+yyKL2iZQ/GWBkt/eHUaZUU5Pp5YkVqu8E4LqGCYGILBSy3lxNr8AnsSpLm6xV3C/dE7VQcCyUvx9/DLdUZilBemMve5vguL8dV11dK8oGWLq48cSJHTxgZd39uwEdFUXBAxY3O93XSYRVx988ZU5r2Pm1DASdtuKLIstr2DWKigpVintjqb3Qpt3c276crHOHV9fU0tHVFb2RUoaSPZIWNk4wxk+3H2GXyYAmZaSIe29e7ycvxc8b0Kp5esTOlxXCOS6iwDwsFugPzYLUnSVUwuaGti/F2dlWirspOKml+rp9zZlVz6byxAEyvKaasMKeXheK4KRyZE8naFY7Q1BGirKDvUTw1A6xFccd+4jGzpoSN9c093CrDEbeFAoOb+fbDR1cx9TtPJkwLd7L0Lp03lvqmDv7xzjY+fcdCLv/TW1FXq7q80ofXOpQF8ZZ0C5cteG1fH8sFc2rY29KZ0pqUVrueozC3b4XipNQCzB5TSn1TR0pSPBvaQkyrLmL8yAJeXLObE376PM+u6hnkdF+YS/JyuPGyufzzSyfw7QtmUF4Y7BVDcWIxjqJKFKdwEgJGFCTOMAMrjrJie0O/ffvtoTC5AV/CUb/jywsxJnmjy0Mdx0JxbgBig9/p5M9vbAZIOObasY4/MLcGn8Db9vTSlTsao4qvPkXWutIbr1le33Qt3wMeZTgVNtK/tGGHM6ZXUZqfwz/e2Zb8YI90Wyh9u7yOsusmgGgX3mN+/NxB353tbe6gvDDIEWNLeW3DHuoa2nl9Q0+FGS9x4OgJI8nL8VNRlMvuxo4ed5gd9h2/M8slURHmAfuCkEyhHDdpJHtbOvnXku39+mwdXZE+OxBMKLcU3pa9wzuO4gTlD6u0Clc31Q/+95GoxstRKMV5AUaV5LF0W3fHiq6woSDXz96Wzh4t+JXU4TXL6wOu5WxgNjBscu8sC6X/KiUvx8+HjhrDMyt3paz1iRND6SsoD3DkuG6FcsRYa05LU0eIh5bUDvjc4Yhhb0snlcVBJld252RsiJk/0p3l1fvndVh1MU0doR5Bc0ehlBcFqSgKsjlB4HuH/Zqa0t5ZWG4+d/Ikxpbl81Q/41fJOhA4FlSyzsmHOo7LqygvwJgR+azfnd6BcvFIZMW2u+J3Y8sK2Lavp+I5fFQxxsDeFLYiUrrxaqHEUoulVIYFpvcgSM987JhxdIYjPNTPu+VEOAWCBUlcXu79M2pK+MqZUwF4btXuRC9Jyv7WTsIRQ2VxkMOquhVKbDaNOygfy4xR1l3tyh3dGWgd9vHBgI/JFYVs2hO/Ct+5kI8b2bdCscYIlLFqR18DP3uTTKFUFgUJBnxsHe4KxbZQAn7h6AllPLtqV9R6HCwSZfG5FcqYst6/k+n272+3FqimBa8xlN+KyC328jvgVWBZekXLIgYYQwHrYj533Aj+tnDrQTes+/7DK/j+wyuB5BYKwO8uP4pvnns4fp/wP2dP4xvnTGPh5n28OsCCS8ddVlUc5CiXBbS7qYMGl0+7r+D27DGl5OX4om6y6x9ewZ9e3QRAXo6PSRWFvJ/AQtm2v5Vcv4/q4uRjAaaNKmZHQ3uPrLRkJGtp4/MJ40cW9OhAMBxx3EUBn/DR+WPpCEX40WOrBuXczv9hoiy+HgolTj3R4fb8nGTNTZWB4dVCcacOvwl8yxjzqbRJlWX0t1I+litOmMD63c28uHbg1gHAPW9uiT7Pz+07hgJw0RGjufr0w6Lrnzt5MlOriviffyzrFRh3eGPjHiZe+3i0xYqbh5fuQMS6WI8tyyfHL1E30I3Pro0eF42hxJExL8fPcZPK+fMbm5n1/ae4+80tvGN3Zg4G/EyqLGRPc2ePepem9i5+8vgqnlm5i+k1xQmD5m6i45hrvaf5tof6tlDAcnuphWJbKD4fp0yt5KNHj+W5Ven3gIfsLhHQl4ViZxgmslDs7tGaOpwevMZQ7nYt9xpjXk+3YNmEGUDasJsPzB3NmBH53PbSxoOSw5m7PlDyc/3c/LEj2dPckdAF9/hyK+7wwuqeyq+tM8xdr7/PJUeOYUplESLCuh+fz3NfO5UF0yr528KtUSUQdXkF4l+cj55gJQm0xBQwOi4voIeV8vqGPfzp1fd5f08L584a5emzzhs/okeWjxfau8IJZXYYN7KAbftah3V7dCeGErAV++TKIhrbQ55n2QyUdle6dqIYSre71cfUqt6113PGWDca6vJKD15dXheJyBIR2ScijSLSZE9wHBYcrIWS4/fxhVMm8c7m/Qc1eCtZZpcXZo8pZWZNCY8vj9+KzXGlxf7D7mnuoCMU4YQp5dFtIkJuwMfnTp5EV9hEYxZtXWGCfaTfXnhETY8sNIdgwB8d6bt2Z/fPy50i+pGjx3r5mBTn5TBzdAnv9EuhRAj24fICK9OrpTM8rIO6oUgEnxD9+44qtepRBjqH5pFlO3jiveQJFO6096QxlICfoyeU8fFjxvGdC2ZE9xcGA4wszE1Zoa/SE6+3vL8GrgDKXZMbS9IoV1bR327D8fjYMeMZWZjLTc+sG9DdrTEm2uLiNx8/8qBkufCIGt7deiBu6qUTJ9kS49ZxYhElcboMO4H2NbYSaO8M9+mSm1JZxENfPon3f3oBr3zz9Oj2YI6P8SMLKMz19wio77FlWvr9s/s1VvmYiSNZsm2/5xTRZEF56M70Gs5ur1DEEPB1XzoOpn8awH//bQlfvvfdpMc5yqIoGEgYQ2nr6q4lEhF+dukRfGFBzxrsquKgWihpwqtC2QasMMPUzrcslINTKfm5fr5y5lTe3LQ3GksJhSO9Um4372mJq3BaO8OEIoZrz5/Oxfawp4Fy/mzLbfTUip299jl3btv2tfLyunqO+tEzNLR2ReeLlOT3TgaoLA5SXpgb7R3W1tV3e30HEenh53asmsNHFbO6ronmjhBN7V3sae6gOC/AiCQV8rHMGl1Ke1eEzR6D6B2hiGeFMpxTh0PhCAF/9//DxHLLTfnA4oGnpDu8vmEP5978StybHSc+MrGiIPrbiCVRLdHPL53Dbz9xFGD9XrW4MT14VSjXAE+IyHUi8jVnSadg2YQVQzl4Lj9uPJMqCvnpE2sIhSP8891azrrpZR5easUzVmxv4LRfvcRvnl/f67VOfKI0v++iPi9MrixiUkVhr4JE6K5G37avld8+v579rV28sr6+TwtFRJhRUxJtxdLamfxO38Hvcos5Snvm6BIWbt7H7Ouf5kt/fZc9zZ1U2n2j+oOTIro2QYuYWNo6w9E5KIlwOhAM50wvy0Lp/ruNtrOpHlqynWXbDvTrvdw3T80dIV5au5u1u5q4962tvY51LBRHgW2sb+G//7aEh5du52dPrgGsv2G8397HjhnPB+aOBqwGohqUTw9eFcpPgFYgDyh2LcOCg42hOOT4fXzrvOms393MXa9vjnYidirpnTv8O157v9dro21HUqBQwKomX/j+vl59xhzF1dIZjrrYlmw9EH0eT6GAdfFeu7OJUDhCfVNHdAb7QJg7tju+8tqGPWze2xJtRNgfDqsqwic94zF90doZSpo9l5fjZ1RJXsLiy+FAKGwIxCSI3HnlfABeWLObzXta+PlTazz1sHMnZmzf3xa9qYjX0cFp0ePcKNz52vs8smwHX/n7Uv7w8kZaO0M0d4aSptRXlQSpb+rIqrb7hwpeFcpIY8yHjTHXG2N+6CxplSyLMKZ/I4D74txZ1Zw1o4obn13LY3YgcuH7+2ho64q2Rm/uCPXqu5VKCwXg+MnlNLaHerS4d87jBMydAV3rdjVF56DEc3mBVW/TEYqweW8LOxraonetXvjMCRN6KKDz59Qwtiw/6l5auaORiuL+K6i8HD8TKwoTNrGMpbUz7CnxYUZNcY/CzOFGKBLpYaEAnDG9miPHjeCV9fV865/Lue2ljXELS1ftaOyxfZ+r83Tt/tbo7yxegN9xeR01voxgwMcjy3omlmzfb42adsY3J2J0aR6hiIlrpfzx5Y3cvyh1rZKGG14VynMick5aJcliUhGUdxARbrhkNu1dETpDEU47vJJQxPDY8h3ROe3G0CsbrKHN+scrTdLHyisnTinH7xMedf1ThiNW4P/4yeXkuvzQa3c1RV1eie7+Zo62cjTe297Azob2fimUH108m0XfPTu6XhQM8Mo3T+fezx8X3TYQCwVsy2lXcoXSGYoQipikHQgA5owdwfrdTbR2Zs8ckMEkFDa9FArAgqkVLNvWbc3Ga8lywS2vcsEtr0a/uwNtboXSFv2dxUsLdgflP3bMuF77aw+00dweSto41WkbtCmm1mpnQzs/fXIN1zy4PLqtrqEt5UPyDmW8KpSrgadEpG1Ypg0fRKV8PGpK8/n1x46krCCHb5xzOEdPKOPGZ9axaPN+FthzVO57u6cPOdUWSlVJHufNHsV9C7dGG046Qc7KoiAz7QKwKZWF1Dd1sHVvK0XBQC9Xh8PUqiIKcv387e1tdIUNk2w/90BxhoQ5162BKpTDq0vYuq816cW/NdrSJrmFcsSYUiKGfrd2yTYeWlLLeb9+pd+NEkOR3i4vgHkTyoiY7t5u62MSTtwuJscydk/o/OPLG6PZc31ZKHk5fq49f3rUgnWo3d9GswcLZYqtUGKLd1e7XKPGGBa+v48TfvoCt7+yqc/3U7rxWthYbIzxGWPyh2XaMAdX2BiPS44aw5Lvn8PsMaX85EOzaWrvYm9LJzNrSvjiqVN4csXOHpX1jkLpb6ZTX3z+5Ek0tYd4wDbx//WulRxQmp/DLR8/ilOmVvCfC6YAsGjLfkr6+EcN+H3MG1/Gws37yPELZ8+sPmj5fD6Jpqcm69+ViOk1VjPA1XV9WymOL9+LQpljN9tc1o8q/Gzkf/6xjDU7mzy7BB1ig/IOTuzLGZgWm9pb51IS7++xFIczv+TLp01hR0M7K7ZbF/UDrV293L5upV+QG+CVa07n9WvP4BPHWtZK7f5WS6EkiaFUlwQpzPWzMaZLsnsCaX1zB1/5+xKgu9i3v0QihgcX1w6r+TnJRgBPtx/nxVsGR8TMk2oLJZbpo0r4ySVzmFpVxIfnjeGqBZM5vLqYb9y/LGr672vpwu8TCj1c8Lxy1Pgy5owp5d9LtlO7vzXaj2nO2FLGlxfwl88dxxkzqgCr7qI4QUDe4UunTaG8MJdffmQuZYWpUXyXHzcegDNnDExBOa37FyYpcGzz2HQTrLqL6pIg79X2L6MpW1nSz8ys2LRhh7LC3OjQLYAdMXNj3CnyzggAx0K5bP646HgAh1iF5LjSil03NmNG5PPTDx/BxPKC7hhKEoUiIkypKuplobjlfX71buoa2qksDrJmZ+OA0sRfXlfPNx5Yxi+eWhPd1tIR4rp/LT9ke4kls1Cc1OAb4yy/SqNcWcVg5IJcdsw4nv3aqUyrLiYvx8+tn5xHW1eYT9/xNtsPtPHimt3MHl2SsuQAhwuPqGFZbUO0T9jYsvweLSsqioLMHmMZo4kC8g4nHVbB4u+dzSVHHVydjJvvXDiDxd89K2F2WTIqi4NMrSrizU17+emTq7n1xQ1xj2vp8G6hAMwZM2LIWyjOzUnt/v5dLGMLG924J4XGVrNvtBVKUTAQba0THceQF2C23X9trm0Bxrq9+orjjS0rYGN9C80doaTTTMFye63f1VOhbHN9D0+vtGq0fvbhOeQGfNz83Lpe72GM4a7X30/YadnJSnthTben4a1Ne/nbwm184e5FPb73Q6WuKdkI4Kvsx9PjLGekUhARuVNEdovICte2kSLyrIistx/L7O1idz7eICLL020tDXQeysFwWFUR/3fFfOoOtHPSz15g7a4mPn7s+JSf54LZNQDc/somRhTk8Oo1p/f6rKdOq0z5eb2S4/dRPsD4icMJU8p5ZV09f3x5E798em3cu8PWqMsr+cUI4JiJZby/p4XdA2w3kg102T25+jtxMZGFAkQ7QVcUBand39rDbbWqrpERBTnMm1DGlr1WP7Qm13wf54Zlrt3J+u8Lt3LPm5ujr29qD1GY648bvznt8EpW1zXSFTY9LJhEzBpdws7G9h6/hTV1TZw6rZJcv483NuyNynL64VW8u2V/r/dYXdfEDx9dxX//fWncczip/u6O187vbFltAyf//EUiEcPbm/Zyyi9e5N8x/fXW7Woacj3jkrm8jhGRUa71z4jIw/bFfGSKZfkzcF7MtmuB540xU4Hn7XWA84Gp9nIVcFuKZYkhNYWN/eXEKRXc94XjAasRn1OYlUrGlxdw7ETrTzm1qiiu4jx7pvUTcLoCDzVOdPUfA/j6/ct6dDOG7oQEL2MBrPesAODNTXtTIOHgE4mYaKxjx4E2Hl66PXqX/NLa3X0WgyaKoQBccpT1G73oiBoipntWTjhieGntbk4+rIJJ5QVs3tPCp+9YyC+eWouI1SUhaDfmdAao/XvpDr7/8Mqo66upvSuh2/UTrpstpx9cXzhKa/k2y8ps7wqzsb6Z2WNKOGr8CDrDEfw+oawglxk1JWzZ19qr+eXeFivtOF6BMMA+23JpddXa7I+xZuoa26PW2hPv1bFhdzOrdjTy+PI6zrn5FZ5eObTmGCZzef0R6ARrrjzwM+AeoAG4PZWCGGNeAWId3RcDd9vP7wYucW2/x1i8BYwQkZpUytNTtvTGUPpizthSnv7qAl74+mmeL3b95SPzrYaLJx1WEXf/3LGlnDilnJ9fOict5083x02yFEqOX/jhB2fx6vo9/PWtLT2Ocdr5l3ssyJw5uoSSvABvbhyaCqXTldm1rLaBr/x9KZ+/exH7Wjq58q53OPfXr/BYggaiVtpw/EvHebNrePO6M7jyxImAlc21p7mDBb94kT3NnZwzaxQTygtp6gjxmn0hdjwAXzptCqdOq+Sy+WOjXacB3n7f+o6b2kMJrY/CYCB6YzRrdPJ8oVmjS/AJLLfjYAvf30coYpg/cWS0AWpBjh+/T5huT3mMHSS3y+4HlqiA07FQWjvDUUstdmzEul1NHLBvbva3dnLx717jglte5er7rN5my4dYnC7ZFcpvjHEu8h8DbjfG/BP4p4jEt/NSS7Uxpg7AGFMnIlX29jFY/cUcau1tA0vHSEKqKuUHyuGj0tuU4NJ5YynJCyQMfItI1FIaipQV5vLof51MYdDP5Moi/v7ONn759FqeXrmTb557OKdMrYx2Dx7pMZnA7xOOm1zOG0NUoThjlwtz/dEMty37WtjX0l3sd9tLG7noiN5WcVtXmJI+0tdrSvOJRKz57avrmhARth9oI9fv47TDK1mcwNKtLsnj7v84FoC/fP443tq4l2v/tZxVdY1cfOQYGtu7+nRn3f6Zo3lr0z5PNVAFuQGmVRez1I6DLd6yHxE4duJIuuzvxnHHzbBT6NfsbOIoO8kDetbKhCOmRxshoMfY77qGdiZVFHKgtYtgwMdNlx3J1fe9y9a9rVELbM3Opl4jHWJTr7OdZBaKX0Scv+CZwAuufem5XfZGvMt73NsEEblKRBaJyKL6+oFNKjzYeSjZjt8nnDe7hpyDnLeSzcwZWxotaLvkSOsiuby2gfsXWQ0N9zZ3Upjr99yDDCxX2tZ9rUMyoOqksk6q7LYEfCLRu+p540ewqq6RxvYu9rV0cuJPn+dBu/mjlUnV9/fU3eSzkeW1BygKBlhzw3mU5OX0yOYK+IQffGBmr9ePGZHPpUePjQbPwxHD2p1NjC0r6HWsw4iCXM6b7W1eDsARY0tZXnsAYwzrdjUxsbyQwmAg6g776llTo7IUBQOsiekqsddV5T/3h8/0yhpzstIAzv/NK/zlrS3sa+mkpjSP82ePIjfgY/uBtmhw3jn+3s8fx5UnTmTcyPwh99tKdgX5G/CyiDwMtGGN/kVEDsNye6WbXY4ry3500iVqAXep7Fggrn1ujLndGDPfGDO/snJgweVMWyhKavnsSZO46bK5LJhWyRsb9hCJGPa1dDCyn/3HzphuGcxPr9yJMYanV+7s18jhTOK4vCZXdGf0tXaGo00vz501CmPg1XV7uObB5exoaOcbDyzDGGNlUnlIXphRU8KSrQd4ZuUujplYFp2fMtFV9Lrhfy/gypMmJXyPqdXFrNvVZLvOOjlzRlXCY/vL3HEjONDaxea9razc0ci0auu7qC7J493vnc1Xz5oGuJRjTFzJHVNp7gjxz5huy80doWhBbntXhO/9ewVrdjZSVpgbLdx9cHEtz8UMs5s+qpgffHAWZ82oZusQG+aWLMvrJ8DXsQLmJ7va1/uA/5de0QB4BGsOC/bjw67tn7GzvY4HGhzXWDrIRJaXkj5yAz4+PG8sHziihr0tnazd1cTelk5GFvYvm2xCeSEzakp4euVOHlhUy3/+ZTE3PdM7vTQb6bB9+icd1jNh4b3t1n3i6dOrKA4GuPq+d3ludXdgeFVdo6dqdLAUSmc4wu6mDq6wYypgXaAXfufMHrNwEjGtqoja/W2s3GHJlUr37/GTrc/+o0dXsnVfK6dO61ZWsa7P6aOKWVPX2OPi3tIZ6pEmvbqusUcRY1NHqNfUyHW7mhlpFyfXlOZ1x+5c53POPX5kAa2d4biNMrOVpD4OY8xbxpiHjDEtrm3rjDHJJ+L0AxH5G9a8+sNFpFZEPoeVBHC2iKwHzrbXAZ4ANgEbgD8BX06lLLFEUtS+XskunCSE1zfsYW9zZ49/aq+cN2sUi7bs58kV3Y0+hwKOhVKcl8OKH57LI/91EgBLtlrxjeqSPL5zYfekwwe/eAJgjYb2UjwIcI7dLWHBtEpOO7ynZVFVnMf48sTuK4dptgL520IrZDquD5dXf5lcUcjo0jxeXFvPxPICPnhk4izK6TUlNLaHetTWtHaGKSvIZdn153DhnBpeXGs1xnRo6QhRVpjDjy+ZzY0fnUuVXfTpFP3+4IOzOGN6FXPGlPKry+YCVgzHuXmdbY8r7m/haSbJZBykB8aYTyTYdWacYw1Wf7FBQw2UQ4/RI/KZXFHIy+vq2dfS6Sk7KJbzZo/i5ufW8eJaKz63qq6Rvc0dB107k2467L5YuX4fRcEA00eVkOv3say2gYBPKA4G+NC8MdQ1tPOBuTUcVlXMEWNLefy9OiLGW3p1dUker3zzdMoKB95/7tRplUyuKGTptgPk+n2eiha9IiKceFgFDy6u5YunTunzMzkt81fXNUaD/s0dIQpy/ZTm53DdBdN5/L06HlqynV99dC5+n9DcbineTx0/AYDH36vjhTW7KbMbvE6rLubOK4+JnuOpr57CGFdCwRFjSynJC/D1+5dR84U8jhjbe2x2tnHoRmFTSCq7DSvZxQVzanh9wx52Nrb3O4YClgumusRSHifbFs9QyPxyLJRgjnUJyA34ou6kiqIgPp8QDPj5n7OncViVtf30w6uifb+8XtjHlxckbdnTF3k5fm6xJy3OGIDCT8Y15x3O7Z8+msvm9+5e7GZmjaVw3X/b1s7uqvyxZQX8+mPWaG5348uiYPdnd5RSItfq9FElPb6rYMDPg186EZ9Ys1+GAqpQPGBI3TwUJbu49OixOGUEA3F5gdV+P9fv47sXzaAkL8Ar6waWTTiYuC0UhxPteEqi9jOnTO2uU0pXTVQ8Zo8p5caPzuX3n0x9Q4yq4jzOmTUqmjCQiMJggBMPK+e51buicZTWjnAPxXrcZKsO5u339xGJGFo6e2bDXX36YVx3/nQ+PM97a6Jp1cWcO2sUL66t9zSwLNOoQvGAWiiHLpMqCvniqVMYWZjLnDEDcymcO2sUq284j+mjSjhrRjVPrdiZ9bNSOsNWUD7oSpM+c7oV89iUYBql2+XipNYOFpcePbaHOygTnDWjmi17W6NNLq1st+7vr6Y0nwnlBby1aS8tnSGMoUfyQmEwwH+eOoXqkpJ0LLIAABWFSURBVLx+nffkqRU0tHVFEyayGVUoHshkpbySfq49fzrvfu/saIX0QHCK2i4/bjxNHSH+vSR+lXm24GQjuS2UefakztMPj59enxvw8ftPzuPzJ09iUsXBzbsZipxlF/4+a2e9tXaGe/V+c0ZrO1X07u7LA8Vxpb62PvstX1UoHkjHPBTl0OToCWXMHVvKr59bF+0Plo04lfJODAWsmTYLv3Mmv//k0Qlfd8GcGr57Ue9CxOHAqNI8jhhbynOrdtERCtPcEYoG2B2On1xOQ1sXr9oXf6dZ5sFQXhRk1ugSXlkfv2dYNqEKxQPGoD4vxRMiwo8unk19cwe/fm59psVJSEccCwWsmEJ+CmfuHGqcNaOaJdsOsNKe1lkRY4EcZ9e2OPPuq/rp3krEKVMreXfL/qwvnFWF4gHVJ0p/mDtuBB8/Zjx/fmMzz9hzNbKNeBaKkpwPzB2NMXCHnXUVO5p6zIh8xo3MZ8lWq3akqiQ16eNnz6wiFDG8EFNVn23or8kLGkNR+sm1501n9phSvnTvu6zIwmCqE0MJ+tUa6Q+TKgo5avyI6FjgeDESZ37QqJK8AQ+Gi+WocWVUlwR54r20NQRJCapQPKAxFKW/lBbkcM9nj2VkYS7XPLicrnB2zRV3pgnmBvQS0F++dva06PN4mWefOWEiBbn+lE4u9fmEC+eM5sW1u7O6FYv+mjygWV7KQCgtyOGGi2ezqq6RP768MdPi9CCa5aUKpd+cMrWSNTecx1vXnRnXQplWXcyKH5zLt847PKXn/eTx4+kKG+5ftC35wRlCf00eMFitvRWlv5w3exQXzqnhluc3sHhL9vT56gxFCPik1wwPxRt5OX5GlSYOuPt8kvJi6CmVRZw4pZx739pCKMssXgdVKB6IGKMWijJgbrhkNqNH5PH5uxexqb7vgUmLt+wbFJdGRyhCUK2TIceVJ05kR0M7D8XMn88W9BflgSE0jkDJQkYW5nL3fxyLT4RP/d/b0UrrWDbWN3PpbW9y2i9fjI6MTRedoYi6u4YgZ8+sZs6YUn7z/PoerfKzBf1FecAasKUmijJwJpQXcs/njqUzHOGyP77Jos293V+3vWTFWVo6w3z+7kXR4rh00BEKEwxohtdQQ0T4+jnTqN3fxp/fyL6GkapQvKDzUJQUMGt0KQ988USK8wJ87Pa3+MPLG6O+8I5QmCffq+Pjx4zj8uPG89qGPXzmzoW9pgCmCrVQhi6nTqvkrBnV3PTsOrbuza4RwfqL8oCOAFZSxaSKQh79fydz7qxqfvbkGqZ/7ym+9+8VvLhmNy2dYc6aUc3/fmgOq350LsdPKufrDyzjWw8uT3kbF42hDF1EhBsumUXA5+Or/1iSVa4v/UV5QLsNK6mkJC+HWy+fx22fnMdH54/l3re38MW/vkuu3+dqIR/gz/9xDF8+bQoPLN7G6b96mfve3toju2dXYzvffGAZb23q//wVtVCGNjWl+fz80iN4d+sBfvDoyqyZO6+/KA/oPBQl1YgI58+p4acfPoKHrz6Zc2ZW892LZvToXhsM+LnmvOk89OWTmFRRwLcfeo8zb3qZe97cTGtniD+/sZkHFtfy8dvf4tYXN/Srz1N7KKwKZYhz4RE1fPHUKdz39lZ+8fTarFAqWTMCOJtRC0VJJ3PGlnL7Z+Yn3D933Aju/88TeGbVLm57aSPff3glNz6zjogxzJ9QRkl+Dr98ei2/fWE9F8yp4bL54zhu0sgeN0Hb9rXyyLIdnDmjipEFuSzavJ8Pzxs7GB9PSSPfOu9wmtq7uO2ljXSGInz7ghkZrS1SheIBrZRXMo2IcO6sUZwzs5rFW/bz5zc289Laev77zKksmFbJiu0N3LdwK48u3cG/3t3OqJI8zp5Zzdkzqzl+cjk3PLaKZ1bt4pdPrwWsCvmrFkzO8KdSDhYR4YaLZ5Pj93HHa++zfnczN350bkrmsAxInmwwkwaL+fPnm0WLFvX7def/5lXGjMjn/65IfBepKNlAW2eYp1fu5MkVdbyybg9tXWEKcv20dYX51HETGFmYywOLtvH5UybzHydPyrS4Sgr528KtXP/wSgqDfr574Uw+dNSYpKONvSAii40xni5+qlA8cN6vX2HcyAL+1IdbQlGyjfauMK9v2MNLa+vZsq+Vmy+bS3lRZu5clcFhw+4mvvHAcpZuO8CMmhK+dvY0zpxedVCKpT8KRV1eHtGWR8pQIy/Hz5kzqjnTHl2rHPocVlXMv750Io8u38GNz6zjC/csYkJ5AZ8+fgKXHze+18jiVKNpHh6IGG1fryjK0MDnEy4+cgzPf/1UfvuJo6gqDnLL84MzPVQtFA9oUF5RlKFGjt/HB+aO5gNzR1Pf1JF26wTUQvGEVsorijKUGaysL1UoHjDq8lIURUmKKhQPGNDKRkVRlCQMaYUiIueJyFoR2SAi16btRFopryiKkpQhq1BExA/cCpwPzAQ+ISIz03EunYeiKIqSnCGrUIBjgQ3GmE3GmE7g78DF6TiR0XkoiqIoSRnKCmUMsM21XmtvSzma5aUoipKcoVyHEu8S36uPjIhcBVwFMH78+AGd6OaPHUlxcCh/VYqiKOlnKFsotcA41/pYYEfsQcaY240x840x8ysrKwd0onnjy5haXTwwKRVFUYYJQ1mhvANMFZFJIpILfBx4JMMyKYqiDFuGrB/HGBMSkf8Cngb8wJ3GmJUZFktRFGXYMmQVCoAx5gngiUzLoSiKogxtl5eiKIqSRahCURRFUVKCKhRFURQlJahCURRFUVLCsJopLyL1wJYBvrwC2JNCcVKFytU/VK7+oXL1j0NRrgnGGE9FfMNKoRwMIrLIGDM/03LEonL1D5Wrf6hc/WO4y6UuL0VRFCUlqEJRFEVRUoIqFO/cnmkBEqBy9Q+Vq3+oXP1jWMulMRRFURQlJaiFoiiKoqQEVSjKIYfovOZ+od9X/9DvKzGqUGLIxh+LiBTYj1klm4icLiLVmZZjKCEi2fg/VwQgIv5MC+IgIh8UkSmZliMB0e8pC/8nM/r7ysYf96AjIueJyJXOaiZlcRARn4iMF5HXgO8DmCwJeInIWSLyDvAAWfQbEpGLReRfwI9FZHKm5XGwL45fy7QcbsSiSkReAv4PwBgTzqxU0d/Wm8AdQE2m5XEjIheKyLPATSKyALLjfzKbfl9ZczHIBCKSIyK/BO4EfiIi040xkWy4UzPGRIBO/n97Zx5kRXXF4e83AyFGRHBBRVwquEAwCEZRccMdt7ggSlwod40VNCpRK9Gi3BJLIxqtaNQYozEaEOOCSbmUUSnBiMENF1RcElQQxVJQxABz8se5T9opCFu/7p6Z81V1zevu+2a+6b7d5259219r3E/SzlBuiUjSmpLuB34BnAu8A2xbtlf6+72BS4FbgdWBEZIOTvtKyeeS2kk6D7gW+LWkvhXKXwbMT0sfSftBOccqBbeOksYBF6Tln8AmZTk1R9KmwGXAdcBrwCmSTkr7In8lSj9RZWJmC4CXgAHA1cAlaXvpJbVETzzz3gacDqWXiBqBu81sdzN7HH9D5vYV8AIPbI+a2Tj8wh8PnCCpUwrOhWNmC4HX8fN4NnBj2l56/ko3we7AC8D5LK4FF36szPkcuMPMBprZY8BDwMFlOS2BHsBTZvYAXmj5PTBcUpd0Ey+8QFXF/NXmAoqk4ZLOlbRP2jTazN4F/gRsJOmAlK7Ql49lvPbMbH4LWARMARZIGixpkxK8zpO0p5l9YmZ3pO3Ca08L03qheUnSfpJ6ZTa9AgyS1MHMPsIDynTglIK9zpB0uaQj0qa/mdl8M7sG6CrpqJSufUleg+Hrm/QHwBbABGCGpNMkbV6C05DkNDptbwQ+BaZL6lCUTzO3wyVtn9n0HjA45a/5ZvYEMBG4sGCvSuavrzGzNrEA7fEmkfHA8cB/gEHAapk0x+OlkNK90r7DgHPT518Cs4Gb0rpKOl7fzqTZD3iz4OPVDXgaeB8YVTsOeO3pZuC8tN4BOAiveXYswEvAWfjN+XC8Znkc0DWT5lDg/YKP19K81sJrdSNTuhHAF8C4tN6uBKd1M2kGAFOLPFbp73YFnsSD7X1AQ2bf7cA1mf9ha2AssF5bzV/Nl7ZUQ1kIbAcMN7Nb8XbaIaQ+gMTdwGxJxwBI6leS15GStgOmAb1Tv8VgYDJexcVSDirYa0jaVuNZ4EVJO9TZJctXwGjgRPwiOySz7y5gX0mbm9lXeB/U2ubNKXUlnY/dgQvMbCx+8W8N7JtJcy/whqQR4B3QJXn1BfYGZgK7Svo7XmiYALydvlq3ZpP/c6wGZdJMBN6T9MN6eSzFbRZwf3KZAZya2X0xcKCk3ul/mA/MBdps/mpOmwgokpROyIv4ScDMbgc+AgZIWjtt+xwv0d4uaRawcUles4Cdgc2A9YDngF549XoPSV1L8vrG8cJrAQLm1NMni5nNxjshJ+I3vz0lrW3ebjweL13eJKkbsCuwqN7Nl5nmvn8BuyTPh4A38ALBlpnkPwaukDQT2LAkr9eBPnhgmQ48a2a9gaHAQEkb1qvAshzHqmdK1wmYCiyoh8cy3K4DXgUeAQ6QtEHynIaPPrs+DZI5Bq/R1LWPp6r5a0m06oBSOxGZi+MzoJuk7mn9XmAHvHkHSTvimWkM0M/M7i/J6z5gR2AScJiZXWTe5j0VODKVosrw+sbxMrP3gfVJQadeNO+fMbMmM5uDl6gX4DdCzGyhmV0EPAH8Br9pnmfeeVk3J1vcaTwNWEPS99P6k8CawBrpO33xZrl7gG3M7LaSvMYDnfACwmlmNjKl/wTYKZ3Xop1qx6pjSjcHHzRQ1+ecluRmZgtSnpmIX3NnZtL8Cg8qJwJbAiea2Zd1clPWiwrkr2XRqgKKpJ0l3SCpNiKqKW2vdVA9ipf6t5PUzsyewduSax3hHwMnmNnQPC+qlfB6Gr9R72Zm8yQ1plrDZ3k236zC8doj82v2MbO78nJahldDs9E0rwDPAz0ldarV3FJQGWZmB+UZfCVtU+v0zFzk2QcCJ+FNRXun4/UqXkqsNavOBk43syFm9kGJXq/gQ3L7mdn8Wv5K388lf+VwrACGmtkf8/BZTjc1y18f4yMZt5DUXf7cTpdUWz/VzI4ws5k5evWXdI2kkyQ11Ap2ZeevFaHVBBRJ2wA34M1D+0u6WlKtuWZB+jkJHyY8EBiWvvoR3sGFmb1pZs9WxGtWxmtR3k0Qq3i8ptZ+j5l9UaBXk5mZ/PmhhtRPMgbv73kZeFzpyf08S43pPnMJ8BhwtqSd0vaGFOgXpb85De9X2gwfigve5/PvtH+6mU2pkNe7aX9u+Ssvp5Rmfh5OK+BmKX91kI/mWmRm4/GCy8t4jWCd5PbfHL3aSxqFD/udijelXZX2NZaVv1aGVhNQgP54W/DNwMnAPLz9s1YdvDSdtHvwppuhkl7Cb5AvhFeL8boYb5bsnNKfiTc/3ImXuD/MWyjdbF8DjgSuT15fB7ial6Rb8IET1wL9JU0GPgEeztspJ69H2oLTCrqNxJ8x2SCtn4Z3zN8I9DGzN+ugtgY+quwAM/sdcALe+b9WLZiUkb9WCitxiNmqLMAR+MM8A9J6f7y0un5a3wPvYB+c0v4Z2Czz/XWBdcKrxXsdCvQswKsBH4DQC/gL8KO0vR0+Yqq5V0egc1vwqqLTKrr1yHx/r6xrzl7nAP3T+gbpZ4f08z68WbKh6GO2Sv9X2QIrcSIa8ad6J6eMMgV/3qA3cAXeaV3LICPx0kX22YnG8GoVXnV5TmIpXodl9q8GHJ0u+C5pW4fM/oa24lVFpxzdisz3hzRL0y1t75zW2xdxzPJYWlyTl3kVcEvgHDMbBVwEDMdvPDOAvpK+Zz5K4w38xjQfvK3U6jQtQXgV7pX7yK2leI3Ep9jolfZ/iY/+eR+vNYGPRqoNt67LENIqelXRKUe3ovL9SOBMfXPWh4HAM2b2qaTV8ZFctXxfhWlolkqLCCiShknaTVKt3fxDoEsa6TAWn6JkL7yzbT7+hDd4pJ+k9BxC3icjvNqE11/xTtkjtHhY9Tt4c8lFkubgzXRYKkK2Zq8qOlXdbQW8aqMrOwHPSToBH8W4bfKqdDABqvsKYEnCh87eiT849BY+i+ypwBl4SfbaFMV74hljkJnNlPQHfPx6V7yNdFp4hdcqeG2J9+sMMrMZqTR5Lz4dzQgze6k1e1XRqepuq+j1D2An/Fq4Ku9jVlfKbnNb0kJqv8QnrrsjfW6Hj8y4BR/h8zD+JPR30v4xwFnpc3sy8wKFV3jl4DUaODN93gA4sC14VdGp6m6r4PXT9PksmvWrtJSl0Bl1l0Vq0rgYaJTPL9SJNKeQmS2U9BN8/qFReOQfimeK0fgT0xNT2gX48NbwCq+8vBbi7+jAzGYAD7Zmryo6Vd0tB6+nU9qr83Iqmsr0oUjaDR/50AWfYuAS/Oayu6Ra22YT3nl7pfm0Ao8AwyQ9j5cAcn+oJ7zCq615VdGp6m5V9SqcsqtImWriLsCxmfXr8YnOjgMmp20NeLvkWGCjtG194LvhFV7h1Xqdqu5WVa+il8rUUPDoPkaL562ZAGxsPpdPo6Th5hG+O7DAzKYDmNlMM3t7ib8xvMIrvFqLU9XdqupVKJUJKGY2z8y+ssXjv/dmcfv58UAvSQ/i77x4LrzCK7zajlPV3arqVTSV6pSHr2fWNHy46ANp81zg58BWwDuW8/Ta4RVe4dUynKruVlWvoqhMDSVDEz5c9GOgT4rqFwJNZvZUiScjvMKrrXlV0anqblX1Koa8O2XyWPCXODUBT+EvsCndKbzCqy16VdGp6m5V9SpiqeST8vI3BB4LjDJ/50UlCK8VI7xWjCp6VdGpRlXdqupVBJUMKEEQBEHLo4p9KEEQBEELJAJKEARBkAsRUIIgCIJciIASBEEQ5EIElCAIgiAXIqAEQZ2Q1FnS6elzN0ljy3YKgnoSw4aDoE5I2hR40My2KlklCAqhcnN5BUEr4nKgh6QXgDeBXma2laTjgEOARnx+p6uAb+EPw30F7G9mn0jqAfwWWBeYB5xsZlOL/zeCYPmIJq8gqB/nA2+ZWV/gZ832bQUcBfQHLgPmmVk//K19w1Kam4DhZvYDYAT+jo0gqCxRQwmCcnjczOYCcyV9BoxL26fgkwp2BAYAd0uqfadD8ZpBsPxEQAmCcsjO8dSUWW/Cr8sG4NNUuwmCFkE0eQVB/ZgLrLEyXzSzOcA7koYAyNk6T7kgyJsIKEFQJ8xsNjBB0svAlSvxK44GTpT0IvAKcHCefkGQNzFsOAiCIMiFqKEEQRAEuRABJQiCIMiFCChBEARBLkRACYIgCHIhAkoQBEGQCxFQgiAIglyIgBIEQRDkQgSUIAiCIBf+B0w96u2OZT9ZAAAAAElFTkSuQmCC\n", + "image/png": 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KTLwqkJuBJ4CNxpg3RaQW2JA8sdKLiOlZiZ4uFkhXqNvqUAtEUZSRxmszxYeMMf/nPDDGbAYuS45I6UfvSvTCbMcCSR8FohaIoigjjVcFslJE9gIvAS8CrxhjDidPrPTC0DMIUpSbJhZIWC0QRVFShycXljFmGvAR4F3gfcAKEVmeTMHSil4WSEHAj98nKW9n4lYgnUG1QBRFGVk8WSAiUgOcCpwOHAusAl5OolxpRe9KdBFhXF4WjS0pViA9XFhqgSiKMrJ4dWFtB94EfmCMuS6J8qQl7nkgDqV5WTS2plaBBHu4sNQCURRlZPGahXUc8GfgKhF5TUT+LCKfTqJcaUXveSAApflZHGjt7GePkaFHFpYG0RVFGWG8TiRcISKbgE1YbqyPAWcAf0iibGlD7ywsgJK8AO8ePJQSeRx6xkDUhaUoysjiNQayFAgAr2LFPs4wxmxLpmDpRO8YCKSHC6tnHYhaIIqijCxeYyAXGmMakipJGtN7HghASV4WzR0hukIRsvypaWrc04WlFoiiKCOL1zNfl4j8TESW2stPRaQoqZKlEdGu7b1iIAAHUmiFBNWFpShKCvGqQO4CmrF6YV0ONAF/TJZQ6Yo7BlKaZymQxhQG0oPh7l5YGkRXFGWk8apAphpjvm2M2Wwv3wVqEymIiGSLyBIRWSEiq0Tku/b6EhF5SkQ22LfjXPvcJCIbRWSdiJyfSHncOBaIT9wurACQWgskFFELRFGU1OFVgbSLyGnOAxE5FWhPsCydwCJjzLHAfOACETkJuBF4xhgzHXjGfoyIzAauBOYAFwC3i0hGgmUC+jZTBCsGAilWIGqBKIqSQrwG0T8P3G3HPQQ4AHyi90YicqmH1+owxjzae6WxItUt9sNMezHAxcBZ9vq7geeBr9vr7zPGdAJbRGQjsBB4zeN78kx/WVhASqvRQ6527pqFpSjKSOO1DmQ5cKyIFNqPm/rZ9HfAg/QMF/TmDKCPAgGwLYhlwDTgNmPMGyJSaYzZbR93t4hU2JtPAF537b7TXtf7Na8FrgWYNGnSAGL1T6wsrKKcTDJ8kmILxHJb5WZlaCsTRVFGnAEViIh8uZ/1ABhjeo+1fcwY86lBXvOe/p4zxoSB+SJSDDwgInMHeqlYLxHjNe8E7gSoq6uLa3B4LAvE5xPG5WalNIjuWCB5Ab82U1QUZcQZzAIpGMqLGWM+lqBtDonI81ixjb0iUm1bH9XAPnuzncBE1241QP1Q5PWK6UftlKa4oaJjgeQH/NrOXVGUEWcwBZJrjPm6iHzYPVAqHkTkPGPMUwM8Xw4EbeWRgzVz/UfAYuAa4Fb79kF7l8XAvSLyM2A8MB1YMhwZ+8cJovc0esoLAjS0pIMFkqEDpRRFGXEGy8J6r4hkAjcl4FiD9c2qBp4TkXewOv8+ZYx5GEtxnCciG4Dz7McYY1YB9wOrgceB620XWMKJ1QsLoKIwwN7DHck4pCeiCiRLLRBFUUaewSyQx4H9QJ6IuAPngpU4VejeWEQW9/M6ApQOdCBjzDtYXX97r28Ezulnn1uAWwZ63UQQKwYCUFWYzb7mTiIRg883UN5AcnBcWAXZ/pQPt1IUZewxoAIxxnwV+KqIPGiMudjD6zmdelt6rResFNtRSax5IABVRdmEIobG1i7KCwIjLpdjgeQH/LRrEF1RlBHGax3I2t4rRORHxpiv91r9OtBmjHkhxvbr4pAvLYg1DwSgsjAbgL1NHalRIGGDT6AwJ5Om9tCIH19RlLGN10r082Ksu7D3CmPMhcaY52K9gDHmjKEIlk70FwNxFMieFMVBgpEI/gwfRTmZNHUEiUTiylJWFEWJiwEViIh8XkTeBWaKyDuuZQvwjpcDiMj7EiFoKokqkBgxEIA9TalRIOGwIdMnFOVkYgy0dKkVoijKyDGYC+te4DHgh9g9qGyajTEHPB7jZuDhOGRLG0w/abxl+Vn4BPalSIGEIoYMn1CYnQnA4bZg9L6iKEqyGdACMcYcNsZsxeo9ZVxLvoh47Qsy8ulJCaY/F5Y/w0d5QSBlFkgoEiEzw0dhjq1A2oMpkUNRlLGJ1yD6I1iKQ4BsYAqwDqsT7mB8Lj7R0oduF1ZfXVhZmM2eptQUE4bCtgWSY32NTapAFEUZQTwF0Y0x84wxx9i307FScl+Ota2IfN++vdneN0nV4SNH1IUV47nKwuyUFRMGw4bMDB9l+VYG2P4Uz2hXFGVsEdcwb2PMW8AJ/Tz9pojcBiyNW6o0o78gOliB9JQF0SMR/BlCZYEVzE9VLEZRlLGJJxdWr668PmAB0BBju28DJcBHgJCIzDfG3JwIQVNJf5XoAOOLczjcHqSlM0R+wKtHMDEEI90urCy/j33NqevLpSjK2MOrBVLgWgJYMZE+len2qFuAk+3Ho155QOx5IA4TS3IA2HGgbURlAquVSabPh4hQWRhQC0RRlBHF60ApZz55gfXQ9G5V4uYuY8w6EbkrEQKmA9HyvBgWyKSSXMBSILOqC/tukETCtgUCUFGQzd4UBfMVRRmbeLJARGSuiLwNrARWiciyAYY9fdi+vSwRAqYD/aXxAkwcZymQ7SmwQKwguiVVZWGAfc1qgSiKMnJ4dWHdCXzZGHOUMeYo4Cv2ulgccUH0/uaBABTnZpIf8LPzYPtIC0UwHCHLb32FFQXZ7FMLRFGUEcSrAslz97gyxjwP5PXeyA6iL8IKop8jIt9KhJCpZiALRESYWJKbkhhIZyhCwJ8BWLNJmjtDtGk7E2UECIYj3PXyFoJhnUMzlvGqQDaLyH+JyGR7+SawpfdGR2wQ3b6NlYUFMHFcTkpcWJ2hMAHbAulO5VUrREk+f3h5Czc/vJr7lmxPtShKCvGqQD4FlAP/tJcy4JP9bPtH4BjgHwAi8k0R+aeILBimrCnDsUB8/WiQiSW57DzYHs3WGik6gxECmbYLq9AqJtyrmVjKCLD7kOWyDWkH6DGN1yysg8C/edx2uYj82RhzjIicBpwP/AT4DXBi3JKmkIjpvxIdrEys9mCY/S0jO1jK7cJyWstrLYgyErR0WgPM8ka49klJL+KqRPeAMx7vIuA3xpgHgawkHSvpRA2LfjSIk8q7rbF1ZAQCJt/4CNsPtEVdWBUFaoEoI0dLp9V3zZ+CUc5K+pAsBbJLRH4LXA48KiKBJB4r6XT3wor9Z6ktt/IJNjUMVB6TQHlcrjJHgRTlZJLl99GgFogyArTaFkhnSIPoY5lkndQvB54ALjDGHMJqb/LVJB0r+QzQCwugZlwuWX4fG/eNjAJx/2kDmZYLy6lGVwtEGQmc7KvOYHiQLZUjmQEdmCLyK1yF2L0xxsSMixhj2rCC7c7j3cDuOGVMOYN4sMjwCbVleSOmQDpcf9qsjO5rgIqCbI2BKCOC0wGhQy2QMc1gFshSYBnWDJAFwAZ7mU93nOOIZ6B5IA7TKvLZOEIurI6gywLxd3+FaoEoI4WjQDqDqkDGMoNNJLzbGHM3MB042xjzK2PMr4BzsJTImKB7pG3/20yryGfnwfYe1kGy6GGB+HtZIFoHkhQm3/gIP3h0TarFSBuci6qO0Ji5jlRi4DUGMh6rE69Dvr1uTDBQJbrDtIp8jBmZQLr7T3uwrXsKoVajJ4cu201z54ubUyxJ+hCKODEQtUDGMl4VyK3A2yLyJxH5E/AW8IOkSZVmDFaJDjC9wtKvIxEHae/qViA7D3ZXwI/2avShFmIGwxF+/9JmmjqSO8r3gE567EMobH1XaoGMbbyOtP0jVhHgA/Zysu3aGhOYwQpBgMllufh9wro9zUmXxx0D+cjCSdH7TjX6aAyk3790B9P/8zE27vP++T3yzm6+/8gafvrEuoTKcrC1ixU7DkUfN7aOvs8z2TgV6GqBjG28tnMX4FzgWKcoUEQWJlIQEZkoIs+JyBoRWSUiX7LXl4jIUyKywb4d59rnJhHZKCLrROT8RMrjxosFEvBnML2ygFX1TckSI4pz1ffPL5zCqdPKouudavT6QyPfGXi4vL39IKGI4YX1+z3v88aWRgDWJFhpX/PHJVx82yuE7ZOkWiB9cVxYaoGMbby6sG7HapD4EftxM3BbgmUJAV8xxswCTgKuF5HZwI3AM8aY6cAz9mPs564E5gAXALeLSEaCZbLwEAMBmDu+kJW7Die9J5aTe5+T2fPtTinLozDbz3Pr9iX1+Mkg234vrZ3e4zfOAK3GFuu2vStMKAHdYd/ZeRiA/fbrqgLpi+PCUgtkbONVgZxojLke6IBob6yEtiYxxuw2xrxl328G1gATsEbnOu6yu4FL7PsXA/cZYzqNMVuAjUBCraKobLYG6a+ZosOc8YU0tnYlfTKg48LK7qVAMjN8XDx/Ag8ur2fL/pFrq5IIHJ3bMgQF4gzQ2t/SxeG2IGf/5Hmuu2fZsGXJy7I+V8eSa+7QpITeRF1YaoGMabwqkKB9dW8ARKQcSNqlh4hMBo4D3gAq7UJEpyCxwt5sArDDtdtOe13Csa31AV1YAHMnFAGwctfhZIgRxUnjzc7s+/VddnwNABv2Jj8WM1QiEdOvhdBlrx+KAnHathxuD/L4qt3saerg6TX7hv3eC7IzAdh92FJQ7qy2ke64nK6EwpqFpXhXIL/ECp5XiMgtwMvAD5MhkIjkY7WC/3djzEABhVin8z7/bhG5VkSWisjShoaGuGTqDqEPrEFmVRciAivrR0iB+Pt67CaOywFIyYTEwbjhvreZ9p+PxXwuaKfKenVhhSOG/S1dlOZZhvAza7rddi+sj+97dijItho0OBaI0/cJuhXdWMexQDQGMrbxmoX1V+BrWEpjN3CJMeb+RAsjIplYyuOvxhinFcpeEam2n68GnDPFTmCia/caoD6G7HcaY+qMMXXl5eVxyeVcdQ5mgeQF/NSW5fHuzuQqkPZ+XFgAJXlZ5GRmpKUCeeQdq5tNJMYMCeeE1OLRXXSwrYtwxDB7fCEAr29u5NiJxRRm+4c93MtxVToWiFuptXXqCRM0BqJYeM3C+osxZq0x5jZjzK+NMWtE5C+JFMTO9PoDsMYY8zPXU4uBa+z71wAPutZfKSIBEZmCVS2/JJEyOQzFabFg0jje2n4w5kkyUTgWiLuNiYOIUDMup0d9SCrY19TBmf/9HMtd6bAOsWIKQ3VhOe6rWdWWAmnqCFFdmE11UU70xB8vjgy7D9sWiKvuZigutiMZtUAU8O7CmuN+YMdDjk+wLKcCHwcWichye3kvVhHjeSKyATjPfowxZhVwP7AaeBy43hiTlF9zdy+swbc9YXIJB9uCbN6fvILCjlCYLL8PXz+zGCwFkloL5KF3drOtsY2fPbUe6K7mhth1FY4Ly+sJel9UgXQ3SKgqyqaqKJs9w1QgzXZh4qPv7uEDv365R3+xti49YYIrjVe78Y5pBuvGexPwDSBHRJrojjt0AXcmUhBjzMv0nyl7Tj/73ALckkg5YjPwPBA3dZOtMpU3tx5kWkXBIFvHR2cw0ieF103NuFyWbTuYlGN7xWnpsnZ3E52hcA/Xz8G2vmmxTntwrzGQ3hYIWHUwHcEwq3fHX4tjjKGlM0R+wE9LZyia0uvQqm1iAAg7LiztxjumGayZ4g+NMQXAfxtjCo0xBfZSaoy5aYRkTDlDsUCmlOVRmpfFm1sPJE2ejmA4ZgaWQ824HJo6QhxuD/KPZTv5wK9f7tH+ZCTosI+3r7mTf761q4dl0dgSS4HYMRCPMYat+1vJ8AmTS/Oi68YXZ1NZmM3+ls4eFs9QaA+GiRj44qJpPHzDaVxeV9PjeY2BWATVAlHwHkS/SUTGichCETnDWZItXLrgpRKd6DZC3eRxI6BABrZAAHYdbOfu17byzs7DPLFqT8KO/+SqPTy+cuDXaw+GmVaRz/iibJZsOdDD9RPLAumOgXjra/XursNMr8jv8TlMLc+nuigbY7prRIaKE8QvyPYzd0IRJ04p7fG8WiAWIZcFkm6pzR3BMPt0rMGI4DWI/hngRawpg9+1b7+TPLHSi+5uvN7mP59UW8qOA+3sGGY2UH+0B8MxU3gdaqKpvG3RWen1hxMXE7n2L8sGLdhrD4bJzcpgwrgc6g+197BADrT2VRJOXUFHMOKpmnzD3mZm2+4rJ5V3SlkeVUVWO5d44yBNtgLJD6HXAyQAACAASURBVFje3RMmlwBw44UzgaFVyh+pGGMIRQyZGYIx6Zfa/INH17DwB89wKMaFipJYvAbRvwScAGwzxpyNVeQ3vGT7UYSXeSBuzjjaShcebj1Cf3QEI4O6sMCqBXH6OSWqQ6/XzrftXZaVVFWUw56mjh4n3gOxgujh7qvY1gHcRK2dIc792QvUH+6Ivs+/f/4UfvyhY8gL+LsVSJxXoI6iK7SLCSeV5rLpB+/lIydMsmXXk5Lzm8qzlWy6xUFW2HGrJ1ftTbEkRz5eFUiHMaYDQEQCxpi1wIzkiZVeeJkH4qa2LI8JxTm8mDQFEo7OQo+FuxbESZmN16XTm50Hui2Z5gGUSUcwTE5mBtVF2ew+3DGoBRJ0XcW2DOAmenv7oWjL/PHFlgKZUpbH5XVWSVB1obUuXgvEcWHlZ3fnl2T4hMIcPwG/Tyc+0p3C6yjZdLPKxtsXEdsO9Gzns3FfMwu+9xR/fGVLKsQ6IvGqQHaKSDHwL+ApEXmQGEV7RypDiYFY2wlnzijn1U2NPU6MiaIjFBkwBuKuBXFO3Inqz3W4vfvkX3+o/5Nph50pVlWYTVcoEq1LKcrJjGmBdIUj0c93oBPS2j3dGVbVtgJxU5jjJyczI+5aEMfV57iwHETEShEepbNWEomjQMryLdfhwRgXBKnEqdvZ1SuVfVV9Ewdau/jza9tSIdYRidcg+geNMYeMMd8B/gur4O+Sgfc6cuiuRPdqg8CZR5fT0hlKSjC9vStE7gAKBLprQRJtgbhdWLsO9R/jaQ+GycmyLBCAFTsst8JRpbkcaIttgYzLtU5IAzUvdCutBZOK+zwvIlQXZcftwvrr69soCPiZMK6vcqosyGbvMGtMjgScFN5yO76WbrGGJvsiZ0cvBXLQdj8m46JurDKgArFncfRYgHexemHlj4iEacBQXVgAp08vIzvTN2i2Ujy0doaj/uf+qBmX28cCSUS2jNsC6X2F56bdzhRzrIRH3rXamNSW5cWOgYRMNOA/UJzBOVn94/OnRJse9qayML5iwj2HO1ix8zCfP3tq1D3jZkpZHhv2Nadd1tFI46TwOgrkYIwLglTiXOSs3d0UjdcA0QuXeFO8lb4MZoEsA5bat72XpckVLX3oDqJ7VyG5WX7OnlHBYyv3JLytSWtXiPzA4BaIUwuSk5lBVyhCU/vwfdVNLgWyc4DBVR1dVgxkQi83U0leIKbLIxSJRNOPB4ozHGzrYs74Qo4/aly/21THWY2+y34/7uJEN/NqijjYFkx5lX+qCUddWI4CGTkLxBjD6kGGtjW1h8jO9NHaFWbJlgM8tXovz6/bF7VADrR2JbXV0FhisELCKcaYWvu291I7UkKmmngsEIAL5lbR0NzJsu2JrQpv7QyR68ECcTi6yqqIj9et46apPYgIzKwqYNWuJg61dcWMWVguLB/lBQHuu/YkAI6bVExJXiYtnaE+cyQ6QxHGF2fjEwbM4T/UHoy6uvqjqiibvU0dQz5JODL1lyI90/4cNzYkf+59OuO4gMo9WIyJ5sHl9bz3ly/xzJr+M6xaO0NcMn8CxbmZ3LtkO5/981I+8cc3o3KGImZEld6RjNc6kDNiLckWLl0YSiW6m3NmVRLw+/jX27sSJktnKEwwbPoEeXszuaxbgRxbY80p2dY4/CFTh9uDFAT8nFRbytJtB/jo79/gm/9a2WObYDhCKGKi7VZOqi1l5XfP52+fPYmSPPuqtZcV0hmKkJvlpyw/MKCiO9QWpDg3tuvKoboom1DE8HaMRo4D0Rntchz7bzGp1PpMtzemtlFlqnGKCHOzMigvCCSt3ikW79qzdjbsi63EjTG0B8NUFGYzd3xRD9nWuFrcOL3UlOHhNQvrq67lv4CHGEuFhPat10JCh/yAn4vmVbN4eX3CWok4rTRyswZ2Yc2o7O7DtWCS5e659i/L+PuyncM6/v6WLsoKAsweX0hHMMKq+iZW9DpRt0cHXnXLmB/wk52ZQWWhpUB2udxfkYihKxQh4PcxYZBGkI0tnYNaIGfNqCDg9/Gb5zcN6b11xJDbTXl+gOxM37DbxY92nCysDJ+P2rI8No/g9EvnYi7cj3Xp1KRkZ/qYUJzT47vavL+VErvotEEVSELwmoX1ftdyHjAXGDNVOl7ngcTiihMm0twZ4lE7iDxcnKD4YEF0f0b3V3tUaW5U9lsfWzOs4zc0d1JREGBqeXcOxdbG1h4uKacPVk4MJXe0rdjW7emeGuhUMgcyfUwpy+t3HG9zR5CmjlC0/qM/Jpbk8pGFk3hxQ8OQMm6c1uT9KRARYVJJrioQO4ie6ROmVuSzfm9zvyf0ROPUHvWnANzD1mrG5fRxrzkXVmqBJAavFkhvdmIpkTHBcP4aC6eUMKUsj/99c8fgGw9CKByJnlwHc2EB1NmB5oLsTB74wqnMqi7kQGvXsK6+Glo6KS/IZppLgUQMbG7oPuk7FkisjsE143IoCPijrgjodh0F/BnUluWx+3BHjzGyDo5lMrFkYAUCMH9iMV2hCFuHcHXcMYgLC2BSSZ66sMKOBSKcVFtKc0coIb9vLzTaCqG/RAvnO8yx2+j0ZkaVo0A0HTsReI2B/EpEfmkvvwZeAlYkV7Q0Is4YiLWPcMUJE1my9UCPq+54+NOrW7n6LmtmlhcFcsfHj+ebF81ianke8ycW86uPzAfgew+vHjAVtf5Qe8wrynDEsLepg/L8AEW94hDuKYwDKRAR4aSppby4voHmjiC3PLKaRT99HrAGZE0psxRTLCtkm33inuhKEOgPx9JZO4TPfKBRwQ6OBTKWU3kdF1Zmho9FMyuYUpbHj59YOyKdeZ1j9Fco2u0+9fXJAASYUJxDfsCfsNY+Yx2vFog7lfc14OvGmI8lTao0I540XjdX1E0kJzOD3744NJ98bzbs7Q4cji/OHnT7svwAnzm9Nir3tIoC/uPco1m8op7FK2I3EjjcFuSUW5/lew+v7vPcP5btpK0rzMIpVoPBb71vNh9ZOJGA38cPH1sT/XM78Z7sfuI0p00rY9ehduZ950l+99KW6FVldmYGteVWe3a3AjHG8IW/LuNbD64kNysjehU5ENMq8snO9PH2du+B9I4BRgU7TCrJoT0YZn+MlvRjhbDtwvJnCPkBP1+/YCaH2oJDUtbx4vzG+kvTdl8ExLJASvOzqCgMaAwkQXiNgdztWv5qjHkl2YKlE/Gm8TqMy8viIwsnsXh5/bBGzbr112BxgP74wtnTmFqex71vbI/5vBPc/tuSvs//+fWtzJ1QyPlzKgH41GlT+OGlx/DjDx3DwbYgT622wmIDWSDQHdTvTcDvi8732LSvW4Ecbg/y6Lt72NfcySlTywY8wTtk+X3Mn1g8pE4AA40KdjjKlm/7gZELHKcbQZcLC7qbdw53EqQXHCW/r7kjZtfmqAWSlUF1Ud//yPjiHCoKAurCShBeXVjvE5G3ReSAiDSJSLM9oXBMMNReWLH4zOlTAPj9S/E3cnNXgedmDe7CikWGT3j/seNZsvVAzHqLPU2WAonVYbWxpYtZVYV9LLEL51aTmSGssgu8OgZRILPHF/Jv50znvNmVPQoCA34fOVkZTC7N7dHzan9L99XiDYumeX2rLJxcwqr6wwM2fXTTEQoTGGBUMFgBemBMB9KdGEimnahRWWhZw/E2mnxi1R4+/oc3PLkFnUSHiCGmFei2QDJ8wl8+vZCbL+6eyD2hOIeKgmwNoicIry6sXwDXAKWuyYSxy3WPQIY6DyQW44tzuGxBDfe+sT3uvPlDdiuGn3z42LjlALhoXjXGwOMxhky5fcvGmB59jpragxTm9K3ByPL7mFZREM2zb+/qDmTGIsMnfPm8o/nd1XX84/OnRNc7HYZnVRf2yNlvaLZk+OtnTuTYiX37X/VH3eQSIoY+Y2n7ozM4cJNKsK62RWB749itRneysBwLpDQvi8wMibuB5ef+soyXNuyPXiANFEvpDEaiqbi7Y8y46XDFQABOn17O1SdPpsj+3VYVZVsWSIJa+4x1vCqQHcBKM0Y/8Yj9tge4MPXEv583HZ8P/vuJdYB1gn5oRX0Py+LVjfv7vZI73B7knJkVfOj4mpjPe2V6ZQHTKvJjTil0BxeXbTvI/Juf4t43thMKR2jtCsfsEQUwq9qlQAaxQHrjuIyc21nVhWxtbGPr/laWbTsYtUCc1hlecVqSePXNDzYqGKz4SFVhdp9W4WOJqAXisz4rn0+YWJLLHS9siquxYpb9ve882E79oXZm/tfj3PbcxpjbdgTDTLYLOmO5zNxZWG4evuE0bv/oAjIzfFQUBmgPhnuMGFDiw6sC+RrwqIjcJCJfdpZkCpZORLXmMBVIdVEOnzmtlsUr6lmx4xBrdjdzw9/e5sN3vApYFdxX/f4NTvzBMzH3P9we7JP9FC9nHl3O0q0H+7QUcSuzJ+2Yxl2vbIl2yC3Iju06m1VVyL7mThpbOqMpuF5iFUC0Y69zInEmDZ71k+e57DevRud/OO3DvVJeEKA0L4t1e7x5W9u6wp5cgxNLcke0+jrd6C4k7P5DnD2jAmDIxZvQXRS782Bb9HN1LrJ60xEMM7nMikPVH+7g4394g2888C6n/ehZ9hzu6E7g6JVJN7Ekl/fOqwagosD6vakba/h4VSC3AG1ANlDgWsYGTiHhcDUI8LkzaykvCPCNB96NBnjX723hcHuwh1+9saXvj/twezBqig+XE6eU0BmKRNusO7ibJT7yzu7oOkeBxHJhQc+r/T2HO/D7JOpqGAxniqDTU2t+rzbtD62oJ8Mng1agx2JGVYHn9Om2rpAnq2lyaS6bG1rHrAskWkiY0f1/+Or5MygI+Hll036aOoJcfsdrbNjr7XN3RhPsPNgeHSncHx2hCNVF2ZTkZfH65kZe2rCfe9/Yzs6D7Ty1Zm90Zn1+Pxc6QLTrsw4HGz5eFUiJMeZSY8y3jTHfdZakSpZGJCKI7lCQncnNH5jDqvomvr14VXT9C+sbehTj9U4/DYYjtHSGKM4Z+kk0FgunlCACr21q7LH+cHuQOeMLGZebGc3IamztoqHF+rMV9meBVFvXE2t2N1F/qJ2qouweV6gD8f1L5nH69LJoQL0sP8ANi6ZxeZ3lqnNaUAwU3O6PGVUFrN/b4qmxYltXmLxBuhwDzJ1QRGNrV9w+/9GOUyPk7naQnZnBdWdNZeWuJh5aUc+SrQf43iN9ux6s3dPEHS9s6qF8HYtm58H2Hhcwvb+zYDhCOGLI9mewYFJxNOvPoSsUiV7oDFQn5aT3uqdrOtz18hY+cufr/e6r9MSrAnlaRN6TVEnSmOGm8fbmwnnV0VTYk2pLKMsPcO8b29jk6vL64oae43CdP1ZRTnzZV70pzs3i+Enj+MdbO3sUDTpWzslTS6PrwhETVWj9WSCl+QEqCwOs3HWY+kMdQ0oznlaRz18+fWIP99FX3jODH3/oWKbY7oqhxj8cZlYV0B4Me8qaau0Kk+PBhTVvgtWc0mtwPp3xOuPejZPG6++l0E+dVgbAc2v3AcSc+3LzQ6u59bG1vOAa9+zIsGV/aw95Gnu1IXH3KvvSOUf3ee1dB9tp7Qzh98mAqdg143LJyvD1+L9F5Xt4Na9tboy2fl+563DM7RQLrwrkeuBxEWkfk2m8cUwkHIwffHAe58+p5DOn1fKlc6fz+uYD/PjxtZTlB7hoXjUPvLWrR7GTE5sojsON0x+fOm0K2w+09biScxTIB4+zrv4dc3/pVqslfX9BdLDah7y4YT/v7jrM0ZWJmTc2vcJ6Had1+FCZUeW41gb/ubZ3hcgbpEklWO46v094d9fQuv2mG69tauSY7zzJqxv3D2k/dyGhm9nVhWT5fTy9xlIgTkDbjTPM6S37giQYjkS3e2F9A/94q7vZZ28Xk7vVzLyaIv7j3KO5yI5rANEBankB/4D/1QyfMKUsj00NPRMh3MprS2Mrq+ubeN+vXubDd7zW72uNdbwWEhYYY3zGmJwxmcZr3yZOfVhX7L/9eB3nzq7kqoWTWDjFSjmdUpbLl99zNB2hMN9ZvCqqvA5FLZDExEAA3jO7kppxOdz1ilWb8vjK3WzY10Jxbhbnzqrgq+fP4PfX1JGZISzdZsVrCgewgE6bVsaB1i7ag2Eur5uYEBmn2QpkXJzJA0dX5uMTojUqA9HaGe439dhNdmYGR1cWjHoL5LGVVozr+fUNg2zZk96FhA5Zfh+zXF0CYmVkOZag06PMiXvdsGgak0pyWbmr+3vq7SJ0kjMcS/VL507n11cdxw8+OI/jJhWz61A7LZ0hT21+asvz2NzLstjtGpe8paGVnzxpBfIPtHbFPbb3jhc29elWfSQx2EjbmfbtgljLyIiYeuKdB+KVDJ/wyyuP433HVHPjhbOYWp7Pf5x3NI+8u5t77IpxxxpJVBYWWD7sK0+YyJItB9hxoI3r7nkLsAY/iQjXnz2NY2qKmTO+KFq01d8YWYDLjq/hvNmV3HrpPI6p8V6vMRCXHDeBvKwMPnt6fPPLcrP8zJtQxOubrVjPQLGQ9mCYPI8FmsfUFPHursOjOpDu/KY2NwwtJdmpAHfSeN1Md40R2N/S1SPLr6kjGM18cmbTOKm0E0tyWTTTyuRyXGO958LEygQUEa46cRJzxxex82A7LR3eFMjU8ny2HWjrMd623jViYFNDC29uORCtO7ovjmaR4Yjh1sfWcvFtPRt3fObupcMeq5AuDGaBOKm6P42x/CSJcqUV8c4DGQpVRdn8+qoF0UDydWdM5awZ5Xz7wZX8+bWtPPLObgqz/dEU10ThpDb+1L7aErEmKbo58+jy6P2CAf6cuVl+fnd1HVcunJQw+Y6uLGDVzRcw1447xMNJU0tZvuMQP3p8Lef9/IV+Z7O0doYGnbPiMK+miENtQbaO4s68zsmzfoDRxLGIpvFm9P0/9HZdums1Ntnp2FWF2WzZb2WxOQokP+Bnznjrt12cm0mGT9jbywJx4oCxLmImleRyuD3Ihn0tA2ZgOUyvzCccMT3iG45Sy8nMYOnWgzR3hvjQggmcPr2M25/bGPPi47bnNvJkjHoq6JkS71xodATDPL1mL//v/1bw4PJd0fWvb26MmXmZ7gw20vZa+/bsGMuiRAoiIneJyD4RWelaVyIiT4nIBvt2nOu5m0Rko4isE5HzEylLb0yio+ge8PmE2z+6gEUzK/nWg6tYvKKeSxfUeK6t8EpteT4zqwr413KrueKzXzmrT5zjrBndCiSeTKhUc8rUMoJhw2+e38Smhlb++Xbfq79wxESnInrhRLuhpGPZjEacdjX1MSq6ByLajTeGBdJ7Vv16VwNQp4X/e+ZU0tQRYvfhjqgrKz/gjyZMBMOGmnE53PfmDj5z99JoIWlTNJW873d0wdwqfGIF4os9uHmdCxJ3F+k1u5spycvilKmlLLFT7MsLsnnfMdU0dYRiJmL89xPruPYvy2Iewz2LxFEmTjcJgC/dt5yXNuwnFI5w5Z2vc9lvXu2x//Pr9qV9qvFgLqwTRKTK9fhqEXnQbutekmBZ/gRc0GvdjcAzxpjpwDP2Y0RkNnAlMMfe53YRSeyZNQbJcmH1R26Wn998bAGnTSsjLyuDT506JSnHcccrJpX0bZWeKHdUqqjrdVK79dG10Uwhh+6rW28KZGp5PuUFgT5p0KMJxwI51Bbkz69t5f6llpvm8ZW7ufPFTf0OiQrHKCR0cH4rN144E+g5Rvap1XupLcvjjOnWBcm1f1kadZvmZ/ujBYJFOZnMqCxgf0snT6/ZG+2Y4PQ0i5XIMbEkl0sX1ETvD8aU0jwKAn5W7OyOT7y76zCzqgs4qbY7A7G8IMDMfhIx3DNrYlm17rhJvR1f6T2LfcfBNvbabj2n+8Ltz29k58E2PvHHN/n8PbGVU7owmAvrt0AXWHPRgVuBPwOHgTsTKYgx5kWgd+vUi4G77ft3A5e41t9njOk0xmwBNgILEylPT9ms21Rce2dm+PjTJ0/gpa8vis7kTjSX2X+8C+ZUxTwpZPiE265awDcvmpWU4yebvICfk2qtupf7P3cypflZ/OrZDUQiJmpdOimjpR6r3UWEU6aW8uqmxlEbB3HHJ7714Cq+9vd3APjO4tX84NG1XGPPnumNM+WxdxovWL/XrbdexHVnTuWo0lzW7G4iHDFc9MuXeGnDfs6bUxlVFO6AeUHAT2leFt9470zu+sQJPdLI39xinRYG64bw/mPHA3hyd/p8wryaomgixIHWLlbvbuKkKaXRcQVgZSEeXVmAiGWhuHG3/YnVl8ttgThuwoO9UpM37mtht8uFePPDq/nx4+s47UfPAf3Pfk8XBrvcyjDGOCf1K4A7jTH/AP4hIsuTKxoAlcaY3QDGmN0iUmGvnwC4q3122uuSgjMPxDfSJoiNP8Pnuao7HopyM3ntpkUDHuOiY6r7fW40cPenFtIRjFCUk8n7jx3Pr57dSO03HuWKuon86EPHRP3PpXne04VPri3lweX1bGpoYVrF6GvM0BmyGhO6T3QtnaFox9uX7b5slYXZHG4LkmV3S27rsnqGDebOnFVVyNo9zWxqaIlmwV1RNzHmnI7JZXmICNeeMRWA2rI8Tphcwo+fWBftZeak2fYXJD/z6HKe/I8zoqnfg3FMTTG/f2kzHcEw79iWyAlTSnrMmykvCJCdmcGU0rw+FojbvbR+bwu15T2Pe8gVA3HchAdsC+Tez57IzQ+tZseBNupdsZ5ne1nGXaEIxpiElhAkksEskAwRcb6tc4BnXc8lpqItPmJ9mjEvA0XkWhFZKiJLGxqGlq7oEElyFlY6UF2UQ2CASXyjnYA/I5oC/eHjJ0bbcCxeUU8oHImeRIeiqJ3CuRfWD62OIl3oCkeijQkd1u9tpqk9GI17vbHlAOGI4dyfv8AHfv1yNPCdHxg8zmA1xWyNuvme+o8zqC3P7/E7O7m2lJsunBltDe/g8wlzJxQxq6qAzQ2thMIRlm49SG1ZXo8K+N5Y1oK3P+qxNUWEIoY1u5tYb7ddmVlVQHZmBufMrOAzp02JxhxnVvdtieN2R113zzJ+9mTP/l3NrrYs33pwFZfc9krUEpleUcCE4hx2Hero01ftpgtncvenFnLZgho6Q5G0Hn41mAL5G/CCiDwItGONskVEpmG5sZLNXhGpto9ZDTjqeSfgLjSoAWKO2DPG3GmMqTPG1JWXl8faZFAS0c5dSR8mleby9JfP5IeXzqM9GObdXYeH7MICy9c+o7Ig6qO/b8l2nlu3b5C90ofOYKRPvGB1fRMRA6dMLSU/4OfRd3bzb397m4bmTjbsa2HlriZaO0Pke2j5Mqu6AGPg24tXMb4om6muK/QvnGVZGnd8/Hg+d+bUfl9jemUBXeEIW/a3smTLAc6eWdHvtkPF6bm2bNtBVuw4TGVhIFqo+4dPnMA33zc7uu3MqkK2HWiL1q2AVTfk5v96peY62zr91ZbvOMRdL28FrEyzCeNyWLO7qU/jyNryfM48upz32Vb/jmEMoUs2g2Vh3QJ8BSvAfZqrnbsPuCG5ogGwGGsOCfbtg671V4pIQESmANOB2A7bBNA90jZZR1BGmqNK83jPbKudzKubGqMWyFAbNp4/t4o3tx7guXX7uPGf7/KpP72ZcFmTRVc4Qm5WBjcsmsYxNT2zkkrzAiyaWcHjq/bwyLu7o/s8u3YfLR1WtfdgzB7fnXJ+/aJpPVxeXz1/Biu/e/6ghbFOWvCLG/bTFY70UELDpboohyllefz2xc08sWoP59m/h1jMrLKU4XpXg0gniH7pcZb3fPfhjh4NJFs6Q2Rn+pjuSm3e09RBYbafzAxfvyn5Tl85J+bpns6ZbgxaiW6Med0Y84AxptW1br0x5q1ECiIif8Oatz5DRHaKyKexgvbnicgG4Dz7McaYVcD9wGrgceB6Y0z/U2iGySiNkSqDUJofYFZ1IS9v2E9jSycF2f5oS3mvXDCnCmPg50+tB6zfSqyAajrSGQyTleHjK++ZweIvnkZFQYC3tlsta4pzM/neJXOj2z795TOYP7GYZ9ft81ztXTPOKg48tqaIq3rVBomIp9eYVpFPZoZE54PEyhIcDqdNK6OhuZPMDB83LJre73axZsu02BbILR+cx28+atVVn/fzF6M9u5o7LFffL66Yz++uruMKO9txnO0m/XDdRL79/tlcf/ZU/nBNHcdOLGZCcQ4146z3OKU0j8JsPy9t3O+pGWgqSGUcowfGmI/089Q5/Wx/C1ab+RFDLZAjj9Onl/GnV7aS6ffF1bBxVnUBR5Xm9mhr8vKG/Xw4Qa1ckklXOBKdAgkwZ3whz62z4oTj8rIoysnk/647mbL8AFPK8lg0s4KfP72eyoLsaNHfYPzu6rphBYFzs/x88ezp/PxpS0HXlufF9Tr9sWhWBX95fRuX19VER/PGYkJxDvkBP6vqu7/ntq4QPrF6c10wt4rz51TyxKq9rNhxiBNrS2ntDFGQ7ae2PJ/a8nzrwmJpt2srwyd80pWaf9r0sh4Xqz6fcP6cKv5v2U7GF2Vz03vTLwtyaJdbYxSTwHkgSnrxgWPH0xWO8OL6hrgy3UQkmgY9q7qQsvwsXhlic8JUYIxVOJnlCkjPc9X7OE00T5hcEi3wWzSzAmMsN4wXFxZYJ8mBgt5e+LdzpkXvD6XLsxfOnlHBs185k+98YM6A2/l8wgmTx/HShv3R80Frp9X6RkQQEX502TGIWIkHgN3YsVtBL5hk1SPNHh87zTjgz+hTKPzDS+dxwZwq/rZke4+2K+mCKhAPJLsXlpI65owvZKadthnPwCqAT546mZNrS/naBTM4dVoZL2/cH+0Xla6EIgZj6NH2/IzpZdH7sbofz64ujNZgeC24TAQiwktfO5tXbkxo84soteX5niykc2dXsq2xLVqb0doZItelIIpzs5hZVcgbW6yss959ueZOKOJf15/Kjy6b51k2f4aPS46bQFNHiLdt92I6oQrEA8noi/8H2wAAE51JREFUxqukByLCTz58LOfMrOD9x8ZX61KQncnfrj2Js2dUcNG8ava3dPXJ5083nKtZd8znuEndFfuxUrp9PmG+3VzwlKllfZ5PJhNLcpmQYOtjqJwz0wqyO+MPWrtCfZpvnlRbwrJtB+kKRWjqCPbp2zV/YjHVRUN7HydPLcUnVl1OuqEKxAPdFoiqkCORuROK+MMnTuDi+cOvRV00s4Kqwmz+9OrWtK5Qd/pguS2QDJ9w7qzKqEUWi19cMZ+vnj9jwIylI5WqomyOqSni6TW2Aunsm4124pRSOoIR3tl5iH3NnVFX4HAoyslk/sRiXtqgCmRUEk3jTbEcSvrjz/Dx2TNqeXVTI0/2GrmaTnRbID0tjd9dfTyP//sZ/e5Xmh/g+rOnDTlb7Ujh3FmVLN9xiH3NHRxo7YpmVDk4TTZf3LCfA61dAwbmh8Jp08t5Z+chDrcNfYJkMhmbv4IhojEQZShcc/JRzKwq4OaHVvfbOj7VOH2weisCtbIH5j1zKjEGnli5h/0tXZT1Kjwdl5fFzKoCHn7HqmuuLBy+BQJWfCpi4IUN8XXTSBaqQDwQjYHon0vxgD/Dx80Xz2XXoXa+eO9b0bqAdKIrhgtLGZyZVVbSxT/ftkZOx0o2OKm2NDqkK1EWyHGTxlGWH+DxlbsH33gE0V+PF4xR60MZEgunlHDzxXN4Zu2+6LCudKIzRhBd8calCybw9vZDdIUjlMeoHTpnVne7leMmjuvzfDxk+ITz51Ty3NqGHm3kU43+ejwQMRr/UIbO1SdP5qoTJ/GHl7ewPM3mYscKoive+NhJR0VnzMSalXPK1DI+eNwELq+rSegI6kuOm0B7MMzi5THb/qWEtKlET2cM6dtOWUlvbrxwJs+u2cfX/r6Ch244LW06HsdK41W8kZvl5++fP6Xf5zN8ws+vmJ/w49YdNY4ZlQX85fVtXHHCxLQ4J+mvxwNGLRAlTgqzM/nBpXNZv7eF7yxelTapvU4QPV0UmjI4IsLHTj6KVfVN0Z5lqUYViAcMmoGlxM+imZVcf/ZU/rZkB79+duOA2764voHH3k1+oFSD6KOTDx43gXG5mfzi6Q2pFgVQBeIJywJRDaLEz/97zwwuPW4CP31qPf/z9IaYlkhzR5Cr71rC5//6Fq9vTu6sdY2BjE7yA34+f9ZUXtqwnzeS/Bvxgv56PGBQH5YyPESEH33oGC5dMIGfP72ebzywsk9679+WbI/e/8zdS/nWgyt7DDBKJBoDGb1cffJkKgsDfPeh1dH59KlCfz1eUP2hJIDMDB8/+dCxfP6sqfxtyXYu+82rvL65MapIHlu5h2Nqivjfa0+iZlwOf35tG5+++00OumaWJwpN4x29ZGdm8N0PzGH17iZ+/9KWlMqivx4PaAxESRQ+n/D1C2by+6vr2HmwnSvvfJ1zfvoC9y/dwfIdh1g0s4ITa0t5/N/P4BdXzGfZtoOc/4sXeWbN3oQG4Ls0iD6quWBuNRfMqeJnT61LaUBdFYgHjDEaA1ESyrmzK3nmK2dy+0cXkB/w87W/v4Mx1nwKh0uOm8ADXziV4txMPn33Uq6+awmr65uiz3cEw1x552v8179WDtmV0RVWC2S0c+tl86gqyuYL97zFrkOpmYKpdSAeMEYtECXxlOUHeO+8as6bXcl9S7bj80l0NrnD3AlFPHzD6dzz+jb+55kNvPeXL3HG0eVce3otja2dvL75AK9vPsA7Ow9x/dnTWDSzwtMAp+YOK7aSNcxhT0rqKM7N4s6P13H5b1/jqt+9zv2fOzlhrVO8or8eDxg0BqIkj8wMHx8/eTIfPfGomMVhWX4fnzptCi9+9Wy+ev4MVtc38bE/vMFX7l/BhOIcfnHFfPa3dHHtX5Zxyq3Pcutja9mwt7nHaxxo7eJL973Nbc9tZF9TB/98axcLJhWrBTLKmVVdyN2fWsj+5k4+dMerrNvTPPhOCUTSpbBpJKirqzNLly4d8n43P7Sa+5fuYOV3z0+CVIoyNDqCYR5+ZzcPLt/FB44dz4frJhIMR3hu7T7uX7qD59Y1EI4YasvyOG92peUuW7OPO17Y1ON17v3siSM+GEpJDit2HOKzf15KS2eI718ylw8eNyGhleoisswYU9dnvSqQwfnuQ6v4+7KdvPsdVSBK+rOvqYMnVu3hydV7eX1zI8Gw9R+/YE4VX1w0jbte3kJteR5fXDQ9xZIqiWRvUwfX//Utlm47yNkzyvnPi2YzrSI/Ia+tCoT4Fch3Fq/in2/t5B1VIMooo6kjyEvr9/P29oN87KSjmFyWl2qRlCQSjhj+9OpWfvbkOtqDYT50fA2fPb2W6ZX9T5n0Qn8KRIPoHjBGmykqo5PC7EwuOqaai46Jb967MrrI8AmfPm0Kl8wfz23PbeKeN7Zx/9KdnDK1lG9eNJvZ4wsTejyNoHlA60AURRlNlOYH+Nb7Z/PajYv42gUz2NbYRnZm4k/3aoF4QLvxKooyGinND/CFs6Zx3RlT8fkSfxZTC8QDOg9EUZTRTDKUB6gC8YRaIIqiKH1RBeIBjYEoiqL0ZVQrEBG5QETWichGEbkxWcexMp1VgyiKorgZtQpERDKA24ALgdnAR0RkdnKOZtQCURRF6cWoVSDAQmCjMWazMaYLuA+4OBkH0hiIoihKX0azApkA7HA93mmv64GIXCsiS0VkaUNDQ1wH0m68iqIofRnNCiTWKb1PXxZjzJ3GmDpjTF15eXlcB/r2B2bz5H+cGde+iqIoRyqjuZBwJzDR9bgGqE/GgXKzRvPHpCiKkhxGswXyJjBdRKaISBZwJbA4xTIpiqKMGUbtpbUxJiQiXwSeADKAu4wxq1IslqIoyphh1CoQAGPMo8CjqZZDURRlLDKaXViKoihKClEFoiiKosSFKhBFURQlLlSBKIqiKHExpmaii0gDsC3O3cuA/QkUJ1GoXEMjXeWC9JQtHWUClSsehiPbUcaYPpXYY0qBDAcRWRprqHyqUbmGRrrKBekpWzrKBCpXPCRDNnVhKYqiKHGhCkRRFEWJC1Ug3rkz1QL0g8o1NNJVLkhP2dJRJlC54iHhsmkMRFEURYkLtUAURVGUuFAFoiiKosSFKhBFURQlLlSBuBBJz8G1IjIr1TL0RkS+IiLvse+n1ecm8v/bO/sgq+oyjn++C4gohGEqARaT6IiiYBZEiWSphU2iNeXbiJo0kzqazsTgmIYtmC+9OFlKQ03J5LtOr0Q50yimWGam+VKmqSjTkCUCUsyQsE9//H7XPW0XYu+ec8/D7vOZObPnnHvO7md/97n3Ob+X8zsaWVh34+bJpYHH2IKIr1aowyUSCCBptqSlwOS6XXoi6RvAcknja1YBQNKxku4G5gNzAMzJSAxJH5D0GLBY0iXgw81rfHmLLYj4aoU642unfh5IX5AkMzNJRwELgdeB6ZJeNLN1dXsVdo0C1gFHS/q+mW2uwwkYAnwBmAlcCewCvFvSEGBL3R8kScOBS0jv5W+BpZJ2M7NLa/JxF18eY6vhRcRXb31cxNeArIH0+CC9AHwImAdMAw714CVpUN79G2AxcBqwf11OZvZv4MdmNiM/yGsdcLKZve7gw90BDAdWA4+a2WpgLnCSpANr8HEXXx5jq+gV8dUrHzfxNeASSH4M7g8kXSRptJmtMrM1ZnYP8DIwU9LYGr0ulDTGzLbmZ71/GPghcC9wsqSPSfqfSc0qdrpI0lvN7OG8f4iZ3Qc8L2lWO1yauJ0r6eMAZtYFGLAX6YOOmT1PKrfOfHxb2oc9xpfH2OrhFfG1416u4mtAJRBJJwJnANeRMvWlkqYUDrkZOICUyYvnVRocPbwmA5dIOjxflf3OzF4BngUuAK4AKg/WJmX1eUmNNtYtkkaRZjbeWrVLD68Rkr5Fau5YKmkwgJm9DPwRuLBw+MXANEkHt+Mq1mN8eYytJl4RXzvm5i6+BlQCIRXsYjO7F7icVP27oPGimT0OPAxMUuowm5/3Vx0czbzOya99RNL9pE7FH5GaHV6r2GdbTp+FVB5m9iowDDgK3qjmV46ZbQTuM7PRwDLg+sLLncAUScdJGpqvHJeR2tfbgcf48hhb2/KK+No+7uKrXyaQnhm3sP08cCqAmb0I/AzYXdLxhcNvJbVv3k6aP7+0DN5Lrz0kTQe+DjxoZlPMbA4wGiht6GUfy+omYKqkXfOHqVS24/aT/PNC4BRJ+2fPfwLXACeTrrQ7gRnAmrLdtuFVa3z1wqktsdWCV1vjaztutcaX1++vZvTLBEKPK4JCBr4L2CRpdt5eA6wADlJiOOlD9QRwqJnN63F+O73uAY4Ebjaz+YXTTjSzR0vy6a3TCnJZ5X3DgNuorpmhqZuZ/UtSh5n9DbgB+E7hmNuAL5GaYvYCZuXmh1JRd0e0m/jqhVO7Yqu3Xitob3w1dXMQX//1vewlvppiZv1mAaYDd+ZCPAgYlPcPzj8FnAX8gu6JJOcBlzeOA/Z25LUgrw8COjw5Nbza/D6+UQ7F8gBeyueMBqY1/Cvy6myyv1E+bY+vPjhVFltleLUhvpq61RxfU0m1rmuAQwougwp+bf/+2t7Sb2ogkvYGvgksB9aS2lM/BWBmW/Jhw4C7SZl7iaQxwGGkMdSY2RYz+7sjry35uK1WYhW+DKeGV1lOO+i21cy68pXWyMJpVwMrgV8Bu+ZjS73qknQGsJTUcfnJvK/Rwdr4W22Nrz46VRJbZXk13Mr02hG3OuJLUoekBaSazs9JieA88o2BhXJo+/fX/6Wd2arKBTgGuDWv704aG70MODDvW5QL/zDSDVSLSNW/G6joSserl0enXrgtJF2Bzcjbs4Cnga8AQyr2GgccC7xU2N+4Ory8pvfRlZNnrx10W1BTfM0F3pnX9yQlkncVXq+tzLbrXdcfLqHATwG+CByft99CGo44IW+PysFwNbAbcAuwX4/fsdtA8PLoVJYbqYlr3wq9ZuftDrqb9x4AFhaO3bvN76MbJ89eZbhVHF+dhbgflt2G5u07gI/WUWa9+j/qFmih4AV8BniU1B74Z1L23hW4DLiuEChHAN8GRhXOL72916uXR6cS3aq6qm/mdRYwonDMwcAGYJ8m57frfazVybNXSW7tiq9n8s/hhWOGAA8CB7SzzFpZdro+EEulOB24ysy+R2orfD/wQVK7+QRJx1hq110L7ANshtTWaBUNB/To5dGpRLdKRuZsw+toYEZjdJCZPUXq5L8q+8wqnN+u97FWJ89eJbm1K77OzV5HFkafTQReNrNnlG5snJr9VGWZtcJOkUAkzZE0U+nuVIA/AWMlDTazXwJPAu8B/kGq6l0raQLpy6gxUVvpAevRy6OTd7cd8HqcVAsa1zjHzOYCZ0haB0xWyTe6eXTy7OXZrRdeb8+v70karnsmqSZySE4epXXcl4Xb2XhzNh5N+iLpAp4j3TRzDmlSs0OACaQOrtuAa4E9zewmSfuSphk4EPi0ma3vz14enby79dLr9oYXsFrSO0idqvcD55nZk/3VybOXZ7cWvd4MrCJ13J9CqnGfZukOc5/U3YbWbKF7RMQBwE15fTBpxMFS0pXod4HTgZH59RuBKwq/Y5eB4OXRybtbH7w68/pIYGp/d/Ls5dmtD16L8vr7gJOqKLOyF1c1kDweuxMYJGk58CbyXahmtkVpJso1pJERtwAnkKqjV5Ky/ION32Vpsrh+6+XRybtbCV4P5WM3kJ4J0S+dPHt5divB69f52JVlOVWNmz4QSTOBR0jVuL/Q/ZCUoxqdSJbavjuBqy21HS4BjpD0UD5vxUDw8ujk3c2jl0cnz16e3bx6VU7dVaBCtW8GcHph+wbSrKFnAo/kfR2kdsU7gfF53x7A2IHk5dHJu5tHL49Onr08u3n1qnpxUwMhZe871D252UrgbWZ2I6lKeL6lDD6O9IjLVQBmtt7M/jrAvDw6eXfz6OXRybOXZzevXpXiJoGY2SYz22zd46+PIQ3nhHSjzURJy0jTFf9+IHt5dPLu5tHLo5NnL89uXr2qxlUnOrwxvbKRbhxrzMu/kfRA+0nAC3VkbI9eHp28u3n08ujk2cuzm1evqnBTAynQRRrm9gpwaM7alwFdZvZAjYXv0cujk3c3j14enTx7eXbz6lUNZXeqlLGQ7kbuIk12dnbdPp69PDp5d/Po5dHJs5dnN69eVSyNh5K4QtI40k02XzOzzXX7NPDo5dGpgVc3j14encCvF/h18+pVBS4TSBAEQeAfj30gQRAEwU5AJJAgCIKgJSKBBEEQBC0RCSQIgiBoiUggQVARkvaQdG5eHyPprrqdgqBMYhRWEFSEpPHAMjObVLNKEFSCu6lMgqAfcRWwn6THgGeBiWY2SelRpScAg0jTW3wV2IV078Bm4Dgze1XSfsD1wF7AJtJTGZ9u/78RBM2JJqwgqI6LgefMbAowr8drk4BTganAFcAmMzuM9FChOfmYJcD5ZnY48DnSFOFB4IaogQRBPdxrZhuBjZI2AD/N+58gzaE0HHgvcKekxjlD268ZBNsmEkgQ1ENxiouuwnYX6XPZAazPtZcgcEk0YQVBdWwERrRyopm9Brwg6RMASkwuUy4I+kokkCCoCDNbC6yU9CTw5RZ+xWnA2ZL+ADwFzC7TLwj6SgzjDYIgCFoiaiBBEARBS0QCCYIgCFoiEkgQBEHQEpFAgiAIgpaIBBIEQRC0RCSQIAiCoCUigQRBEAQtEQkkCIIgaIn/AHtPHPUyaTfQAAAAAElFTkSuQmCC\n", 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" ] @@ -260,12 +238,15 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -273,60 +254,64 @@ "output_type": "stream", "text": [ "Max: \n", - "array(539.369893)\n", + "array(539.36989292)\n", "Mean: \n", - "array(120.044761)\n", - "Monthly means: \n", - "array([163.591172, 86.604951, 104.529562, 167.926609, 115.902616, 125.099843,\n", - " 147.89506 , 134.871203, 127.745297, 110.203753, 109.357798, 45.021447])\n", + "array(120.04476061)\n", + "Monthly means: \n", + "array([[163.59117203],\n", + " [ 86.6049509 ],\n", + " [104.52956231],\n", + " [167.92660932],\n", + " [115.90261645],\n", + " [125.09984299],\n", + " [147.89506049],\n", + " [134.87120303],\n", + " [127.74529704],\n", + " [110.20375339],\n", + " [109.35779817],\n", + " [ 45.02144745]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean(dim='time'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Now we can also see the results coming from the 5 donors using the 'ensemble' variable" + "Now we can also see the results coming from the 5 donors using the 'ensemble' variable" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[,\n", - " ,\n", - " ,\n", - " ,\n", - " ]" + "[,\n", + " ,\n", + " ,\n", + " ,\n", + " ]" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -341,13 +326,6 @@ "# Plot the simulations from the 5 donor parameter sets\n", "ensemble.q_sim.isel(nbasins=0).plot.line(hue='realization')" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -366,7 +344,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/Raven_run_parallel_basins.ipynb b/docs/source/notebooks/Raven_run_parallel_basins.ipynb index c4096d03..d2a8586c 100644 --- a/docs/source/notebooks/Raven_run_parallel_basins.ipynb +++ b/docs/source/notebooks/Raven_run_parallel_basins.ipynb @@ -24,49 +24,20 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, { "cell_type": "code", "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "PosixPath('/home/ets/src/raven2/raven/tests/testdata/input2d/input2d.nc')" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "TESTDATA['input2d']" - ] - }, - { - "cell_type": "code", - "execution_count": 3, "metadata": { "scrolled": true }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/src/birdy/birdy/client/converters.py:294: UserWarning: No converter was found for /tmp/tmp_di_5mns/raven-gr4j-cemaneige-sim-0_solution.rvc\n", - " warnings.warn(UserWarning(\"No converter was found for {}\".format(output)))\n", - "/home/ets/src/birdy/birdy/client/converters.py:294: UserWarning: No converter was found for /tmp/tmp_di_5mns/raven-gr4j-cemaneige-sim-1_solution.rvc\n", - " warnings.warn(UserWarning(\"No converter was found for {}\".format(output)))\n" - ] - } - ], + "outputs": [], "source": [ "# The model parameters for gr4jcn for both catchments. Can either be a string of comma separated values, a list, an array or a named tuple. \n", "gr4jcn1 ='0.529, -3.396, 407.29, 1.072, 16.9, 0.947'\n", @@ -93,20 +64,22 @@ "\n", "# And get the response\n", "# With `asobj` set to False, only the reference to the output is returned in the response. \n", - "# Setting `asobj` to True will retrieve the actual files and copy the locally. \n", + "# Setting `asobj` to True will retrieve the actual files and copy the locally.\n", + "\n", + "### asobj= True is failing!\n", "[hydrograph, storage, solution, diagnostics] = resp.get(asobj=True)" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "['observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_g37xmyli/input2d.nc,-0.0371048,36.562,\\n', 'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_g37xmyli/input2d.nc,-0.0888378,37.4628,\\n']\n" + "['observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_pt_tjslk/input2d.nc,-0.0371048,36.562,\\n', 'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_pt_tjslk/input2d.nc,-0.0888378,37.4628,\\n']\n" ] } ], @@ -124,34 +97,22 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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1M3Bz2Op6tDdiMCQGfwPk0FTGm1sCuR2MgIS0c7cAl0miZyjxCkj4xdtgaP8EO+9alg5hgRkLAiFJdN2N12VyIBlKXAJitzQxGDKLgO1sW37wZOvnHXrD9uWpsykdaJYDyTICkqHE6sb7aqwDxLOPwbBPEuy8qwI6hAVQ2ld7IJkcsonQjdcISGYSywOZHKNliQDD29AegyF9CIaw6nZCcXf9vENv8NVCzTYoLE+dbanEat6N1whIZhJLQE6M4xhmijZD+8RfD2/9nw5ZDTlGr3OW8maqgETwQEwZb2ayRwExuQ9DZiKAgpXvwscP6FUu+1/FOZiwZ4aOBXGIhbJna/QbDyQjiaedu8GQWYj9bzHntqZ1A+2K8RIzFsRZhWVyIJmNERCDIZxgo8TgJFJnPs3btYNYu6MWcoshrzTDBcTRkFuZHEgm02IBEZFSEdkvEcYYDGlB0ANpqII+k2HI0Vz8zwUc9Wd7Qs5MHwvSbCChEZBMJS4BEZH3RKRYRMrQbU0eE5F7EmuawZAixPFvUdwdZcf8axrs0E2HPpktIBGqsEwSPTOJ1wMpUUpVAqcAjymlxqG75BoM7Q+ngBSUU+8Pm0Mt6IFk6kXT4YGIpcfKmCR6ZhKvgHjslukzADNw0NC+CRGQjtQ1BEK3d+gD/jqo2Zpcu9IFZUFWAQBZlhcAywhIRhKvgNwGvAUsV0rNF5H+QEXizDIYUkiw7xVAfke8/nABcYwFyUSUBdn5ALgtPQzMeCCZSbwC8opSaj+l1OUASqmVSqlTE2iXwZA63NlNz/M74fWFhbBK++rljlVJMymtUBZkaQHxWLpfmEmiZybxduNdLCKbgXnAXOBDpdTuxJllMKSQEAGJEMIq66fDXNsz1AlXFmTrEJbHnmPOJNEzk7g8EKXUQOBMYBFwHPCViCxMpGEGQ8pwjnPILWkewvLk6DzItu+Sa1e6YAUaPZAs2wMxIazMJC4PRER6ApOAQ4DRwDfABwm0y2BIHXZ7DgByi/FWBZrv02kQbMvQtu7KgpxCwOGBGAHJSOINYa0B5gO/U0pdmkB7DIbUE2zjDpBTjNdf13yfjoNg1Tx7sqkMa+igLPDkAkK28UAymnh/+WOAfwJnicjHIvJPey5yg6H94Rwol13YPIkO2gPx10HluuTZlS4E50fx5JKltIAYDyQziXdGwq9EZAWwAh3GOgeYAjyaQNsMhtTgDGG5XHh9UUJYANsqmsp6MwWldKlzVi5ZXjOQMJOJt5XJAuBj4GRgGTBFKdU3gXYZDKnD8oW89AUieCAdHQKSaShLN5x0eiCmCisjiTcHcrRSKkOH3RoyCqVCPRDAF4hwcSzsDDnFmVnKawVAXATcuUjAjAPJZOLNgTSIyD0issB+3C0iJQm1zGBIBcH8R99D4PR/A+B3eCCNz0XsSqwMFBBlgbhZX5dFRyoBE8LKVOIVkH8AVeheWDOASuCxRBllMKSMoPcx4HAYdjwQenEMaazYMVMFRHsga9y9GODaAJgkeqYSr4AMUErdbLcwWamUuhXon0jDDIaUEMx/uJqiu84QVkhCvXwIVG2Aul3Jsi49UBaIi10F/ekh2ymk1nggGUq8AlInIpODL0RkEhChON5g2McJeiDurMZVzhBWiAfSdZRebv4mGZalD8oCl5u6DrqQYIBsMEn0DCXeJPplwBN23kOAHcD54TuJyClxHMurlHo9bgsNhmRSt1MvnR5ItBBWlxF6uXkx9J2UDOvSA0t7IFWF/QA4tXc1i9YYAclE4h0HshAYLSLF9uvKKLv+DXgJLTLRmAK0SEBEpAPwd2AkoIALgW+BZ4C+wGpghlJqZ0uOazCEsPkbeHCifu4QEKcHEhLCKuoGeWVaQDIJO4S1JasbXpXFCPc6LLU/SilE9vSvb2hv7FFAROTqKOsBUEqFT2v7hlLqwhjH/HdLDLS5F3hTKfVDEckG8oEbgDlKqTtE5DrgOuBXrTi2waBxtmd3Ckg0D0QEuo6ETZkpIA0BN9/Rh841uqlkwFJ43EZAMolYOZCiGI8QlFLnxDphPPs4sb2exlHvSqkGpdQu4ETgCXu3J4CTWnJcg6EZ+WVNzx05EOdAwvrwUeldRsGWpaHtT9o7dhWW37L4VvrRuXoZoEwiPQOJFcLKV0r9SkROU0o9tzcnEpHpSqnZrXhrf2Ar8JiIjAY+B34GdFFKbQRQSm0Ukc5RzjsTmAnQu3eGtZwwtIyQFibOEJajCit8fvQuI3RPrO0roHxwoi1MD2wPxBew+M49gJzAbHrJlqZEuhWAD/8MB1wMuWa4WHsmlgdyjIhkAde3wbla2zfLA4wFHlRKjQFq0OGquFBKPaKUGq+UGl9eXt5KEwwZgbMLb0gIaw8eSNeReplJeRArAC4PvoBiuXsgAOPlu6bR6CvehTm3wRsmotzeieWBvAlsAwpExJk4F0AppYqdO4vIy1GOI0DHVtq4DlinlPrUfv1ftIBsFpFutvfRDdjSyuMbDJooHohvTx5I+VDdmXbzYhgZTxFiO8AKgMuNL2CxytOfaunK8YGPmwTEbX92qZry97u3YOkrcOIDqTl/BrFHAVFKXQtcKyIvKaVOjON4wU691WHrBTiwNQYqpTaJyFoRGaKU+hY4AlhiP84D7rCXL7Xm+AZDI04PJGwciEvAUlDtDe2ThSdHi8jGr5JkZBoQzIEEFB6Ph1Wdj2bKqieorNoC+T2bPsfa7amx78kZennC/brQwZAw4h1IuCx8hYj8IcJ+nwC1Sqn3wx7voctuW8tPgf+IyNfA/sDv0MIxXUQqgOn2a4Oh9YR4IO7Gpz5L0bssn44F2Xy6KsJFsccYWP+FbsSYCdgeSEPAwuMSVvc4Do9YZC17UW9vqNFLb4pH6Ic1xTS0PfEKyPQI644OX6GUOlop9W6kAyilprTEsLD3LrTzGPsppU5SSu1USm1XSh2hlBpkL3e09vgGAxBywfn9W03T1foDFtkeF4cOKef977Y27zzbfQzU7YBd3yfL0tRiTyjlsz+X6pLBLLH6kPvNM3qQYVBAUn0B99en9vwZwB4FREQuE5FFwFAR+drxWAV8Hc8JROS4tjDUYEg4jhDWl+uqUbZH4Q8oPC4Xhw/tzK5aH1+uCRuv2n2sXq7/IlmWphbbA/EHFFluF26X8GTgcLK2fA1fPdUkICrCPCp7y46V8beOMQKScGJ5IE8Cx6PzC8c7HuNaMJ7jttabZzAkEcdEUn50iAZ0CCvLLRwyqByPS5izLKxeo8tIPSJ97l3tv7GiZQEKpCmE5Rbh34Fp+PM7w4o50GCnQBMR0rtvTFO3gFgEjIAkmj0KiFJqt1JqNXqEt3I8CkUk3kEVJotl2DcIhApIcC50f8DC43ZRkpfF2N6lfFCxLfR9nmw4+g+w5Rv44p/JtDj5KLuM2eVpDO25XQII3h4TYfWHjR6ICviiH2ev7YhDnIwHknDizYG8BrxqL+cAK4E34nzvJa2wy2BIPo6YvQvVOOZDh7D0fdDEgR1ZvGE3u2obQt+73wzoNhq+bed9QoMj7l0ufPbnku3Rl5HdXQ6E6k1UrtahPPHXQSBBeZDaOFKeRkASTlwCopQaZSewRymlBqFLcj+ItK+I/NZe3ma/97O2MtZgSCiOO2YP/iYPxLLIcut/lUkDO6EUfLIyQjVWv0Nh/efQUJsUc1NC0AOxk+hZbhejeujR5p9awwAoXvtO0/4NVYmxY/eayOudLWVMCCvhxOuBhKCU+gI4IMrm+SLyF2BBq60yxE9Nimrt2yMODyRLAnj9AZ6dv5Yv1uyiJF+PCxndswN5WW4+WhHhc+87GQINsG5+sixOPo0eiBu/3TyxV1k+w7sV84f5AQL5Yd0e6uMQEMsCf0Ps/ZwEE/XhOMNmxgNJOHEJiIhc7Xj8QkSeRPenCt/vZuBw4EzgCBH5dduaawjh6+fgzv6w7vNUW9I+cCTRN6kyVm2r4ZfP62LDrsW5AGR7XBzYr4wPl29r/v7eB4G44PsPk2JuSnB4IJalcNkD9e46bTRbqxv4Lnd06P47VsY+5hvXwm/LW5Z0D0QRHOd6IyAJJ14PxNmBNwedC2k2Mt2e6hbgYPu1qcBKJKve08tM6sOUSOx4/UTvfaxS3bjzraaxr0W5TU0bJg3syIqtNWza7Q19f26JnqVwdTsWkGBfMJcbSyk7gQ7Duxczvk8Zc7y6oeRSqxd+XLBqbuxjzv+7Xrbkgh/NY3GOPTECknDizYHcaovDPcC9Sqn/KKW8UXb/h91y5B9tZaQhCo5/ZkMbYPnA5WEDnQBYu0PnMs6f2JdLpgxo3G3SQL19bkUzJxz6TNYhLF+0f499HNUUwrIUjR4IwKFDynlhZ38AsvGzRAbByvfjP3ZDtd3J916oD++GFEZUD8QRwjI5kIQTbwhrpIh8CSwGvhGRz0VkZJTdT7OXp7aFgYY9EByoJa1KZRnCCfjA1dQDq95vccyortxywgjysptEeni3YroW5/LO0gj9O/tO1heu9e00rBi8wxc3AUuFtJo6dHA5K1U3HuN4fu67nA8DI2DDF+DdHeOg9kHqK6FiFsz+Ncy6cc9viSYgljMH0k5FPI2I98rzCHC1UqqPUqoPcI29LhImiZ4sjIC0LZY/pAsvQPeSvGa7iQiHD+vMvIqt1PvD2rv3ORiQ9psHcSTRlVK4HQoyvFsxnQpzuNV7Jl+rAbzvH65/o7FCekEPur666be8K0qVVXB7tDEmIUn0Fibm041/nazznGlMvFeeAmePK7s5YkH4TiaJnmSMgLQtlr+pFblN5+KciLtOG9aZmoYAn6wMG4+QV6pHpq+elygrU4sjiR5QKiSE5XIJUwY1VWF9YQ1CefJgVYwwVlC066sczysj7qqC3kq08JRDQKx9qZy6emuo4NVXwYp34IWLU2dTHMR75VkpIjeJSF/7cSPQrNm/SaInGSMgbUtYCAugc1FuxF0nDuhEbpaLOUs3N9/Y/1BY80nsOP6+iBWWA3GFNpo4dEiTgDSQxe7ycXqCqT0htgfSUN0UdvJGFhBfsL1WNA/EEcIK7Euf/10D4bnzml5XRfhdpSHxXnkuBMqBF+xHJ+CCKPs+BuwHPA8gIjeKyAsiMnYvbTWE03g3aASkTbB84M7CeU2M5oHkZrmZPLCcOUu3NDZdbGTgNB2jb49eSONNiw5hhekHk+0Cg0MGdSLb7eJTz3jY9q2e8jcajSGsKvDVNT2PdHr7kqWiVVg5hMVXFyYgVkBPNJXMtvuzboTVEcdcNxG0OdjFoHorPDSpaXsaTxMQbxXWTqXUlUqpsfbjKqXUzij7LgRuUkrNFZHJwJHAE8CDbWe2ATAeSFvjr0d5cnF2a4/mgQAcOaIL63fV8dW6sCRxn4mQVQAVsxNkaApxeCABKzSEBdCxMIcXr5jEA2eNZdLAjvxj61C94f6xsPTViIdssIJJ9KomD0QFIu4b/Gpq6uqi2NdUxhsIF6H5f4dnzoFF/4383rZGKfjofnj82D3v5wsLtX10b2gBQDxtW1JEoq48wW//WPRc5i8B2Qk6V+YSvDMxAtI2+L0oT6jHEc0DAfjBiK5ku128+tWG0A2eHOg3BZbPTuu7x1YRvEDbISx3uAsC7N+rAyV5WUwf3pVPdxVT12Wc3hClsmp3g/6MfHWVTR6IFVlALPuSVVUdeSS65cgjWF7bA3nuAvjvhVBth4W2L4/wzgTgiyJysfYLD19Vhf2+0ohEXXnWi8jDwAzgdRHJSeC5MhfjgbQtPi/KHSoYRTnRZ30uyctiyuBOvPr1RqzwSaYGTdOVRNsqEmFp6ggbib6nGWOnDe+MCDw66K9wxK9h5yrYva75Ie1LQ0PNbpR9MVVR5hJxYfcn80UOYTnXq2AO5JsXYPHzTfmthiTlRsI9iyB3DtSeSbT9wsueqza1rV1tSKKuPDOAt4CjlFK7gDLg2gSdK3MxAtK2+JsLiMSYU/v40d3ZVOnl8/BJpgbak3hWzGpLC1NPSBI9tIw3nM5FuezfqwOvf7MVhp2gV378V9i0KGS/HLTX0FBbyfebdIsYb0PkJLnHDm5YUUp0fQ1N61V4FdYWeyKqyvVRbW5TIvXrsiyo2RrqjTk9EKUa55K3EC2u33+UYENbT6wZCQAJX4IAACAASURBVO8XkfuiPaK9TylVq5R6QSlVYb/eqJRqZ/9JaUCjm9/OwiSpwl+PZQvI6F4duOGYoTHfcsSwLuR4XLy8MCzMUNpHl/MufSURlqYORxI9UhVWOCeM7s6SjZW8t70Ea8hx8Mlf4KHJsGtt4z55toD46yobPRC3FcHDUAqP6PNHFRDbA/Ept/Y0nCHEjV/pZeXGmH9mmxDJA/FHCGs5BcTvhbod1PU+lP28f+P9wChY9FxT14k0I9at6wLgcyAXGAtU2I/9acpzGFJF8J85SrzY0EL8XmotHeY4+8DezHS0L4lGYY6H6cO78MrXG5oPKhx2Aqz9NK1DEC3GMR9IQO05hAVw4v49EIHzH5vPQ9nnQq+D9IaFT+plwE+26LxKwFuJO6CTx9mqofnv2pEgj1aF5fdpYdlNAZ66raHVXMHBicnKKUQahxIpL+IUmtrtsGMlGz29qCaf2VmHwe61aTswNdaMhE8opZ4ABgGHKaXuV0rdDxyBFhFDKgkKSCLmns5AvN5aPlit4+NZnvgn0vzhuJ7sqvUx5MY3WbDaUTEz/ARAwbLI1Uf7JI4cSPhI9EiUFWRz83HDAbjn8wC+89+A3hNhyYt6B+cdeX116OC/8BBQiIBE9kACtoB8aQ2iaPd38Povmu9UuTE5d/S+CCGsSF6JU1Re0/bW1ujf4fzcgyG7CL56OhEW7jXxBs+7ozvxBim01xlSSaOAGA+kLVA+L/VoDyQ4gVQ8HDKonKn2ALrbXl3StKF8KHQcCEteblM7U0pjFZYnYhlvJM6f1I+HzhmH31J8uHwbavgJsGUJbP0u9OJZX4U4R6CHC0ggdp+rgF/vc4f/DDZ2Ohi+fiZ0h7xSPd5nwxcx7d5r4vRAGryOpP53eqLXj3IPAWB9NfrzWvJSWk5UFu9/yR3AlyLyuIg8DnwB/C5hVhnio1FATA6kLXAH6qlXLRcQt0t4/IIDufHYYXy9bjcVm+2wiYgOY63+AGoizB+yLxJjJHo0pg4pp0eHPM5/bD5nzOusVy55KeSCmufdgrveUYFUFZarcHggeXWRw4JBD6ZW5fJFj3OabZ9TcAzKk9tcWBKAipREj7CuvjasKuzAmbzr071qaxoC1Aw7Tc/smIbTJcc7kPAxYALwP/txsB3aMqQSE8JqUyRQ3+iBZLdAQIKcNKYHHpfwzPymBDEjT9Ue4uIX2srM1GJ7u8qu/ItTP8jNcvPbk/RF8dPtuWwuHQtfPdUY0pkbGEVJ/QbKKxfztdUPP25deuvEISAltZGbLVq2IHnJYlleU/MLb4+JADyzoTOryg7R30e0digtoXJD1FHzPm+kEFZYxRXgqwzr6tyhD2t31pLl1h/u2qIxUNJLf15pRrzt3AWYBowODgoUkQMTapkhNu0piT7vHrilJKUmuAL11NvjXVvigQTpVJjDUSO78syCtdTU2xe7riP1JFNfPdmWpqYGpRp/awGCAhJ/ruiwoZ1ZfcexDO1axDP+qbBjBYGKtwF4PnAIPskiJ1DDatWV99UY+PrZxkm+9El1fmOl1ZUC33aobt5O32oICkg2u7wWHH4TrwcOZOKKc3lmyJ+YZY1nccejoHYbrHyvFR+Cg5rtcM8weOknETd7vc1DTsqZA/F7YfsKyj76bcg+geKebNzt5cB+ZQCs21UP+83QzRXTrEdWvP8lf0U3SDzTfl0F/CUhFhnipz15IHPsPpx7I4Zbv9X19a1p/aAUbqvekQOJ/8Lo5MLJ/ajy+vnv544Bc6PPhA1fwpZlrTpm2vDfC+HJGQAodP+qSCPRY3HSmB78desorOwi5NOHAdhCKV/k6f5Pu1UBz/oOgZot+qJp46/XF9/XLLuS6+tnmx1b+ZoEpNLrgym/4HLfVeygmG/yDwSEL7PH6VzI3oax1n4augyj3ts83xHilTTURJw3ZmtOLwKW4rAhnSnK9fDsgrWw3xn6/3xRerV3j1dAJiilrgC8oHtjkeTWJCLiFpEvReRV+3WZiMwWkQp7WZpMe9KCdpVED7bp3os5HF76iR7h+3Er7m3sslCvsj0QT+sGZ47tXcqY3h147MNVTaPTR52mO86mYQiiRXzTFIaz7BBWCxyQRk4Z04OAO5fPi6fhqtThPq/K1iWrQCX5vGONwcorC/nMggKyyOrHmvwR8OW/muf/fHXUqyxcLjeVdT4Cjg4Bn6zUA/RW7vTBiJNh2Wt71zE5mMjPaj5nDEB9vUNAbE+q3tngsb6qMSy3UZVxdsP1fDbmD0x+THsZw7oVc/Hk/sxesplF9V2g+1j4Or2qseL9L/GJiBt7xJqIlAPJvu39GbDU8fo6YI5SahAwx36dWbQnD6RxoqBWCoivruluLmykc1zYF4NGD8TV+tH9F07qx+rttbyzzA6xFHbWHXq/frZ9hBsBy27BHquMNxKdi3M5fnR37tgyoXGdJ7eAp3YM5APPQXxojcSHh90DTtAX+bpdQJOAeMnmk5JjYOsyeO0aWDUPXvmZLlTw1VFHNp0Ks1m1rYaKLU35ie8264v399trYPRZOv+yN3f0wd9qlO+0od4xVsUuV26oC/NA7FHnR9XfwYfWKGZ83Au/LXqDuhRy4eS+dMjP4p7Z32pPdtMi2LCw9Ta3MfH+l9yHTp53FpHbgQ+A3yfMqjBEpCe6MePfHatPRHf5xV6elCx70ob2JCDBlt6tTWxuXqI9MU8ebFkae/9wbA8kKCD+vRgncNTIrnQvyeWh91c0tXrf/0w9gG35nFYfN52wpOU5ECcXT+7P5w29WZkzjN0qn2MmH0CNTzin+krqek7G4xKe9R+qJ46yx0AE6vXFt07lMEsO1gda8Cg8cRx8/ji88Svwe/GSzenje7F+Vx1nPPJJs3Ov3VmHt8sY6DJKv7+1VYzBwYxR3u+rd5Qa+/TzkJJdW0AC4mF38/n5KC/MoSg3i5lT+vPut1tZWPoDyMrXXYXThHirsP4D/BItGhuBk5RSzQOQiePP9vmd/9VdlFIbbfs2Ap2TaE960J6S6MFJhVrrgWy078qGHKW7rrb0ohDmgXh9rReQLLeLy6YOYMH3O/loxXbbrmOhsAvM/1urj5tOWOgmk63UD4Z3L+bQweUcu/taDq5/gBH9ezeOpRnWrZgT9+/Bn7/Jx99tPHz2CFgWPjspXS/ZfLHZQh1zN+SVNR10y1JoqKVOZXPuxL5ce+QQdtWG3pAc2K+MgKV47ov1cMCF+o5+XStn37Z/q/4o/38BZ8NHO3nudybWG6oJVG9jm1VIYwgXGFBewANnjWnsw3bewX3pWJDN3fM263Doov9CXcTZNJJOvFVY/1JKLVNK/UUp9YBSaqmI/CvRxtnnPg7YopRqnm2K7/0zRWSBiCzYunVrG1uXYoIXyfYwDsTVCgGp3ABr7ATmxq90YrTb/vqutaUdV4MeiMpiaNci9uu5dxVhMw7oRdfiXP789nfaC/Fkw7gL9Bwhe5pcaR9BSeuT6EGuPGIQdeRSSy6FOR5mHtIfgLL8bC49tD91vgCzi06EHStgxTuNCejhvTuzo6aBBZ1PgZ8thD6TobQvbF1KTt0mvGRTkO3hrAl9Gs9VXqR7nJ1xQC/G9O7Aw++vwD/ih3qU94JHW2X/+u16zEpVbeS2Kso57a6d3A96UQANdVXs2LKe7Sr0t3bjccM5br+mcdoFOR4uPXQA8yq2sbjHDB0OW5geVX3xhrBGOF/Y+ZBxbW9ORCYBJ4jIauBp4HAR+TewWUS62fZ0A5rX9AFKqUeUUuOVUuPLy8sj7bLv0x6S6NKKENasG+EfP9B3kFUboUMfKNAz4gVjy3Fjx6h9ks2bV02hYA9t3OMhx+Pm8sMGMH+1wwsZf4EWyvmtu2ClEwHRn09rQ1gA4/qUcvTIrgwoL6BnWR4HD+jIDccM5eSxPRjUpYhpwzpzU8UAVEEX+OxhGuwcyJH796dTYTb3zamA3BK44DU440lQFt13f4mXHHKzXBTmePjjD/fj/Il9+c/FE7j5+OEcP7o7V0wdyLqddbyyrBJGn67HhNTY39HudbBpcVz2B+ckCUTxQJS/6bccLN8N2H9DvfLA/EfxVK9nkyrlRwf1YWjXIjoVZjO6Z4dmxzrnoD6UF+XwmwVuVK8JOoyVBg0WY3XjvV5EqoD9RKRSRKrs11uAl5JhoFLqeqVUT6VUX+AM4B2l1DnAy0BwEuHzkmVPWtIuciD2TzHaVKWRCJbrrnhHt3nILoB8W0BqWiog+rzh7dz3hhnjtRdy51vfai+kqCsMPxG+/HfkVt/7EAFb8PfCAQHgwXPGMeeaqRTnZiEizJwygAHlhQBcNnUg2+pgQacToWI2WVt1m5iSoiJ+fEh/5lVs45h75/Hkp2u4/sMADb2nANo7CoZ/ZozvxS0njGBwlyIumNSPLLeLw4d2ZkiXIv767gqscRdpj3XBP7Qn/6cRejpZ5/iTKFj2b8YV7f/P4YE02N6T1VDLVlXCzf7zyV4zl9LKb9msSrnxuGG8eMUk5v7yMMoKmhe45mW7uXzqAD5dtYOK3mfAjpVQ8Vacn3LiiNVM8fdKqSLgTqVUsVKqyH50VEpdnyQbo3EHMF1EKoDp9uvMInj31x4EpDU5EI893eyGhbpxXVY+5HfU63auatn57RxIoA0FJDfLzdXTB7Nw7S5e/dpuy3HgJVC/G75ISgQ4YaigB7K3CrIHxvUp5bAh5fzq+3Eodxbdl2rPLTe/kHMO6kNhjoclGyu54X+LeOqztfzNr6eOXenut8fjulzC5YcNoGJLNa9sKtFzt3z2MOz6vmmnOH4/ys5xZBHFa3b8lr3BdiU+naN5JjCVupKBAFRldSLH4yY3y01+dnTP98wDe9OtJJcbKwaiSnrpwbcpDl/Hm0S/XkRKReRAEZkSfCTauAh2vKeUOs5+vl0pdYRSapC9TN+JgxNNe0iit6YKK9jttHqzjjFn5+tR32UD4O1bwVu55/c7se8mrTYUEIBTx/VkWLdi7nhjGV5fAHpP0N1oP7oPonSU3Rdo8kASJyAA1x45lJXeIj7uenbjupy8AgpyPDxx4YFcOKlJLJ7cMZjb+/yDh/Jmxjzu8ft1Z1i3Yu6a9S2+g36qJ3l66qymHTYt0uXDr14N8+6OeAxlC0RwQqxwxCEg9cHyXV8ddeSgcLFs3C2syB7K8qL4mnrkZrm54rCBfLamioqBF8K6z1Le5j3eJPrFwFz0LIO32stbEmeWIT4y3AMJdif17tLPs/IhKxdOfggq18FbLXCSbQ/EFWVQWGtxu4Qbjx3G+l11PPbhar1yyjV6Vrx9eGChZXsgrRkH0hKGdy/mhNHduWjNkdRkae+yIE9/R+P6lHLTccP40+mjueKwAazfVccTy/PJzY09xtnlEq47eihrd9Tx7029YNjxTTMWAnz8ANw7WifY59wG25rPox6ckyQbf8SbOAn4qFbaS+78+kUw5ze4fDXU2WOw7/y2nEty/8jOTmObvTcaM8b3okeHPP5v9WhUQbn2QlJIvEn0nwEHAN8rpQ4DxgDtrKRpH6Y9JNFdtuveEgEJNqbz7m4KYQH0OhAm/UznGr59I85jaQFx5+TGf/44mTSwE9OGdeb+dypYv6sOBhyhq8U++FNcsfZ0JGC3MkmwfgBw9fTB+C3F2Kq7OaL+TvJz3I3bRISTx/Tkp4cPoldZHg0Bi1yPew9Ha2LKoE5MHNCR+99dQeUJj6LOfJpL3Ldxt+sCPSjVu6tp529fa34AZ74ufB5ztAeyQnVnoaWry5h3FwMqPyXgyuXaI4fw0YrtLN9STbeS+H9z2R4XVx4xkPnrvSzvfy6smBOxHUqyiFdAvEopL4CI5CillgFDEmeWoUW0izLe4Ej0VoSwvLvtJHp+07ap1+spZV++Mr6Euu2BuNvYAwly8/EjUAp+/eJi3c5hyrU6zv7WDfukiFhJCmEB9O1UwPVHD6OebFaoHuRnNReI3Cw31x89DICRPeIrwRYRrj96GDtrG7hvzgp29Dict2oG8kjtoVhZBSiXhzUXf0NDjwl6Lvfw+TicNzsR5ll3WQ004OHchuv45Li39eh3AJeHy6cOYOIA7VF179Cy39wpY3vSp2M+162dgMor0x5SiohXQNaJSAfgRWC2iLwEJGleSENU2lUSvRWtTIL/0IEGXYab5RAQT44OZdXthNeuji2ytoB4chIjIL3K8rnmB4OZs2wLbyzeBEOPhbHn6eTtpw8m5JxtStjnZ9mXjr0ZB9ISLpzcj2uPHMIBfUvxROmUfMyobsz6+RRusmdAjIdRPUs444BePPbRah56X4/PqSebWdNnc17efUx54CvOWnkkVG9q9j2Jo8pKBafLdeCyfPjIopJCzvjvFq7e/UPm5U/jtfwTEREeOGsst54wghnje8VtL+iBqldPH8znm/ws6H2h7iq84t0WHaOtiDeJfrJSapdS6hbgJuBRMrF1SLoR/KduD0n01uRAfLWhouF8Djqhftj1evrUWAOvbAHJyk6MgACcP7EvI3sUc/PL37C7zg/H3wuDj4J3f68HRaYzYb+xYJPCZISwglxx2ECeu3TiHvcZ3KWoxaJ27ZFDKc3P5m/zmiqvLn1hNXO36/EYC9RQNnc9DD64N7TTc8DHVnsQoDx9VrOZJ13KR1Z2DvnZ+rf9wjIvP9pxIYuLdNfhsoJszpvYN2LZbixOGN2dQwZ1YubS0fiLeuhu1imIRMQaB1IW/gAWoXthFSbFQkN0MrkXllJ6LEWxY2bl7Ob9hJh0FfQ9RM+Nva0i+vHscRme3AjHaCM8bhd3nLIfO2oauOmlxfrqe9QdeorVOb9J2HnbBCs0zBbs8ZUsDySRlBVk8/rPJvPHH+7Hfy6ewINnNyW1bzx2GB0Lsrm59lRUQxXMvbNxmyvQwAbVkd/5ziSQXQwvXhbSpyonUIflyeffF0/gzh/ux+VTBwBQkpe11zaLCLefNIo6lcU/c87W0wWET8CVBGINt/0c3YE30q9EAf3b3CJD/DS2MslAD8RXCygo7gHb7QqZnKLm+7nccMoj8OAkeOAA6DUBTvordBwQul99FXVkk5fb9kl0JyN7lHDVEYO4e/Z3HD60MyeN6QcHXQYf3gsTZkL3MQk9f6uxQoU92CU9GTmQZNC5KLcxlKSU4tJDB1Bd7+PCSf3o27GAi//ZwMJexzPm04dhzI+gy3CyA9XsVHk8Ejieb/Om83DBw+S+dg2U9YcBh1NoVVLrKeGw3qWM7V2KZSnG9y1lcJcIv9NW0LtjPtdMH8JvX/dzcudhlM7+NQw5OvKNVIKINZCwn1Kqv70MfxjxSDXtyQNpaQ7EbvFNaVO/I3Kbt4AAtJdy1jO6VHPbd/Do9KYeWkEaaqhReeRlx1fBszdcfthAxvcp5aYXF/PKVxsITL4GCsrhyTNgTfPusWlBmAcSDGG1AwekGSK6xPe3J43C5RKmDe/CWRN6c9G6o/FlFcHr14JS5AWq8GXrENb7m3M5ftc11Bb1g1eugoYailQlDdlNv0mXSzh8aBd6luZHO3WLuXByP8b37cSVu8/Uifwke7LxjgOZEumRaOMMMYggIBt21bF2R/OpNNOe4IUoXjEMlk12cAhIXhQBAV3ae/q/4OK3tdD88wT4/qPGwXwBbxXVKpeCJAiI2yX86fT9yct289OnvuSG175HnfO8npjovxe1bABksgjLgVgqKCDtUEEicOOxw+jQsRt3W2fA9x/AoufID1QSyCnh+csmcuOxw9hcCxdsO0ePaH/jl7ixQrsFJwC3S7h7xmgWMpTX807Qif4k9lqLtwrrWsfjJuAVzEDC1NPYzr3pojvxjnc45I+pqcjYO+wLkRVnSWuwRr+0b9O6aB6Ik44D4MK39D/2Y0fD34+A+iosbxU15O6xlURb0qssn3m/OoyZU/rzzIK1/HNVCZz6dz1nyOxfJ8WGFhH2vWSagORne7j3jDH8o/YQVucMRb15PYVWFYGcDozrU8rFh/Tns/+bRmXXCTzLD/QYJMBV0DHhtvUqy+e2k0bw052nUVE8EfXmdXp+nCQQbxXW8Y7HdGAkkF6zu2ci7SmEFSTeirJgCKvEUQK5Jw/ESWE5nP+qLqPdvBieOx/Lu5tq8ijISbwHEiTH4+a6o4YybVhnbnt1Cc9v7op/wuXw+WOw/O2k2REXzQREL9tDEj1eRvUs4WfTh3JJ5flYdbvIwo/KbRpzkpvl5sGzx3IPZzfOK+Mp7pIU207avwfnHNyfGVvOpZoC1P8uaf3kbC2gtfN2rkOLiCFVbF+h51SGdpJEb6EHUmN37w+2b4f4PJAgHQfACffBsffA8rfJWf8JtSonaR5IEJdLuOf0/enfqYBrnvuK81b9AKvTUD2/e20atXcLhCfRk1/Gmw5ceugAug0ex/3+kwFw5YeGqPp2KuCPZ03iuPrbudY3E1+fyUmxS0S45YQRnHvEOH5Rdz6y6euoPbzaknhzIPeLyH324wFgHvBVYk0z7JH7x+rBTZCZHsgn9qCu/I4w7VYYearug9VSxl8AB/8EgEKpa6zZTybFuVm88tPJ/OHUUXy8pppbPVeiarbqZG26EJ4DsTIrhBXE7RLuPWMMrxafwW2+H7Gt5/Rm+0wZXM6PTz0GGXMOBw3qljTbRISrpg2iYPRJ/C8wCev9O2H9Fwk9Z7y3W845H/3AU0qp1LaBzGTCBwxFEJCApfax8EJwVH2cAtJQo2eiy+sAk6/au1NPv401tdncPz+Ly5LsgQTJzXJz+gG98VuK//vfYg7qeS5HL/4HDJym51NPNSaE1UhJXhYPnTeBS/7l4dj+kVvHzxjfq8UjzNsCEeF3p4zix1uvZMLWy+n09LlkX/5B/OHdFhJvDuQJx+M/RjxSTPhdeoS79ur6fau/UiBYCBBvCKuhBjoPa5uTu9xUDL2UudbopOZAInH2hD5cPX0wP1l3GKsLx6Be/XncM+QllChlvBnmgDQysHMRc66Zyrg+pak2pRm5WW7uPm8qt+T8AlfVBmqevSRho9TjDWEdJyJfisgOx8yEaVhrmCGEDeqK5IHsawKybrv+Oal4Q1i+Ol32GkYwtNJSahr0eZOdA4nETw8fyI8mDuC0bT+mWgpQz/4oYrfXpBJFQDyu1qZRDYmkc1Eu1888jz/LjyhY9SaV7/4pIeeJ99v/M3ra2I6OmQmLE2KRITbhg+0iCEiVN/EVGG1JfYO2N+CPw27L0s0Tw0bc/vyZhQy56Q3eXLyxxeevtQU3FTmQcESEm48fztEHj+aC6suxdn6PemFmanuehQmIz/YYPe4MdUH2Afp1KuCoi25llppAwdzfsGvJO21+jngFZC2wWKn20De8HRBenhdBQBr8+1Zi3S36pxWXgPjteUAcHsim3V7+9+V6fAHF+9+1fKqaJg8k9QICWkRuPWEEIw8+ilsafoR89ybqrRtSZ1BQQKbeABfNxh/Q31eW8UDSmpE9O1B29t/5n0xjpatP7De0kHj99V8Cr4vI+0BjD2OlVGqnw8pUoghIwBG+CbQylJMq3Nh/Q6y5MSyrcaCd351LTZ2PkrwsZi3RFWkdC7L5bnN1i89f7dXnLcxJfQgrSNATud11CY9+spmLPn0If0kfPBMvT74xQQHpczD0OhD/Iu3lGQ8k/Rk/uDfDr38qIeHZeG8fbgdqgVygyPEwpILwEJYd2nB6HfusgPhjCMiajxs7nr74zS5G3zqL3bU+Plq+nd5l+fxgRFdWbatp8fkrvT4Kst1R55pIFSLC/x07DGv6bbwVGI9r1g3UfvFc8g0JCog9c6TP/n1lGQHZJ0hUbi/eo5YppX6QEAsMLSeKB1Lvb4qR76sCYsXyQHasbHz69WYtpK8t2sjuOh9dinPoVpLLjpoG6v0BcuKc2hR0zqgod+/bbCcCEeHHhw7m1YKH+fzlsxn78kw2+aDrhNOSZ0QgVED8ATsHYkJYGU283/7bImIEJF1oVoWlhaM+nTwQ727YsSr2fjZuiTOEtXN149PCIl3H8cnK7VTX+ynKzaJLcQ4AW6vqI707KpV1forz0id8FYnjxg/EOutZvmEgHd+4hC/ffjrkpiGhNHogWpSDORATwsps4hWQK4A3RaTOlPGmAVGqsOp9DgFJdb3DvLvhiePj3r3JA4mRRG9oym/sbNAX/O931FLl9VGY46FzsR6N/vW63Y13yUE+W7WDu976tlFcV26t5ut1uqdWVX36eiBOJgztQ9klL7Pa3Y9R8y5j0W8nMeujzxJ/4kYB0Z9RsAorK81CfobkEtctl1LK5DvSiWYhLH1BbHBcMP2p9kBqd7Sol5OrUUBi3FE7BGRdg55XYWdNA7UNfgpzPfTrqEt7L//PF+RmuRjatZj9e3Vgv54lXP2s7r7z4PsrGFBewJodtXh9Fucc1JtPVu7gkEGdmp8vDenZrRu1V75Fxat/ZNjyf1P91mncXXEnPz79ZIoTJYJWeAgrOA7EeCCZzB4FRESGKqWWicjYSNuVUolttGKITBxJ9NYOqGszAg2N84zHQ9ADUTE9kKa5Tr716kZ2O2oa8AUsinI99O1UwDvXHMrCtbv4ZkMli9bv5tkFa3n8o9UAnDq2JwU5br7ZUEnP0nyKcj08M38tAUtRlt/yualTRX5JJ4ad/Uf8G88l8NgpXLryJ9x892p+eOZFHNQ/AS3Ew5PowRyI8UAymlgeyNXATCBSW0cFHN7mFhliEyWJ7ksnDyTQoHMzAT+4Yzu6HrQIWtEGy335H+h3SOPc5QBb6j14XNI46r7ILsHtX15I//JCTrFvewKWomJLFTuqG5g4sLmXsbOmgbkVWxnbO/3aUsTC020kxT+dS+3jp/KH7b/n1kfXM2fiJVw9fUjbzq4YngMxVVgGYgiIUmqmvTwsOeYY4qKZgOiLrlNAUu6B2DP94feCuzDm7kEBUZGS6L46eOlyPf95qW5eV99vGiyFQV2KWLpRp+OijeFwu4ShXaM3BEpA3wAAHUhJREFUTigtyObE/XvEtDFtKepK/sy38P/3Im6reJynPv6e4xZfyo0njeWwIZ3b5hzNQlimCssQI4kuIgeISFfH63NF5CW7rXti52psOmcvEXlXRJaKyDci8jN7fZmIzBaRCnu5790+tpYoSfS0yoEEbYxzjnP3ngSkbqdeVq4HXw0MnE7FtH8AMLRrU3quOC/9k+AJI6cQz5lPwiG/4EzPuzxUfz2/fvxVrnjyC7ZUxh9KjEpQQNx2Ej1gPBBD7Cqsh4EG0POiA3cA/wR2A48k1rRG/MA1SqlhwEHAFSIyHLgOmKOUGgTMsV9nBlGaKYbkQOzE+uZKL/NXp2BiooBdRhtPHkSpJg8kUggrKCCgQ1jZBY1luoO7NAlIWcG+k8NICC43HHETnPUsA7N3MLvg18jSl5l613vc+3YFtQ170WAz6PVKMIRl4XYJkqnteA1AbAFxK6WCV5/TgUeUUs8rpW4CBibWNI1SamMwWa+UqgKWAj2AE4En7N2eAE5Khj1pQXgIywqGsJq8jmCVzLH3zeO0hz5OmmmNBG2MR0CcjfoitXMPTl8LOomeXcj971QAoR5IxgtIkMFHIpe8T27nQTzg/hOPlfyNR9/+kql3vsfTn61pVt4cF77Q/mP+gDIVWIbYAiIiwcDyEYCznWPSR12JSF9gDPAp0EUptRG0yABtFOzdB2gWwtJi4cyBBMeBbKuOL4TU5vjrQ5cA370Fb9/afF+naESaUMrpgdTthJxC1u3UF7QR3ZtyG6X7UBVVwintCxfNgqnXM6H6XRaU3cRx+Uu47oVFTP/TXF5auD5ksOm7y7bw7Py1RO2XGixeyNb5LF9AmTEghpgi8BTwvohsA+rQU9kiIgPRYaykISKFwPPAVUqpynhdZxGZia4ko3fv3okzMJnEkUQPH4nuD1jJLbkMOJLoQZ6coZfTbg7bt+nvkVghLF8NlPSk3m9x/sS+dCzMadxkPJAw3Fkw9ToYfCTZL1zCr7fdxMxBx3DN7hn87OmF3P/OcgZ1LmRQ50Lue2c5oD/DacO7ND9WQzVkFYCdNPcFLDMK3RCzCut2EZkDdANmOdq5u4CfJtq4ICKShRaP/yilXrBXbxaRbkqpjSLSDdgS6b1KqUew8zXjx4/ftxpERSM8zNPYCyu6gDSkTEDi8IBieSC120NeqtK+VNf7Kczx4HYJ/ToVUF3vT5tW7GlH9zFwyVz46D66zr2Lf7vnsuSAK/j1psl8u7mKNxZvogs7KJZaZv4LjhnVjYP6d2RUjxL261mi8xz1VZDTVE3ntyzjgRhih6GUUp9EWPddYsxpjmhX41FgaVj7+JfRk1zdYS9fSpZNKSf8Lj3COJBwAan3WSQ1wuMPS6I7QyNWoHE8gX7dJCASKQdSEzq/x+2fNBCwcinK1T/fWT+fgoBJ6O6JrFw49Jcw6ofI679kxKI/8Hyn/0HPoaw76BhK5z9Awa5lPD7ice5avJVXv9bt2geUF3DK2J6ctXsnHbILgjPX6xCWyYFkPOndPU4zCfgRsEhEFtrrbkALx7MichGwBkhia9IUE36RDSbR9+CBeJPVdK/RgGASvT70NeiErONuNiSEFckDqd4CWfmQ34mKTofz9290v6tCW0DMnXALKOsPZz8Hy17T/crWzafn0pcbN5+/9v8465hr2DrgZOatrOaFL9Zz51vfMiRrLT09ipffXMaZB/ZOfkjUkJakvYAopT4Aot3qHJFMW9KG8ItsowcSfUIpZ6PFZKAC9fpLC3ogzlxIuIA4y5Ij5UBqtkDn4fDjOTz/xjJgBZBekz/tU4jAsOP0wwrA4udh9zroeQDMuZXsN66mB1dzRseBnDHhUtadcgo5z3jYUV3EQ++v4MH3V6AU9C8viH0uQ7vG/AfuizTLgdi9sCJUYQWpT/IUt756L9kQuRorOCVtEIdolHtXwScPwvYVsHstVG+GzUtgoL5X2F3XJDbBEJZhL3C5Yb8ZTa8vmg0r34V1n8N3b8Lrv6Bn/h0QaKC898F8eNzhPDN/LW8u3sTxo7unzm5DWmD+A/dFmgmI3Y03QgjraNenHOmeT71/UtLMA5CgV9E4oNAhGr4wAbFDWAuswYx3fQdvXgc5xdChDxR1gVE/hDE/AvTMgUES1nk2kxGBAYfrx5RfwPcfwmePwIaF0OdgupXkcdW0wVw1bXCqLTWkAUZA9kX2kEQX0XoSFJAHs+8F4LNkhrCUIkvp6ivL59WDjZweSLiA2GLzd/8xvD38Zq47aQIUdNIXM0ApxZ/eruCorEoqHR5I//LYPbYMe4EI9J2sHwZDBEwWbF8kWhI9YJHrCe2WGqS+oWUz9O0VDvt89bZYhOdAIuzvx80mTw8oLG8UD4BKr5/75lRw+sMfhwiIGfdhMKQWIyD7IlHGgTT4LbI9LtwuadaN119XQ9JweBu++tpm65rlQAJNAuKL0AQy2Peqqt7P7jofHQuyufeM/dvWZoPB0GKMgOyLRE2i6/YSbpFmHkigvpq95uO/6oqdWDharfjj8EACdg7Ejztinybn/OY7aho4ZlS3fbv9usHQTjA5kH2RPeRAst2iPZCwKqyAt2rvz/vW9XoZ7Is09tzI+zkFJBg68zkEpCHUGwr4GnBjeyCBCB5IdZOAVHr9DDDlowbD/7d35tFxluUC/z0zmUnSNmmarnYH2t5u0CKVtkpBVgG5VsRqEcWqvZwr7gtHT0XRIgrqlaOyeJCDchBF8OoFWZSDFhC4ItiKFMpSum9padokTZrM8j33j/ebZJJOe5PpTOad5vmdM535vvm+ya/fvDPPPO/qBRZAypHDVGEl011VWKkeX8SSLEAGkuGBcBabwwWQrOqqdDJHBtLefRq1ZDJBHEhppNto+gw917OYNW5on5UNwyg8VoVVjhzSiN7VBhKLRnJmINlriRedrJHl6YT78g+yMhDNnhwRSCUzVVgVhwQ+6J6BAMwZX1cwVcMw8scCSDlyhCqsTABJhUElUNebSRL92Iie7vrC1zBwdDamA6nW/d0PDydcTBLNmYFkt4GcPX0U8QortobhA1aFVY4cEkCyGtHDKqzM93CKKHFSRJJ9CCCq3brRdu7rLVlVWBpWXSXa26gE0iqkWhvpHAKYbIfGDQCkj9ALa9bYWt4xZQRXnH587z0MwygqFkDKkSAFtePg3y6E/Vtgx2rATaZYGY1QEZHO3kxBZhqxnl1nD0d7E1w/ES74Psy/omt/qvfjSIJUojO1DZLuvGSrW9hyq45izJuvwqrvwsYnYNvz1AdJEhqlUWsYmb2uezpg/Z4DrNvZwskT61hx4YxeOxiGUXwsgJQjQQoqquDdP4CHvgTbnwfcXFhVsQixaFdjtHYGkF6uTNi40d0/f0f3AJLM0YaSSkDFoYP5kh3tZJZ5kjADCVp206zV7NThTG5YDQ1r3DoVC69kc/Us3v9giqZoPbt3NHPVfS/wWkMLr+xq6ZzD6+KTrduuYfiGBZByJEhBJHzrJNJtJHpNVQXxiki3iRUBJOhlAGnZ5e6rarvv7zl6HNwqdRX1h+5OuAByUONUt+8CVaRtL3u1lq+nlvGTs2qZseB8qB4GQOOWfezhGT62YCK/eGYTj77cwKyxtVy+cBIzx9Yyd8IwjhthXXcNwzcsgJQjPQNI1mSKsajLQBIp7T4oL9We44Vy0LTV3VfWdN+f6/xEKwzKEUA63LH/nV7Eh9v+DBtWMWzTQ2xjEut1PJtHnsKMMHhkvAHOmTGaL547jSGVFbY4lGGUAdadpRzJXtFPot3WRI9XRDozkOwsJJLuZQaSWf0vWtl9f64qrETusSXJhMtWfpM+k9ZoHdx1MRFN06Qui2hs7e6SGTwYi0aoqYpZ8DCMMsECSDnSLQORrrmw0gHxaITKaIREKk1HMiCKCy6S7l0jeOqgG+TX1NTYfX9Hjl5c7U2w5m547dFuu5Ph6PMDVHPn+GsAaKsazddSHwdgd0v3bCaRdo7WPdcwygv7xJYjQSorA4l0jQNJKbGouAwkFdDR0UFcMgGkdxnIvn0ucOzZs9v1vLr/07B/K+2tzYccq22NcP+V8KvuqwmnwsGDCa3gxdgc+OI67lrwEFt1NPFopHNch6qyY/9BXtruXjtuS6QaRllhbSDlSHYGEol2a0SPRV0V1v6DAcn2riqmaNC7DKStxQ3yq5U22PQUrLkLDjTQPnUJPVffSOzd1NnbirbGzvaQdFiFlaCCtkQaaseyvWktNVUVjB1azWPrGnhxexNv7D5AayLMPqIRRgyx6dkNo5ywAFKOBOkejehZVVgVEWJRIZlSkge7JlDsbRtIOjxncNDa1XB+YDcdrU2HHrvl710bu1/uXHgo3vg6B7SK6rrRrN68j3U7m/nd6u2Mrq1k0dQRPLJ2F0OrYyyZN4ETRg1hysghTB9TwzBb38MwygoLIOWIpiESftlmNaJnemHFK6Ik0gGp9q52i2gvu/FGwkkXq4MDaPNOBAjam0m2HRpABr36+66NR74K8UFwYDfj92/l2WAa110yly/d+wKLb3qaRDpgwYjhXH3RTK6+aGZ+/2/DMLzCKp3LkZ7deIF0OqAjFVAdixKPujaQVNYaIJFeBpCKlAs6EQJ2b3oJgKYDrSR7ZCB71XXz3aH1rErPQQnc4MZxp/D65KVcn1rKCSOHcMeytzF0UIzzZo7mW4tnHdV/2zAMv7AMpBxJJw8JIG0dLkCMT21hycYVLE9+maCjazBgbzOQeLora4nsdgFkcLKRXW37adNK1upk7kqdy5sM5fITDnLL+npe1ON57JLTmTKqhiBQfvfHV1j76kbqBsUYW1fN31ecbV1zDeMYxAJIOdLRAvGwSTviAkhruwsQc3bey/iDr/I+HiHdcVHnKVHtRQAJ0tSlG9kSjGRiZA91jS8AECfJuF2P0UoVH0i4brkRgXXbY+xXNxX7Zbc/Syqt7GtLECgsOL6eQXFXvCx4GMaxiQWQcqSjGarCRZVibnBeouFVAGqSbwIwTTcRhGM3mnUwkxPrSd7xbiqmnImc+H6IxsNbDCIxkAi6fwtxkqzWqUxkD7GgnR1az1hppLZ9B+uYDMCyt0/mbxv28squFuYfV8+Mt9TS0NxO/eA49YPjDBsU56zpo/r3mhiG0e9YACk3VKG9uWuuqpM+CE/cwFseuJS7Y6MYtfsNAE5hHQffuAeAdZGpzA/+CVuecre/XJvzpTN5wmujL+K+XRXUSSs/TV2EoAypSNE0+Dhe/8YFnWuut6fSDIlXEIlYhmEYAxELIJ6jqt2rgJIHIUhCZRhABg+HJT+nedXNVLZuob1mEi8MPZvxG+9jxJ417NJhrF7wQ2568lGahkxh5IF11NFKTFLESBHH3QsgBBygmrPOuYQb/zyXto4UV5x+PGu3N5EMlPcdP5xYONgvHhEbOW4YA5yyDiAicj7wIyAK3K6q1xf7bza1Jfn1c1s4f9YYJhd5hlhV5ce33kSCGB2xWki1c9XSd1EJ/Hz1Ps4/6SCDKyvoGPUO1iycyRXr/8Ef3n8awcEkS3aeze6WDuoHxXnyzDm8Z8FMRtdUsn3/QZoPpkirkg4C0gGkAyUdKIEqNVUVnDxxGO+cPqbTY8m8CUX9fxqGUZ6UbQARkShwM3AusA14TkQeUNWXi/H3nly3jcce+i1Vrdt4b/pR7v/zfBprpoNIWIUjRAREIogIIhARARFEhEh4L5ljECRCuD/iqo9E2Nawh6rKOIOGT2D/3l18p/nqbh63/2w5y4E1DQE3/OBxggDSqswe6zKSwZVRThw/lGdXnIOGs/SKCIMr3Vs9abhNi24YRmEo2wACnAqsV9UNACJyD7AYKHgA2bjmcUbe/zlWssntiMBMNkOxlhnvAHpMPaUIgrK87XYA3jpzGmt3VXPa1BEc6Ejx7IZGTho/lLF11Z3nWO8nwzCKSTkHkHHA1qztbcD8ngeJyBXAFQATJ07M6w/teuJ2ZrObhrNuZPTUeTBqplvHO9ECCuE/WeuG59g+0nPZ29G4m5rkQIMbYT76RBg2yWUoqXbY8xok21g2eRHLItYGYRhG6SjnAJLr57UeskP1NuA2gHnz5h3yfG+Y9eHvkYhUMrp+eNfOkdPyeamjo6ISJryt//+uYRhGDso5gGwDslt3xwM7ivGHakeMLcbLGoZhlDXlXAfyHDBVRI4TkTiwFHigxE6GYRgDhrLNQFQ1JSKfBv6E68Z7h6q+VGItwzCMAUPZBhAAVX0YeLjUHoZhGAORcq7CMgzDMEqIBRDDMAwjLyyAGIZhGHlhAcQwDMPIC1HNa2xdWSIie4DNeZ4+AnizgDqFwrz6hq9e4Kebj05gXvlwNG6TVHVkz50DKoAcDSLyvKrOK7VHT8yrb/jqBX66+egE5pUPxXCzKizDMAwjLyyAGIZhGHlhAaT33FZqgcNgXn3DVy/w081HJzCvfCi4m7WBGIZhGHlhGYhhGIaRFxZADMMwjLywAGIYhmHkhQWQLMTTRcRFZEapHXoiIl8SkfPCx15dNxEZmvXYGzefXDL4WLbAylc+lMLFAgggIotF5E5gTqldeiIiPwEeFpHJJVYBQETOE5E/AV8BLgdQT3piiMhZIvJP4FYRWQF+uPlavnwrW2DlKx9KWb7Kej2Qo0FERFVVRM4ErgWSwEIR2ayq+0rtlbWrHtgHnCMid6lqRymcgBjwDeAM4LtAHHibiMSAVKk/SCIyBFiBey//DtwpIoNU9eoS+XhXvnwsWxkvrHz11ceL8jUgM5AeH6SNwLuAq4D5wEk+eIlINNz9N+BW4DJgaqmcVDUB3K+qi8KFvPYBS1U16cGHOwIMAbYCa1R1K7Ac+KCITC+Bj3fly8eyle1l5atPPt6UrwEXQMJlcH8nIl8QkTGquklVd6rqX4AG4AwRGVdCr8+LyFhVTYdrvZ8P/B5YBSwVkfeJyCGTmhXZ6Qsi8hZVfS7cH1PVJ4ANInJBf7jkcLtSRC4BUNUAUGAk7oOOqm7AXbeV4fH9Uj/sY/nysWz18LLy1Xsvr8rXgAogInIx8FHgx7hIfbWIzM065G5gGi6SZ59X1MLRw2sOsEJETgl/lT2vqm8CrwOfBa4Dil5Yc1yrr4lIpo41JSL1uJmN08V26eFVIyI/xVV33CkiFQCq2gC8DHw+6/CvAvNFZFZ//Ir1sXz5WLZyeFn56p2bd+VrQAUQ3IW9VVVXAd/EpX+fzTypqv8CngNmi2sw+0q4v9iFI5fXJ8Pn3i0if8U1Kv4Prtqhucg+h3P6HLjroaqNQDVwJnSm+UVHVVuAJ1R1DPAgcHPW0yuBuSJyoYhUhr8cH8TVr/cHPpYvH8vW4bysfB0Z78rXMRlAekbcrO0NwIcAVHUz8BAwWETek3X4r3H1m7/BzZ9fsAjeR686EVkI/Ah4RlXnqurlwBigYF0vj/Ja/RI4VUSqwg9TQTmC2wPh/eeBS0Vkauh5APgesBT3S3slsAjYWWi3w3iVtHz1walfylYeXv1avo7gVtLy5ev3Vy6OyQBCj18EWRH4t0CbiCwOt3cCjwMzxTEE96F6EThJVa/qcX5/ev0FOB24W1W/knXaxaq6pkA+fXV6nPBahfuqgXsoXjVDTjdVbRWRiKruAm4Bbs865h7gO7iqmJHABWH1Q0GRroZob8pXH5z6q2z11etx+rd85XTzoHx1+172pXzlRFWPmRuwELgvvIgzgWi4vyK8F+BjwB/pmkjyKuCbmeOAUR55XRM+jgIRn5wyXv38PnZeh+zrAWwJzxkDzM/4F8lrZY79mevT7+XrKJyKVrYK4dUP5SunW4nL16m4rOt7wIlZLtEsv37//jrS7ZjJQERkFHAT8DCwF1ef+nEAVU2Fh1UDf8JF7ttEZCxwMq4PNaqaUtXdHnmlwuPSWsAUvhBOGa9COfXSLa2qQfhLa2jWaTcATwNPAlXhsQX91SUiHwXuxDVcfiDcl2lgzfytfi1fR+lUlLJVKK+MWyG9euNWivIlIhERuQaX6TyCCwSfIhwYmHUd+v376/+lP6NVMW/AucCvw8eDcX2jHwSmh/u+HV78k3EDqL6NS/9uoUi/dHz18tGpD27X4n6BLQq3LwBeAX4AxIrsNR44D9iStT/z6/CbJXofvXLy2auXbteUqHwtB94aPh6OCyTzsp4v2TU7onep/nABLvilwLeA94TbI3DdEaeE2/VhYbgBGAT8Cjihx2sMGghePjoVyg1XxTWhiF6Lw+0IXdV7TwHXZh07qp/fR2+cfPYqhFuRy9fKrHJfHbpVhtv3Av9eimvWp/9HqQXyuPAC/CewBlcf+CouelcBXwd+nFVQTgN+BtRnnV/w+l5fvXx0KqBbsX7V5/L6GFCTdcwsoAkYneP8/nofS+rks1eB3PqrfL0W3g/JOiYGPANM689rls+t7NpA1F3FhcD1qvpzXF3hO4GzcfXmU0TkXHX1unuB0UAHuLpGLVJ3QB+9fHQqoFtReuYcxuscYFGmd5CqvoRr5L8+9Lkg6/z+eh9L6uSzV4Hc+qt8XRl6nZ7V+2wG0KCqr4kb2Hhq6CfFvGb5UBYBREQuF5EzxI1OBVgHjBORClV9DFgLLAD24FK9G0VkCu7LKDNRW8ELrI9ePjr57tYLr3/hsqDxmXNUdTnwURHZB8yRAg9089HJZy+f3frgNSl8fjiuu+4yXCZyYhg8CtZwXyi8nY03jMZjcF8kAfAGbtDMJ3GTmp0ITME1cN0D3AgMV9VfisgE3DQD04H/UNX9x7KXj06+u/XR6zcZL2CriByPa1T9K/ApVV17rDr57OWzW55ew4BNuIb7S3EZ92XqRpj7Sanr0HLd6OoRMQ34Zfi4Atfj4E7cL9E7gI8AQ8PnfwFcl/Ua8YHg5aOT725H4bUyfDwUOPVYd/LZy2e3o/D6dvj4HcAHi3HNCn3zKgMJ+2OvBKIi8jBQSzgKVVVT4mai3InrGfEr4L24dPS7uCj/TOa11E0Wd8x6+ejku1sBvJ4Nj23CrQlxTDr57OWzWwG8/jc89ulCORUbb9pAROQM4B+4NG49XYuknJlpRFJX970SuEFd3eFtwGki8mx43uMDwctHJ9/dfPTy0clnL5/dfPUqOqVOgbLSvkXAR7K2b8HNGroM+Ee4L4KrV7wPmBzuqwPGDSQvH518d/PRy0cnn718dvPVq9g3bzIQXPS+V7omN3samKiqv8ClhJ9RF8HH45a43ASgqvtVdfsA8/LRyXc3H718dPLZy2c3X72KijcBRFXbVLVDu/pfn4vrzgluoM0MEXkQN13x6oHs5aOT724+evno5LOXz26+ehUbrxrRoXN6ZcUNHMvMy9+CW9B+NrCxFBHbRy8fnXx389HLRyefvXx289WrWHiTgWQR4Lq5vQmcFEbtrwOBqj5Vwovvo5ePTr67+ejlo5PPXj67+epVHArdqFKIG240coCb7OwTpfbx2ctHJ9/dfPTy0clnL5/dfPUqxi2zKIlXiMh43CCbH6pqR6l9Mvjo5aNTBl/dfPTy0Qn89QJ/3Xz1KgZeBhDDMAzDf3xsAzEMwzDKAAsghmEYRl5YADEMwzDywgKIYRiGkRcWQAyjSIhInYhcGT4eKyK/LbWTYRQS64VlGEVCRCYDD6rq7BKrGEZR8G4qE8M4hrgeOEFE/gm8DsxQ1dnilip9LxDFTW/xX0AcN3agA7hQVRtF5ATgZmAk0IZblfGV/v9vGEZurArLMIrHV4E3VHUucFWP52YDHwJOBa4D2lT1ZNyiQpeHx9wGfEZVTwG+jJsi3DC8wTIQwygNq1S1BWgRkSbgD+H+F3FzKA0B3g7cJyKZcyr7X9MwDo8FEMMoDdlTXARZ2wHucxkB9ofZi2F4iVVhGUbxaAFq8jlRVZuBjSKyBEAccwopZxhHiwUQwygSqroXeFpE1gLfz+MlLgM+ISIvAC8BiwvpZxhHi3XjNQzDMPLCMhDDMAwjLyyAGIZhGHlhAcQwDMPICwsghmEYRl5YADEMwzDywgKIYRiGkRcWQAzDMIy8sABiGIZh5MX/AfypYuqWPAt5AAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] @@ -163,17 +124,13 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "# Plot the hydrographs for both basins\n", "hydrograph.q_sim.isel(nbasins=0).plot.line(hue='realization')\n", "hydrograph.q_sim.isel(nbasins=1).plot.line(hue='realization')" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -192,7 +149,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/Region_selection.ipynb b/docs/source/notebooks/Region_selection.ipynb index f61da322..aae83df2 100644 --- a/docs/source/notebooks/Region_selection.ipynb +++ b/docs/source/notebooks/Region_selection.ipynb @@ -21,7 +21,8 @@ "import requests\n", "import matplotlib\n", "import ipyleaflet\n", - "import ipywidgets" + "import ipywidgets\n", + "import os" ] }, { @@ -51,14 +52,9 @@ "outputs": [], "source": [ "# Create WPS instances\n", - "\n", - "# # locally running instance\n", - "# raven_url = \"http://localhost:9099/wps\"\n", - "# raven = birdy.WPSClient(raven_url, progress=True)\n", - "\n", - "# instance via pavics.ouranos.ca\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", "pavics_url = \"https://pavics.ouranos.ca\"\n", - "raven_url = f'{pavics_url}/twitcher/ows/proxy/raven/wps'\n", + "raven_url = os.environ.get(\"RAVEN_WPS_URL\", f\"{pavics_url}/twitcher/ows/proxy/raven/wps\")\n", "\n", "raven = birdy.WPSClient(raven_url, progress=True)" ] @@ -122,7 +118,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "89452f06cebe438181f1d08de3a2dad6", + "model_id": "6bf0347c6e9846b48bd0f5c7b54816ce", "version_major": 2, "version_minor": 0 }, @@ -150,16 +146,16 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[-71.93847656250001, 48.48748647988415]" + "[-72.33398437500001, 48.748945343432936]" ] }, - "execution_count": 11, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -171,13 +167,13 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4411003f654c4a2ab105986d88974af1", + "model_id": "a484d2457236427e97fcefe4439800a6", "version_major": 2, "version_minor": 0 }, @@ -190,60 +186,40 @@ } ], "source": [ - "# user_location = raven.hydrobasins_select(location=lonlat, aggregate_upstream=True)\n", - "user_location = raven.hydrosheds_select(location=str(user_lonlat), aggregate_upstream=True)\n" + "# NBVAL_SKIP\n", + "# Get the shape of the watershed contributing to flow at the selected location. \n", + "resp = raven.hydrobasins_select(location=str(user_lonlat), aggregate_upstream=True)" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 9, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'COAST': 0,\n", - " 'DIST_MAIN': 167.2,\n", - " 'DIST_SINK': 167.2,\n", - " 'ENDO': 0,\n", - " 'HYBAS_ID': 7129001701,\n", - " 'LAKE': 301,\n", - " 'NEXT_DOWN': 7120317402,\n", - " 'NEXT_SINK': 7120034330,\n", - " 'ORDER': 1,\n", - " 'PFAF_ID': 724083034000,\n", - " 'SIDE': 'L',\n", - " 'SORT': 96070,\n", - " 'SUB_AREA': 72417.5,\n", - " 'UP_AREA': 1067.6,\n", - " 'id': 'USGS_HydroBASINS_lake_na_lev12.96070'}" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ + "# NBVAL_SKIP\n", "# Before continuing, wait for the process to finish!\n", "\n", "# Extract the URL of the resulting GeoJSON feature\n", - "user_shape = user_location.get(asobj=False).feature\n", - "user_shape\n", + "features, ids = resp.get(asobj=True)\n", + "\n", + "user_shape = resp.get(asobj=False).feature\n", "\n", "# Examine its properties\n", - "user_data = requests.get(user_shape).json()\n", - "user_data['properties']" + "#features[0]['properties']" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ - "# Add this GeoJSON to the map!\n", + "# NBVAL_SKIP\n", + "# Add this GeoJSON to the map above!\n", + "#df = gpd.GeoDataFrame.from_features(features)\n", "df = gpd.read_file(user_shape)\n", + "\n", "user_geojson = ipyleaflet.GeoData(geo_dataframe=df, \n", " style = {\n", " 'color': 'blue', \n", diff --git a/docs/source/notebooks/Run_Raven_with_Parallel_parameters.ipynb b/docs/source/notebooks/Run_Raven_with_Parallel_parameters.ipynb index 80bc5fd6..c2d4d3a3 100644 --- a/docs/source/notebooks/Run_Raven_with_Parallel_parameters.ipynb +++ b/docs/source/notebooks/Run_Raven_with_Parallel_parameters.ipynb @@ -11,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -23,14 +23,16 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 2, "metadata": { "scrolled": true }, @@ -68,37 +70,27 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 3, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/src/birdy/birdy/client/converters.py:294: UserWarning: No converter was found for /tmp/tmp1l6f_gnt/raven-gr4j-cemaneige-sim-0_solution.rvc\n", - " warnings.warn(UserWarning(\"No converter was found for {}\".format(output)))\n", - "/home/ets/src/birdy/birdy/client/converters.py:294: UserWarning: No converter was found for /tmp/tmp1l6f_gnt/raven-gr4j-cemaneige-sim-1_solution.rvc\n", - " warnings.warn(UserWarning(\"No converter was found for {}\".format(output)))\n" - ] - }, { "data": { "text/plain": [ "\n", "Dimensions: (nbasins: 1, params: 2, time: 732)\n", "Coordinates:\n", - " * time (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2002-01-01\n", " basin_name (nbasins) object ...\n", + " * time (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2002-01-01\n", "Dimensions without coordinates: nbasins, params\n", "Data variables:\n", " precip (time) float64 ...\n", - " q_obs (time, nbasins) float64 ...\n", " q_in (time, nbasins) float64 ...\n", + " q_obs (time, nbasins) float64 ...\n", " q_sim (params, time, nbasins) float64 ...\n", "Attributes:\n", " Conventions: CF-1.6\n", " featureType: timeSeries\n", - " history: Created on 2019-06-25 09:42:03 by Raven\n", + " history: Created on 2019-10-29 11:22:33 by Raven\n", " description: Standard Output\n", " title: Simulated river discharge\n", " references: Craig J.R. and the Raven Development Team Raven use...\n", @@ -109,7 +101,7 @@ " time_coverage_end: 2002-01-01 00:00:00" ] }, - "execution_count": 11, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -121,23 +113,23 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[,\n", - " ]" + "[,\n", + " ]" ] }, - "execution_count": 12, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -149,32 +141,29 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", + "\n", "hydrograph.q_sim.isel(nbasins=0).plot.line(hue='params')" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "['observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_hc8ir6d5/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.0371048,36.562,\\n', 'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_hc8ir6d5/Salmon-River-Near-Prince-George_meteo_daily.nc,0.0198906,35.5431,\\n']\n" + "['observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_1k3pzhbp/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.0371048,36.562,\\n', 'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_1k3pzhbp/Salmon-River-Near-Prince-George_meteo_daily.nc,0.0198906,35.5431,\\n']\n" ] } ], "source": [ "print(diagnostics)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -193,7 +182,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/computing_objective_functions.ipynb b/docs/source/notebooks/computing_objective_functions.ipynb index 0af4c224..957032ff 100644 --- a/docs/source/notebooks/computing_objective_functions.ipynb +++ b/docs/source/notebooks/computing_objective_functions.ipynb @@ -15,6 +15,7 @@ "metadata": {}, "outputs": [], "source": [ + "import os\n", "from birdy import WPSClient\n", "\n", "from example_data import TESTDATA\n", @@ -24,7 +25,8 @@ "import numpy as np\n", "from matplotlib import pyplot as plt\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, @@ -32,8 +34,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# First, Run GR4JCN to generate a NetCDF file containing 'q_obs' and 'q_sim'.\n", - "This file contains 'q_obs' from the initial dataset, plus the simulated discharge 'q_sim' from the model." + "First, we run GR4JCN to generate a NetCDF file containing `q_obs` and `q_sim`.\n", + "This file contains `q_obs` from the initial dataset, plus the simulated discharge `q_sim` from the model." ] }, { @@ -77,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -94,7 +96,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -118,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { "scrolled": true }, @@ -141,12 +143,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Now that we have numerical values for the goodness-of-fit, let's perform a visual inspection.\n" + "Now that we have numerical values for the goodness-of-fit, let's perform a visual inspection." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -157,7 +159,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -170,22 +172,22 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Now that we have run the graphing service, display the plots" + "Now that we have run the graphing service, display the plots." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -194,35 +196,6 @@ "# Graph of full time series\n", "graph_objfun_fit" ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Graph of average annual hydrograph\n", - "graph_objfun_annual_fit" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -241,7 +214,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/example_data.py b/docs/source/notebooks/example_data.py index 72618002..9aa03ed3 100644 --- a/docs/source/notebooks/example_data.py +++ b/docs/source/notebooks/example_data.py @@ -9,60 +9,93 @@ from pathlib import Path TESTS_HOME = Path(__file__).parent.parent.parent.parent -TD = TESTS_HOME / 'tests' / 'testdata' -CFG_FILE = [str(TESTS_HOME / 'test.cfg'), ] +TD = TESTS_HOME / "tests" / "testdata" +CFG_FILE = [str(TESTS_HOME / "test.cfg")] TESTDATA = dict() -TESTDATA['gr4j-cemaneige'] = \ - {'pr': TD / 'gr4j_cemaneige' / 'pr.nc', - 'tas': TD / 'gr4j_cemaneige' / 'tas.nc', - 'evap': TD / 'gr4j_cemaneige' / 'evap.nc'} +TESTDATA["gr4j-cemaneige"] = { + "pr": TD / "gr4j_cemaneige" / "pr.nc", + "tas": TD / "gr4j_cemaneige" / "tas.nc", + "evap": TD / "gr4j_cemaneige" / "evap.nc", +} -TESTDATA['raven-gr4j-cemaneige-nc-ts'] = TD / 'raven-gr4j-cemaneige' / 'Salmon-River-Near-Prince-George_meteo_daily.nc' -TESTDATA['raven-gr4j-cemaneige-nc-rv'] = tuple((TD / 'raven-gr4j-cemaneige').glob('raven-gr4j-salmon.rv?')) +TESTDATA["raven-gr4j-cemaneige-nc-ts"] = ( + TD / "raven-gr4j-cemaneige" / "Salmon-River-Near-Prince-George_meteo_daily.nc" +) +TESTDATA["raven-gr4j-cemaneige-nc-rv"] = tuple( + (TD / "raven-gr4j-cemaneige").glob("raven-gr4j-salmon.rv?") +) -TESTDATA['raven-mohyse-nc-ts'] = TESTDATA['raven-gr4j-cemaneige-nc-ts'] -TESTDATA['raven-mohyse'] = TD / 'raven-mohyse' -TESTDATA['raven-mohyse-rv'] = tuple((TD / 'raven-mohyse').glob('raven-mohyse-salmon.rv?')) -TESTDATA['raven-mohyse-ts'] = tuple((TD / 'raven-mohyse').glob('Salmon-River-Near-Prince-George_*.rvt')) +TESTDATA["raven-mohyse-nc-ts"] = TESTDATA["raven-gr4j-cemaneige-nc-ts"] +TESTDATA["raven-mohyse"] = TD / "raven-mohyse" +TESTDATA["raven-mohyse-rv"] = tuple( + (TD / "raven-mohyse").glob("raven-mohyse-salmon.rv?") +) +TESTDATA["raven-mohyse-ts"] = tuple( + (TD / "raven-mohyse").glob("Salmon-River-Near-Prince-George_*.rvt") +) -TESTDATA['raven-hmets-nc-ts'] = TESTDATA['raven-gr4j-cemaneige-nc-ts'] -TESTDATA['raven-hmets'] = TD / 'raven-hmets' -TESTDATA['raven-hmets-rv'] = tuple((TD / 'raven-hmets').glob('raven-hmets-salmon.rv?')) -TESTDATA['raven-hmets-ts'] = tuple((TD / 'raven-hmets').glob('Salmon-River-Near-Prince-George_*.rvt')) +TESTDATA["raven-hmets-nc-ts"] = TESTDATA["raven-gr4j-cemaneige-nc-ts"] +TESTDATA["raven-hmets"] = TD / "raven-hmets" +TESTDATA["raven-hmets-rv"] = tuple((TD / "raven-hmets").glob("raven-hmets-salmon.rv?")) +TESTDATA["raven-hmets-ts"] = tuple( + (TD / "raven-hmets").glob("Salmon-River-Near-Prince-George_*.rvt") +) -TESTDATA['raven-hbv-ec-nc-ts'] = TESTDATA['raven-gr4j-cemaneige-nc-ts'] -TESTDATA['raven-hbv-ec'] = TD / 'raven-hbv-ec' -TESTDATA['raven-hbv-ec-rv'] = tuple((TD / 'raven-hbv-ec').glob('raven-hbv-ec-salmon.rv?')) -TESTDATA['raven-hbv-ec-ts'] = tuple((TD / 'raven-hbv-ec').glob('Salmon-River-Near-Prince-George_*.rvt')) +TESTDATA["raven-hbv-ec-nc-ts"] = TESTDATA["raven-gr4j-cemaneige-nc-ts"] +TESTDATA["raven-hbv-ec"] = TD / "raven-hbv-ec" +TESTDATA["raven-hbv-ec-rv"] = tuple( + (TD / "raven-hbv-ec").glob("raven-hbv-ec-salmon.rv?") +) +TESTDATA["raven-hbv-ec-ts"] = tuple( + (TD / "raven-hbv-ec").glob("Salmon-River-Near-Prince-George_*.rvt") +) -TESTDATA['ostrich-gr4j-cemaneige'] = TD / 'ostrich-gr4j-cemaneige' -TESTDATA['ostrich-gr4j-cemaneige-rv'] = \ - tuple(TESTDATA['ostrich-gr4j-cemaneige'].glob("*.rv?")) + tuple(TESTDATA['ostrich-gr4j-cemaneige'].glob('*.t??')) -TESTDATA['ostrich-gr4j-cemaneige-nc-ts'] = TESTDATA['raven-gr4j-cemaneige-nc-ts'] +TESTDATA["ostrich-gr4j-cemaneige"] = TD / "ostrich-gr4j-cemaneige" +TESTDATA["ostrich-gr4j-cemaneige-rv"] = tuple( + TESTDATA["ostrich-gr4j-cemaneige"].glob("*.rv?") +) + tuple(TESTDATA["ostrich-gr4j-cemaneige"].glob("*.t??")) +TESTDATA["ostrich-gr4j-cemaneige-nc-ts"] = TESTDATA["raven-gr4j-cemaneige-nc-ts"] -TESTDATA['ostrich-mohyse'] = TD / 'ostrich-mohyse' -TESTDATA['ostrich-mohyse-rv'] = \ - tuple(TESTDATA['ostrich-mohyse'].glob("*.rv?")) + tuple(TESTDATA['ostrich-mohyse'].glob('*.t??')) -TESTDATA['ostrich-mohyse-nc-ts'] = TESTDATA['raven-mohyse-nc-ts'] +TESTDATA["ostrich-mohyse"] = TD / "ostrich-mohyse" +TESTDATA["ostrich-mohyse-rv"] = tuple(TESTDATA["ostrich-mohyse"].glob("*.rv?")) + tuple( + TESTDATA["ostrich-mohyse"].glob("*.t??") +) +TESTDATA["ostrich-mohyse-nc-ts"] = TESTDATA["raven-mohyse-nc-ts"] -TESTDATA['ostrich-hmets'] = TD / 'ostrich-hmets' -TESTDATA['ostrich-hmets-rv'] = \ - tuple(TESTDATA['ostrich-hmets'].glob("*.rv?")) + tuple(TESTDATA['ostrich-hmets'].glob('*.t??')) -TESTDATA['ostrich-hmets-nc-ts'] = TESTDATA['raven-hmets-nc-ts'] +TESTDATA["ostrich-hmets"] = TD / "ostrich-hmets" +TESTDATA["ostrich-hmets-rv"] = tuple(TESTDATA["ostrich-hmets"].glob("*.rv?")) + tuple( + TESTDATA["ostrich-hmets"].glob("*.t??") +) +TESTDATA["ostrich-hmets-nc-ts"] = TESTDATA["raven-hmets-nc-ts"] -TESTDATA['ostrich-hbv-ec'] = TD / 'ostrich-hbv-ec' -TESTDATA['ostrich-hbv-ec-rv'] = \ - tuple(TESTDATA['ostrich-hbv-ec'].glob("*.rv?")) + tuple(TESTDATA['ostrich-hbv-ec'].glob('*.t??')) -TESTDATA['ostrich-hbv-ec-nc-ts'] = TESTDATA['raven-hbv-ec-nc-ts'] +TESTDATA["ostrich-hbv-ec"] = TD / "ostrich-hbv-ec" +TESTDATA["ostrich-hbv-ec-rv"] = tuple(TESTDATA["ostrich-hbv-ec"].glob("*.rv?")) + tuple( + TESTDATA["ostrich-hbv-ec"].glob("*.t??") +) +TESTDATA["ostrich-hbv-ec-nc-ts"] = TESTDATA["raven-hbv-ec-nc-ts"] -TESTDATA['donnees_quebec_mrc_poly'] = TD / 'donneesqc_mrc_poly' / 'donnees_quebec_mrc_polygones.gml' -TESTDATA['watershed_vector'] = TD / 'watershed_vector' / 'LSJ_LL.zip' -TESTDATA['mrc_subset'] = TD / 'donneesqc_mrc_poly' / 'mrc_subset.gml' -TESTDATA['melcc_water'] = TD / 'melcc_water_management' / 'zone_gestion_leau_saintlaurent.gpkg' +TESTDATA["donnees_quebec_mrc_poly"] = ( + TD / "donneesqc_mrc_poly" / "donnees_quebec_mrc_polygones.gml" +) +TESTDATA["watershed_vector"] = TD / "watershed_vector" / "LSJ_LL.zip" +TESTDATA["mrc_subset"] = TD / "donneesqc_mrc_poly" / "mrc_subset.gml" +TESTDATA["melcc_water"] = ( + TD / "melcc_water_management" / "zone_gestion_leau_saintlaurent.gpkg" +) + +TESTDATA["cmip5_subset"] = ( + TD / "cmip5" / "tas_Amon_CanESM2_rcp85_r1i1p1_200601-210012_subset.nc" +) # TODO: Replace the following files with subsets and set originals as production data -TESTDATA['earthenv_dem_90m'] = TD / 'earthenv_dem_90m' / 'earthenv_dem90_southernQuebec.tiff' -TESTDATA['hydrobasins_lake_na_lev12'] = TD / 'usgs_hydrobasins' / 'hybas_lake_na_lev12_v1c.zip' -TESTDATA['simfile_single'] = TD / 'hydro_simulations' / 'raven-gr4j-cemaneige-sim_hmets-0_Hydrographs.nc' -TESTDATA['input2d']=TD / 'input2d' / 'input2d.nc' \ No newline at end of file +TESTDATA["earthenv_dem_90m"] = ( + TD / "earthenv_dem_90m" / "earthenv_dem90_southernQuebec.tiff" +) +TESTDATA["hydrobasins_lake_na_lev12"] = ( + TD / "usgs_hydrobasins" / "hybas_lake_na_lev12_v1c.zip" +) +TESTDATA["simfile_single"] = ( + TD / "hydro_simulations" / "raven-gr4j-cemaneige-sim_hmets-0_Hydrographs.nc" +) +TESTDATA["input2d"] = TD / "input2d" / "input2d.nc" diff --git a/docs/source/notebooks/getting_variables_other_than_flow.ipynb b/docs/source/notebooks/getting_variables_other_than_flow.ipynb index d1a70dd9..b8398aa6 100644 --- a/docs/source/notebooks/getting_variables_other_than_flow.ipynb +++ b/docs/source/notebooks/getting_variables_other_than_flow.ipynb @@ -23,8 +23,10 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, @@ -71,22 +73,10 @@ "execution_count": 3, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 3, @@ -95,7 +85,7 @@ }, { "data": { - "image/png": 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As+qzr1oajbVfLg8GotmvU55PHBHi5kIEhl3dEf76v5+hNxIfMctevFTVEXOnBMZAbFPVe/KqpERo7hzg/T95CoAvvPPQA1pn2GZSlwdB6MME7njzCqqMAPDUpj2090e5+zOncMz8Bl80ZHv1Wi8ivwPuxQ0xAVbmmonNbf0A/Ov5R3HJ8gUH9FmO1aWXBYPRRNYdfvOJWJlroOjsd5t7Lmms9U1DtgaiBtcw/FXaNitzzUBz5yBwYMnpFCE7YcuC/miCpoZgeBBqIc3A0DEQpSIkTD6AKMSBktWRVfWKfAspBe5f28JXfu/2LTyQ3EMKS1KXB72RGPXV2XX4zSeOrSgXKDr7o0ydVImIf/Njsp0otxi4hjfPpP5AfmQFnxe3d7HqjQ5UQVG2dQzwm2e2MX9aDZ8+/WBCOZj0ZEnq8qBnME59TTCS1JajDg4d/VGm1fobesx2VP4BuBE3B2FDCPi729ewsbVvxLZj5k3ht584KWcuoa0HUfpE40kGY4lAeBAhx0KaQaJrMMaULNeOyRfZXskiqvqjvCopIuKJJG+09/PxUxdz7dmHICIIbi+dXLZLcBxbk7rU6Y24i0jV+3whAAg7jpW5BoiheDLrxcXyRbYG4ocicgPwICOrmJ7Pi6qAs6NrkFhCOXR2HXV5vPMLOxYTLnV6InGAQISYwiHzWIPEUCxBZd3EJ9rmgmxH5VG4E+XOZGSzvgm1+haRBuAXwJHe51wJvAbcipvneAO4SFU7J/L5+WbzHreUdcmM/JafWbO+0uWeNTt54OVd9KQ8iACEmMKOQzxh4y0oRBNJqsL+zrDP1kB8EFiiqtEcHfeHwB9V9QIRqQQmAV8BHlHVb4vI9cD1wHU5Ol5O2eLNdViUZwMRshBTyfLDhzfQ2jvErPpqjpk3xffFggAqQtZePkhE40kqi8RArAEagNYDPaCI1AOnAZcDeEYnKiLnAqd7u90MPE5QDcSefuqqw0zPc4VByEJMJcnungivt/Xz+bMP5dqzD/FbzjAWYgoWQ/Hi8SBm4c6mfo6ROYiJlLkuAdqAX4rIMcBq4Fpglqq2eJ/bIiIzM71ZRK4GrgZYsODAZipPlLbeIWbXV+e9PtnKDkuTG5/aAsAZhx34ZMpcEnYc8yACRDSepHIcC4zlg2wNxA05PubxwDWqulJEfogbTsoKVV0BrABYtmyZL7c7PZHClJ+FHMyDKEE2t/Vx2Ow6jp7nT3+dsagIieUgAkTRhJhU9YkcHrMZaFbVld7zO3ANxG4RmeN5D3PIQTgrX/REYsysO/CZ0vvD1oMoTXZ2RWhqqPFbxpsIh6zMNUi4SWqfl6Hd14sict/+PiCbfdJR1V3AdhFZ6m06C3gFuAe4zNt2GXD3eD63kHQXaAJLak6FJapLi5buQeZMyf8NxnipcIRYQq0fUwCIJ5Ikkhp4D+JUEdlXm28BJrLS3DXAb70Kps3AFbjG6jYRuQrYBlw4gc8tCD2Dceqr81+3HvJyHAlVHPxdr9jIDdF4ks6BWE56deWasBfvTiSVcMjGm59EvVxQ0A3EuVl8xrhLX1X1RWBZhpfOGu9nFZI127voHIjSW6AcRMqDSCSVACwXYOSAzgH3dPG7x04mUv3D4knF58hG2RONewYiyEnqHOceipq1zd2c+9M/Dz+fVYAQQeqEtYZ9pUOH1+M/3yXSE6EitNdAGP4y5BmIKp+XovV/fn+RcM+aHVSGHX595XKqK0Ic0VSf92MOh5jshC0ZUgYiiB5E2HEvRnErdfWdovAgjL1sbutnyYxaTlwyvWDH3JukLtghjTwTZAOR8iBiVurqOykPwu8cRFZHF5EzRWRSvsUEkYFonKc27mFDay8Lpxf2K0jlCW0uROnQNej2Xpoyyf/eS6NJJamt1NV/Br3Fwf1eqzxbD+Jy4L9EpB34k/d4KqjN9HJFMqlc8t8rWbO9C4APHju3oMcPORZiKjUi3ok/qTJ4zns4laQ2D8J3UsUMU4thwSBVvRRARJqAC4CfAk3Zvr8YuempLdyxuplXWnr4zBkHceZhMwveUM0xA1FyDMZcA1Htc+ggExWeB2HtNvwn5WlO9dnTzHbJ0Y8Cb8dt+70H+AmuF1FyPLO5nav+5zn6owmWNNZy0bJ5fOGdS3OyhOh4SZ8HYZQGg7EEFSEZDucEibBVMQWGbs+DmFJTBB4E8APgdeC/gMdU9Y28KfKZZ7d00B9NcM2ZB3PZyYuYMdm/BTtsJnXpEYklqA7opJZUFZN5EP7TOeB6EA3F4EGo6gwROQK3Tfc3ReQQ4DVV/Vhe1fnA1vYBZtdX88W/Wrr/nfNM2EJMJUewDYSNt6DQNRBjclV4OOznF9lWMdUDC4CFuCu+TWHvynIlxbaOfhYUuFppLIaT1BZiKhkGownfK1PGImxlroGhJxIrSDuf/ZGtgqfSHj9R1eb8SfKXXT0RTlgw1W8ZgLseBFiIqZSIxJJU+zw7dixSd6s2Uc5/+ofi1FYViYFQ1aMBRKQOdw3pkkRVae0ZYmZAGqmZB1F6DMaC60E4VhQRGPqG4kwOgAeRbYjpSBF5AXgZeEVEVovIkfmVVnh6h+IMxZM0+piYTsexVhslR5BzECGbuR8Y+obiTA6AB5Gtr7sC+IKqLlTVBcAXvW0lRWuPu5rqzPpgGAg7YUuL1p4IK7d0BNhAuD/Ng/Cfvkic2gBMpszWQNSq6mOpJ6r6OFCbF0U+8lKzO2N6yYzJPitxsRO2tLj+rrUAzArIDchoLOcVHPoDEmLKVsFmEfkq8Gvv+UeBLfmR5B+3r2pmzpTqgnRqzQYLMZUOv125lUfXt3L24TP5xnlH+S0nI9baJTj0FlmI6UqgEbgL+L33+xX5EuUHbb1DPL25nY+cuGB4gprf2HoQpcF9L+3kH37/MtNrK/naOUf43qFzLKwoIhioqlfF5H8oMtsqpk7gb/OsxVc2tfYBcPS8Bp+V7MXWgyhuHnl1N5/+7fMMxZPUV4d59IunB7KLawrzIIJBTyROUqHB5zYbkH0vpkOBL+FOkht+j6qemR9ZhWdTm2sgDpoZjPwDWKuNYqY3EuNrd69jSk0FlyxfwAUnzAu0cQC7IQkKQVozJNsg1+24fZh+ASTyJ8c/nnm9nca6KpoKsJRotpjLX7w8/OpudnQN8u3zj+Li5Qv8lpMVjoU0A0FHv1tNOX1y8RiIuKr+LK9KfGTLnn7+d20LF791PiLByD+AJamLmefe6GRyVZgLl833W0rWmAcRDNr7UuuW+1/tlm227F4R+bSIzBGRaalHXpUVkK/fuw4gcCezJamLk1uf28bvVm7j1INn+NImfqJYDiIYtKdCTEXkQVzm/fy7tG0KLMmtHH/Y0TnIMfOmcMLCYPRgSpG6o7MVvoqHTa19XHfnWmorQ1xxyiK/5YwLuyEJBqkcxPRiyUGo6uJ8C/GTXd0RPnTCPL9lvAmvPb+dsEXE81vdVXjvv/btLJxeXHNJUwbCFgzyl/a+KJMqQ4GYcb/PEJOIvFVEZqc9v1RE7haRH5VKiKk3EqN3KM6cACWnU+x1+X0WYmRNc+cAjkBTQ43fUsaNzaQOBh39Q4GoYIL95yB+DkQBROQ04NvAr4BuSqQX067uCABzAnhCh62Kqeh4YN1uZtVX+77Qy0SwHEQwaO+PBiK8BPs3ECFV7fB+/zCwQlXvVNWvAgcfyIFFJCQiL4jIfd7zxSKyUkQ2isitIlKQb6glZSAC6EHYHV1x8dwbHby2u5f5U4Ox4NR42bsGus9Cypz2vijTg9JRej+vh0Qklac4C3g07bUDbRRyLfBq2vN/A76vqocAncBVB/j5WdHSPQjA7ICsAZGO3dEVF398eRcAP/3I8T4rmRjDOS8bb77R2R/ltd29LJ1d57cUYP8G4hbgCRG5GxgE/gQgIgfjhpkmhIjMA96HO/EOcScfnAnc4e1yM3DeRD9/PLR0RxCBWQE0ELaAS3HR2R9l/rQaGuuCcfc3XsKehbDx5h+vtPSQSCqnHjzDbynAfrwAVf2miDwCzAEeVB0eOQ5wzQEc9wfAl4GUmZwOdKlq3HveDMzN9EYRuRq4GmDBggOfobqrO8KMyVWBbKAWslYbRYW7jnCw22nsi5QHYR6rf0S9ipRJlf5XMEEWE+VU9RlV/b2q9qdt26Cqz0/kgCJyDtCqqqvTN2c69Bh6VqjqMlVd1tjYOBEJI2jpjgQy/wDWaqPY6B4sbgNhM6n9JxZ3DURQihz8aDh+CvABEXkvUA3U43oUDSIS9ryIecDOQohp6R5kUUDr1S1JXVz0DMZZNKM4E9RgOa8gEPMqBIIS0Si4ClX9e1Wdp6qLgIuBR1X1I8BjwAXebpcBdxdCT1F4EHbCFgXFHmISEURsYqafxBLB8iCCocLlOuALIrIJNydxY74P2DcUpzcSZ/aU4M2BACs7LDZ6BmPU1xSvgQB3zNkNiX9Ehw1EMHp4+bqmnbe29ePe75uB5YU8/i6vxLWpIZgehJUdFg+qSn80QW1AkosTJeSI5bx8JOVBVJoH4T+pSXJBnAMBlqQuJoa85GJVAPrnHAghR0iYy+obQUtSB0OFT7T2uAtzzAyogbD1IIqHYQMRkOTiRAmJeRB+MhxiCsg4CoYKnxiMuYvjBTUsYPMgiochbywFoQPngeA4YuPNR1JVTEHJQZS1gYh6d31BKSkbTchmUhcNJeNBWA7CV1LXpAonGOMoGCp8IuXOBdVAOFbmWjQMxUvEgxCx9vI+EkskCTsyfO77TTCvjAVi2IMISEIoEyHHyg6LgUisNDyIsIWYfCWWSAYmQQ1lbiCG4gkcgXCA/iGjsaRhcZDyIEqhislWlPOPWEIDFdEIjhIfiMaTgfpnZMJxLEldDAx5HkR1wMfT/nAcm0ntJ1HzIIJDNJ6kKhzsO76w41hMuAiIlIoHYTOpfSUWT1IZkAomKHcDkSgCD8J64xQFQyWSg3AcsfHmI7FEMjBzIKDMDcRQPBnoBDVYkrpYSJW5lkIVk9kHf1BVNu/pD9Q1KThKfMANMQX7K7C69OJgIOqFmAI+nvaHeaz+sWF3Hy81d3PO0U1+SxmmuEfzAVIUSWqxssOgE08k+fmTr1NfHWZmkS43msIRCzH5xbNvdABw3nFmIAJBMeQgLMQUbCKxBDfcs46t7QOcvnRmoEums0FsopxvPLelg5l1VSyYFpxFp4p7NB8gxRBicmweRKC58akt/HblNuZMqeYHHz7WbzkHTMhxY+FGYfneQxu4Z81O3rp4GiJWxRQIiiHEFLKZrYFm/a5eAO757KmBaY9wIFiIyR8eXLcLgOvffZjPSkYS7KtjnonEE4GfB+Emqf1WYWSioz/KvWt2csbSRhqLPPeQQkSw+5HCs6snwkdPWsD8AIWXoMwNRM9gnPpqXxfV2y+O2EzqoPLM5nYAjpw7xWclucOqmApPJJagayAWyIXLytpAdBfBGsKWpA4ug15p6wUnzPNZSe6wEFPh2do+AARz4bKyNRDJpNITiTEl4AbCktTBJVIiLb7TcT1Wv1WUF3es3k7IEd62ZLrfUt5E2RqI3qE4qgTeQFiSOrhEhhv0lZKBMA+i0Ozpi9LUUB24/AOUsYHoGYwBFEWIydovB5NILNWgr3ROI2u1UXj6huLUVgYzF1o6I3ucdKcMRHWwDYTd0QWXSCyBSPG310jH2n0Xnv6hOJOrzEAEitRyo0G/+7MkdXCJxBJUh0OBmth0oFjOq/D0D8WpNQMRLFJx/VDAT27rzx9cIrEk1QG/wRgvNg+i8PSZB7EXEZkvIo+JyKsisk5ErvW2TxORh0Rko/dzaj51pC66oYDPfg1Zf/7AEoklSqqCCSAk1mqj0PQPJaitCuY48uP2Jw58UVUPB04CPiMibwGuBx5R1UOAR7zneSPlRjtB9yAsxBRYIvFkyRkIy3kVHgsxpaGqLar6vPd7L/AqMBc4F7jZ2+1m4Lx86kjVegfdg3Cs1UZgGYwmSipBDV6IyeZBFAxVpT9qIaaMiMgi4DhgJTBLVVvANSLAzHweO+VBBL07c8habQSWoXiCmspS8yCsiqmQDMYSJBXzIEYjIpOBO4HPqWrPON53tYisEpFVbW1tEz5+6qJrISZjoqSqmEoJCzEVlr6hOGAGYgTXg+bdAAAZD0lEQVQiUoFrHH6rqnd5m3eLyBzv9TlAa6b3quoKVV2mqssaGxsnrKFYktR2wgaXUqxicosi/FZRPvQPuZMtJ1uS2kXcovEbgVdV9XtpL90DXOb9fhlwdz51WJLaOFBKsYpJLMRUUPpTHkRAZ1L7oeoU4GPAWhF50dv2FeDbwG0ichWwDbgwnyKSxeJBODZxKagMlqCBsFYbhSUVYgpqkrrgqlT1KWCsq/JZhdKxN0kdbAMREmvWF1TcEFOpGQjzIApJv+UggkmimJLUdsIGkqFYouRyEI7N3C8olqQOKKm7pHDAPQjH6tIDSyRegiEmx0JMhWRvktoMRKBIFMlEuZCD3dEFkHgiSSyhJVjmaiGmQrKja4CQI0yrrfRbSkbK1kAMz4MIvIGwEFMQicS9xYJKMMRkBqJwvN7az8Lpk6gM6Iz8YPo1BWA4SR3wHIQjQjyRZCAaJ6luSKzUwhrFSGqxoFKbSW3dXAvLG+39LJlR67eMMSlfAzHsQfgsZD9Uhh06B2K85WsPAFAREv7v2rdz8Mw6n5WVNykDUZIhJrMQBaM3EqdhUjDDS1DGBiJZJB7ElacsZmZdNSLQ0jXIzU9vZWdXxAyEz2xtHwBgRl1wT+6JYCGmwuIuNxrcm4yyNRDF0mpj/rRJ/M3pBwHwUnMXNz+9lVjCypr85pd/3sKkyhBvWzLDbyk5xVptFJaBaJxJAa1ggjJOUieKJEmdTtiLh8Ws/7dvRONJHnutlYdfbeWTpx1UgjkIq2IqFNG4WwkX1BJXKGMPolhCTOlUhl2tcZsY4Rs33LOOW57dRmXI4fzj5/otJ+dYq43CMRB1J8lNCvBNRhl7EO7PoIeY0tnrQZiB8IsXt3cxqTLEPdecwvxpk/yWk3McsXk3haIv4I36oIwNRLJIurmmEw65Wi3E5A+/evoNXm3p4aMnLeSw2fV+y8kLlqQuHANRtxJuUkBbfUMZG4hiSVKnUxkyD8IvXt7RzdfuXsfUSRW864hZfsvJG9Zqo3AEvVEflHEOIj7crM9nIeMg7BmIuHkQBWNzWx/f/r/1bGrroyrs8MSXz6C+usJvWXnDWm0UjldbegGYXV/ts5KxKVsPIplUHHFnjhYLe0NM5kEUiv97eRcPvrKbyVVh/vasQ0raOICFmArJ46+1snD6JA6bHdw5TWXrQSRUiyq8BOkhJjuBC8Xmtn5m1Vdxz2dP9VtKQUi12lDVorp5KkZ2dg+yeEZtoL/nMvcggvuPyUSqNXncPIi8MxCNc8HP/sKdzzdzUONkv+UUjNQ9kzkR+WdXd4Q5U2r8lrFPyteDSBafB5HSayGm/HP7qmZWbe3k8pMXleR8h7FIzQtKquKMufCjMZo/bWxjxZObiSeUT5y2mDMP23chw1A8wZ6+KHOmBDf/AOVsIFSLapIcuO5/ZcghZnXqeWdr+wC1lSH+6QNH+C2loKQ6C9gQyx5V5fO3vkhvxK1Kum9N9X4NxO7uIYDAG4jyDjEVmQcBbqI6FjcPIt/s6Rti+uQqv2UUnNQ9kyWqs2dPX5Q9fVH+4X2Hs3R2He390RGv37m6md+u3Dpi287uQQALMQWVYkxSA1SEnOESXSN/7OkbYsbk0urUmg1OWojJyI6dXe7FvmlKDdNqK+lIMxC3rdrOl+94CYDzjp07POdhV3cEgDkNwfYgytdAJItrFnWKipBYDiJPdA/GuOv5ZvqH4mxs7eO4+Q1+Syo4zrAH4a+OYmLYQDTUMG1SJZta+wA3z/mdP742vF9L9+Bwm/5Xd/UAwQ8xla2BSCaVUBEG2MKOYwYiS15t6eGu55v5+/ccnjGc2D0Y49ktHSSSSRJJWPHk66xp7h5+/bgFUwspNxCYBzF+dngGYm7DSA/i/rUt7Okb4qpTF3PjU1vY4a3j0t43xK+f3srZh89kUoD7MEEZG4hiTFIDVITFZlJnyZduX8O6nT1ctGw+h8x682Skr9y1lv9d2zJi2zfOO5IPv3U+IZGizFEdKKkLVld/rOQnBeaKHV2D1FaGqK8J09RQw0A0wa7uCI+ub2VmXRWXn7yIG5/awvaOATbu7uXCnz9NJJbg8+881G/p+6UsDYSq8lJzF00NwU4QZaLCcYiaBzGMqnLbqu2090c556gmFkzf22E11Wf/4VdbRxiI19v62NzWz/+93MIlyxfwsZMW4jju/vOmll6H1vFwrBdWW72tY8R3aWRmKJ7gl39+g7kNNYgIyxa5XuedzzezrWOAJY21zG2oYcbkKp7Z3M66nd30ReLcfOVyjmia4rP6/VOWBqJrIMaG3X185b2H+S1l3NRVh9nWMWAzXT3eaB/gujvXAm61yAOfO224Z9W0WjfJ/ONHN/LXJy5gSo17R/zBn/6ZHq8k8f3HzOEtTaXZmXUiLJ1dx4zJVdy7poUPHjfPbzmB537PA+0ejAFwRNMUptdW8u8PuLmHDy+bj+MIZx8+kz+8uINILMlphzby9kMafdM8HgIVhReRd4vIayKySUSuz9dxWnvdGuRi9CAuXDafl5q7+f5DG/yWEghavHLBy09exOtt/fzksU3Dr3UNxKitDBGJJfja3S+TTCqd/dFh49AwqYITFpZfnmFfhBzhsrct5NH1rdz30k6/5QSSwWiCT/56FZf/8lluX9UMwO8+cSLgfn8rLl2GI27C/8Ql0wC44pTFw4n/4xcUT/FDYDwIEQkBPwXeCTQDz4nIPar6Sq6P1drrlpjNrAt2BUEmPnLiAtY2d/OjRzexeU8/V566mGPnNZRlvBygtcc19h89aSE9gzF+8PBG3tjTz+Fz6nl6czunL23khAVT+e5DG3hjT/9wEvpbHzyKUw+eQVU4uL34/eKT7ziIh9e38tnfvcD3HtrA+49u4v3HNHFQ48i+QTu6Bvn7u9biCFx16mLetmT6sPdWyqze2skD63YPP79o2TyOnrf3on/Cwqls/tf3jXjP0tl1PPi502juHBwOQxUDgTEQwHJgk6puBhCR/wecC+TeQHgXlca64psIJSJ86/yjmD2lmp8/+Tr3vdTClJoKGiZVUBlymD2lmtn11cyoq2JyVZjayhC1VWHiSWV7xwBhR6itCjO5OsykyhAhxyEkQshxH2HHTc6GRBgrgpVx85j7Zn5hXJ+9Dx58ZRcAs+qr+M4FR9PUUMOKP23mDy+6d78nLZnOJ09bwtypNfzLfa9QERI+c8bBXLJ8voXoxqAy7PCbq5bzw4c38vy2Tn706EZ++MhGptdWMm9qDXXVFUyrreS+l3YO3xU//lobNRUhDptTx/ypk2isq2JabSU1FSFqKkPUVISoCjs4juCIeHfY7hiT0c/HOQrG+28cjCboGoyOGPthb/ynbrRUFVVQlGQS1Nv2aksvT2xoBeD3nz6ZXz29lStOWZzVcRfNqGXRjNrxifWZIBmIucD2tOfNwIn5OFAqxDSzCA0EuG7s5995KB9/+2IeXLebVVs76BqIoQotPRE27G6jvS/6pgl1Icdt5VxqFYyNnjEUEb70rqVcdepiXtvdy7ypNcNJ5/OPn8c5RzeRVKW6wryG/VFXXcE/nvMWwA3jPbq+lRe2dbGjc5DeSIzmzgEWTJvEp08/mA8c28Tjr7Wxcks7r7b0sKa5i9aeIQZjCZ//ivwwuSrMiYuncdyCqSVfCi0akKuFiFwIvEtVP+49/xiwXFWvGbXf1cDVAAsWLDhh69atb/qs/dHSPcjG3X2cdmhxJIomylA8Qf9Qgv6hOCFHmD65kgrHYTCWoG8ozkA0QSKpIx+qw/MCMpFpvIw1gsYaWjrWOyY4FJfOrivLthhBJxJLeI8kg97vqRuUpCpJ76d6v6tObD3sMcfTGIQdh8a6quExH08mSSZxf6oCrifjiOvL7PV03DLgRdMnFb33KSKrVXXZ/vYLkgfRDMxPez4PeFOWTFVXACsAli1bNqFLypwpNYHvgZILqsIhqsKh4WqeFLVV4UAvc2iUBtUVIfPWipwgZZSeAw4RkcUiUglcDNzjsybDMIyyJTC3kaoaF5HPAg8AIeAmVV3nsyzDMIyyJTAGAkBV7wfu91uHYRiGEawQk2EYhhEgzEAYhmEYGTEDYRiGYWTEDIRhGIaRkcBMlJsIItIGjH+mnMsMYE8O5eQK0zU+gqoLgqktiJrAdE2EA9G2UFX3O1O4qA3EgSAiq7KZSVhoTNf4CKouCKa2IGoC0zURCqHNQkyGYRhGRsxAGIZhGBkpZwOxwm8BY2C6xkdQdUEwtQVRE5iuiZB3bWWbgzAMwzD2TTl7EIZhGMY+MANhGIZhZMQMhBF4pNhXZykw9n2ND/u+xqbkDUQQ//kiMsn7GShtInKGiMzyW0cxISJBPIcmA4hIoFbrEZEPiMhBfuvIwPD3FMBz0tfxFcTBfcCIyLtF5PLUUz+1pBARR0QWiMhTwNcANCAVAiJytog8B9xOgMaEiJwrIncB3xCRJX7rSeFd6L7gt450xGWmiDwO/AJAVQOxKLQ3vp4GbgTm+K0nhYi8T0QeAr4nIqdBMM7JII2vwFwMcoGIVIjIvwM3Ad8UkcNUNRmEOylVTQJR3JWXjxORU8HfOxYRmSIidwP/AHwZ2AIs81uXd/wjgG8AvwRqgS+JyLnea76MWxEJi8h1wI+A/xCRYwM0vhSIeI+jReQ94Ot3JSIyWUTuBf7RezwDLPRTV5q+RcA3gR8DrwJXi8jHvddsfHmUlIFQ1RjwEnAy8H3gX7ztgbiTAg7DHYw3A58G3+9YQsDtqnqGqj6Gu8TriQHQBa6hekhV78U9kZ8ErhSRes/YFhxVjQOv4f4fvwD83Nvu+/jyLmrzgBeB69nrpfr1Xamq9gG/UdXTVfUR4I/AuX7qSuMg4ClVvQf3JuQXwDUiMtW7KBf8BimI46voDYSIXCMiXxaRv/I23aqqbwC/BuaLyPu8/Qq6el6arrPSNr8OJIC1QExEPiQiC33QdZ2InKWqHar6G2+74Ho3ce95QceGiLxHRA5P27QOeLeIVKlqG66B2A5cXWBdfysi3xaRi7xN/6uqEVX9ATBTRP7a26/CJ10fguEL7k7gUODPQIuIfEpEDvFJ14Werlu97SGgC9guIlWF1OQd/wIROTFtUzPwIW98RVT1ceAvwFcLrCuQ42sYVS3KB1CBG4J4ErgC2Aa8G6hJ2+cK3LsE33V5r50PfNn7/VtAO7DCey4+fV/Vafu8B9hY4O+rCXga2AF8L/U94Ho3/w1c5z2vAt6P6xlOLoAuAT6Pe7G9ANfzuxyYmbbPB4EdBf6+xtI1DdfrusHb70tAP3Cv9zzsk67GtH1OBtYX+PuaCTyBazz/ADhpr/0K+EGa/mOAO4BZ5Tq+Rj+K2YOIA28FrlHVX+LGOC/Ei6F73A60i8hHAUTkOJ90fVhE3gpsAo7w4v4fAlbjupSoNyIKrOtCb1uK54A1InJSnrWkMwTcClyFe9Kcl/baLcC7ROQQVR3CzeFMVzd0kVe8/8cZwD+q6h24J/MxwLvS9vk9sEFEvgRuMtYnXccC7wR2AaeJyP24NwF/BjZ7b81rmGIf39e70/b5C9AsIh/Ip5ZRulqBuz0dLcAn017+Z+AcETnC0x8BeoGyHV+jKUoDISLifcFrcL9UVPVXQBtwsohM97b14d5x/kpEWoEFPulqBU4FDgZmAc8Dh+O6s2eKyEyfdI34vnDv0gXoyaeedFS1HTcp9xfci9lZIjJd3bjrk7h3fytEpAk4DUjkO1yYFl5bBbzd0/lHYAOugV+atvvfAN8RkV3AXJ90vQYcjWsotgPPqeoRwMXA6SIyN583IFl8X4d5+9UD64FYvrSMoevHwCvAg8D7RGSOp3ETbmXVf3pFIx/F9Tjymh8J6vjKRFEZiNQXmzbYu4EmEZnnPf89cBJuOAUReRvu4LgNOE5V7/ZJ1x+AtwHPAuer6tfVjRmvBz7s3eX4oWvE96WqO4DZeEYkX4zOb6hqUlV7cO94Y7gXNlQ1rqpfBx4Hfoh7EbxO3WRe3jTp3gTqJqBORI7ynj8BTAHqvPccixsGuxM4XlVv9knXk0A9rsH/lKre4O3fAZzi/V/90JX6viZ7+/XgJtLzNtcmky5VjXlj5i+459y1afv8K66RuApYClylqoN50ibpugjA+NofgTYQInKqiPxMRFIVP0lveyph8xDuXflbRSSsqitxY7GpxPAe4EpVvTiXJ8kEdD2Ne+F9h6oOiEjIu6vvzmW45AC+rzPTPuavVPWWXGnajy5nVLXIOuAF4DARqU95Vp6RuFRV359LYyoix6eSgGknbfoEs2dxQzPv9L6vV3Dv4lJhzHbg06p6oaru9FHXOtzy0eNUNZIaX977czm+DvT7ArhYVf8nV5r2o0tGja89uJV6h4rIPHHnjUz1vOlPqupFqrorh7qWi8gPROTjIuKkbtT8Hl/jIbAGQkSOB36GG455r4h8X0RS4ZGY9/NZ3LLW04FLvbe24SZ8UNWNqvpcQHS1pulK5NrlP8Dva33qc1S1v4C6kqqq4s5fcbw8w224+ZKXgcfEm9mdy7s677rxL8AjwBdE5BRvu+MZ7oR3zE24eZmDcUtHwc2ZbPVe366qawOk6w3v9ZyOr1zp8vaJFFCXeuOrStxqpYSqPol7I/Iy7h37DE9XNIe6KkTke7hlqutxQ1ff9V4L+TW+JkJgDQSwHDeW+t/AJ4AB3Phhyv36hvdPuBM3VHKxiLyEe8F70XQVja5/xg0DNnj7X4vr7v8O9454d64FeRfPV4EPA//p6Ro2WCldInIjbiHBj4DlIrIa6AAeyLWmHOl60HS9SdcNuHMc5njPP4WbqP45cLSqbsyDtDrcqqn3qep/AVfiJsOnpYyDH+NrQqiPJVTpD+Ai3MkhJ3vPl+PeTc72np+Jm3D+kLfvb4GD097fCMwwXUWv64PAYQXQ5eAm5A8H/h9wibc9jFsRNFrXZKDBdBWlroPS3n92us4c6/oisNx7Psf7WeX9/ANuGNAp5Pd1wH+X7wLcevev4VrSL+BOIns/cATwHdwkbuoffgOu9U+v3Q+ZrpLQlZc6/TF0nZ/2eg3wEe8Enuptq0p73TFdJaGrkOP+vFH7NHnbG7znFfn+vnL18D3EpK7LtRT4oqp+D/g6cA3uhaQFOFZE3qJuFcIG3AtNBNxYo+ZpGrrpKriunFcmjaHrBtyWCod7rw/iVrfswPVqwK20SZUH56Xk0XQVXFehxv0NwLUysivA6cBKVe0SkVrcSqXUuPe75cg+8asp1aUi8g4RScWddwNTvUz+HbgtKc7GTT5FcGcAg2uJnxWvDj7XX67pKgtdd+EmKS+SvWXAW3DDE18XkR7csBjq3eKZLtM1QV2p6sF64HkRuRK3Sm+ZpyvQxgEoXIgJN044B3gM94KxAjcONxn4Cq6blnLBDsNNnKbi1jcB/4uX8TddpusAdS3FnTSYihMfjltt8iBu4tJ0ma5c6noUtzrp5lzryvejMAfx4n+4jcR+4/0exq08uBG3guUB3Jmyk7zXbwM+7/1eQVpPF9NlunKg61bgWu/3OcA5pst05VjX57zfP8+ovESxPPLdsiCM2+8kJG5/mHq8njCqGheRz+L2j/keblnjxd4/+VbcGbV/8faN4ZZjmi7TlStdcdz1CVDVFuA+02W6cqzraW/f7+dKU6HJWw5CRN6Bm9mfijul/F9wLxZniEgqNpjETWb+u7rTyB8ELhWRF3AtdM4niZgu02W6TFex6io4+XJNcJtQfSzt+X/iNp66HFjtbXNwW1DcAcz3ts0Glpgu02W6TJfp8veRzyqm1cBtsrfvyJ+BBer2YQmJyDXqWuB5QExVtwOo6i5V3ZzxE02X6TJdpqu8dRWUvBkIVR1Q1SHdW3/8TvbGn68ADheR+3B7/j+fLx2my3SZLtNVKroKTd6X4fQssOK2+L3H29yLWxp2JLBF89CO2HSZLtNlukpVV6EoxES5JG554x7gaM/qfhVIqupTPn65pst0mS7TVay6CkOukxqZHriL0iSBp3AX5PA9+WK6TJfpMl3FrKsQj9QC8XlF3BXMPgZ8T92e/4HAdI0P0zU+TNf4MF3BoyAGwjAMwyg+fO/mahiGYQQTMxCGYRhGRsxAGIZhGBkxA2EYhmFkxAyEYRiGkREzEIaRJSLSICKf9n5vEpE7/NZkGPnEylwNI0tEZBFwn6oe6bMUwygIee/FZBglxLeBg0TkRWAjcLiqHikilwPnASHc/jzfBSpxJ1cNAe9V1Q4ROQj4KdAIDACfUNX1hf8zDCM7LMRkGNlzPfC6qh4L/N2o144E/hpYDnwTGFDV43BXFbvU22cFcI2qngB8CXeNAcMILOZBGEZueExVe4FeEekG7vW2r8Vt8jYZOBm4XURS76kqvEzDyB4zEIaRG9J79CTTnidxzzMH6PK8D8MoCizEZBjZ0wvUTeSNqtoDbBGRCwHE5ZhcijOMXGMGwjCyRFXbgT+LyMvAv0/gIz4CXCUia4B1wLm51GcYucbKXA3DMIyMmAdhGIZhZMQMhGEYhpERMxCGYRhGRsxAGIZhGBkxA2EYhmFkxAyEYRiGkREzEIZhGEZG/j90dDEQ4iFMRwAAAABJRU5ErkJggg==\n", 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5yE+epzuSZP7UTMRByNjrcJ4qEnMdha+KyC+B3+GEjwArSR2KT931Ih39CT55/lzOmJPbRLXBCFn4qCTIeAqVZf62ucj8xqTSmrcfHCN3Wroi7GiPcOvfLeTyJTM9O2+uRqEaxxhcPGCblaQOQl8sSVtvnE9fMJfPX3zcEX1WOBs+GgtlRlCJxJNUl4d9n4uSnRdjNyGBoL0vDsCUIwhBj4acjIKqXp1vIcXCupZuAOZNOfLZqZlFuMxTKG764infK49gQA7Lxlsg6Oh3jML4EZSxjwW5Tl6bA3yK189ofmd+ZBUmj7+6j6vvXAHArImjzyVksERzadAdSdBYnVvrk3yS9UxtuAWCdrer8oQcG2iOFbmGj34L/Agnp2DBDODlnZ389NltpNNKWpVIIsWf1uxl1sQaPn/RsSyc3njE57BEc2nQHU1SHwCjIANyCob/dGY9BW/HRq5GIaqq386rkgLjZ89u47erdjF1XBXiVgScefQEvvPB02iqG5sWyGFLNJcE3ZEEDVX+Vh7BgOojMwqBoCuSICRQV+nt2Mj1bLeJyI3AwxxcffRiXlQVAFva+lg0azz3fPysvJ3DwkelQXc0wfTx1X7LoMxNYiWssiEQxJJpKspCns8ZydUoLMSZvHYBBzfEG1XbbBEZB/wQWOB+zkeB14B7cPIWW4H3qWrHaD7fC7a09XHxiVPyeg7zFEqD7kiShir/w0fl7nhLpmy8BYF4Mk1lmfcFCLkahXcBR6tqfIzOexvwR1V9j4hUADXADcCjqnqriFwPXA98aYzON6Z09SfY3xdnTlNtXs+T8RQsxlt8PP7aPr724FrSCvv7YjRU+x8+yngKZhSCQcZT8Jpcz/gSMG4sTigiDcCbcBLXqGpcVTuBpTg9lnAfLxuL8+WDLfv7AJg9Mb9G4UCMN6+nMXzgdy/tZm93jIXTG7nslOksPXm635Iod6cxW/goGMSSKSrC3huFXG9PpuDMal7BwTmF0ZSkHg20Aj8RkZOBF4DPAFNUtcX93BYRmTyKz/aErW2OUci3p2DzFIqTaCLFXza0sWTOBL79gVP9lpOlLGSeQpBwwkfBNQo3jvE5TwM+parPichtOKGinBCRa4FrAWbO9G7q90D2uzMN873QuoWPipOH1+6ltSfGWxdO9VvKQZRlPIWUeQpBIO5T+CjXGc1PjuE5dwI7VfU59/WvcYzCXhGZ6noJU4F9Q2i5A7gDYPHixb78WnZHnEkl9XlODoat7UBRsrPDWZr1rQubfVZyMJnwUdJuQgJBzCdP4bBnFJEHh/uAXPYZiKruAXaISKYx0IXAWuAB4Cp321XA/SP5XC/pjiaoryzLe9OwzAxTc+eLi5bOKI3V5b53RT2UA+Ej8xSCQFA9hTeKyOFaZgswmmU6PwX8wq082gxcjWOg7hWRa4DtwHtH8bme0BVJ0ODBDFRrUFactHRFmNrobZOzXDgQPrLxFgTiqTRV5cEzCktz+IwRl6mq6t+AxYO8deFIP8sPuiNJT4xCmbW5KEpae+N5z0eNhoynYOMtGMSTaV9muh/2jGOcSyh4nlzfytrd3azf28O0cfm/07P1FIqT9r4Yc8agYeJYU2YlqYEilkwFevJaydPVn+Dan64klnQumAuOz3/FbNjaXBQlHX0JJtQGz1Mot5LUQBHUnILhsnxjG7FkmnuuPZOTjxrnSVWAdUktPmLJFL2xJBM87nyZCxlPwRLNwcAvo5DTGUXkAhEJnr/rIVvdWcwLpjdSVR72pEmVLXpSfHRkeuQH0VPIho9svAUBv9pc5OopfAS4XUT2A39x/5YHuWHdWNETTXDfi7t4dN1eJtVXUuthG9sDnoJnpzTyTHfUMQpB6HV0KFaSGix6Y0lqfViRL9fJa1cCiMg04D3Ad4FpuR5fyFx/3yv8/uUWAN6ywNvJRtbmoviIxFMAgVh+81AOhI9svPlNNJEilkwzzuNV1yD35Tg/DJyD00K7DfgOjrdQlOzrjvLQKy1840+v0R9P8fE3Hc2nL5xHdbm3F7Ktp1B8RBKOUajyoapkOMptPYXAkF2fOahGAfgWsAm4HXhcVbfmTZHP7OuOctatj5FKK8dOqePSE5v5+zcd7WnYKIMlmouPaMYoBNFTsPUUAkNnvxNmHFfjfUFCruGjJhE5Eafl9S0iMg94TVWvyKs6H1i/t5dUWvn8Rcdy+ZKjmFzv38zTbEM8Cx8VDRmj4LXXmQvZnILdhPiOn0Yh1+qjBmAmMAtnZbRGDqzAVlRsa3eqjN6zaIavBgFszdxiJBs+CqJRsJLUwNAVccJH46qDGz5aPuDvO6q6M3+S/GV7ez8V4RDNDf73prHlOIuPaML5wQ2kp2BdUgNDdzQJQH3Q2lxkUNWTAESkHmdN5aJlX3eMyQ2V2RYTfmKJ5uIjU33kR6Oz4bBFdoJDr49GIdfw0QIRWQWsBtaKyAsisiC/0vyhtSfG5IA0K7NEc/ER5PBR5j7IPFP/6Ys5RsGPApdcb1fuAD6vqrNUdSbwBXdb0bGvJxqYDpbZ9RTMKBQNsUQKEXxZPGU4RISQmGcaBHpjSSrLQtkyYS/J9Yy1qvp45oWqPgHkd4FiH1BV9nbHfE8wZ3C9eWtzUSS09sT47hObKA+FPGmTMhrKQiG7CQkAvbEkdT54CZB7onmziHwF+Jn7+sPAlvxI8o/1e3vpiiQ4YWqD31IAa3NRbNz+5CZSaWXR7PF+SxmSUMhuQoJAbyzpS+gIcvcUPgpMAu4DfuM+vzpfovzi53/dRnlYePP8/LfFzgVbo7l4+OmzW/nR8i0smTOBe//hLL/lDElYxHJYAaAv6J6C2/ju03nW4juPv7aPN58wJTDho0xOwS7SwmV3Z4SXd3bx1fvXUFUe4muXBbs+IxQyoxAEeqIBNwoicizwTzgT17LHqOoF+ZHlPZF4il2dEd6zaIbfUrJY9VFhs2FvD5d86ynS6sxLePyfzqM5gGszDyQcEvNMA0BHf5zZE/1J2+Zqin6F0/foh0Aqf3L8Y+O+XlRh7uQ6v6VkERFELHxUiKgqn73nb4RE+Ob7T+aMORMDbxDAwkdBob0vzqJZ/uSecjUKSVX9fl6V+MxfNrYCcPrsCT4rORi7SAuTzW19rNndzd+fM4elp0z3W07OhC185DvptNLRn2BCrfctLiD3RPPvROQ6EZkqIhMyf3lV5iF7u6N865ENnDSjkSkBaG8xkFBIbDJRAfL8lnYA3rf4KJ+VjAwzCv7TFUmQSisTfVqdL1dP4Sr38YsDtilw9NjK8Yd7Vuwgnkxz1Vmz/ZbyOsIiNpmowPjfF3by5fteYdbEmkCFI3MhJHYT4jf7+5xmeBPr/PEUcq0+mpNvIX7S0hWhqa6SdwcoyZzBuXPzW4WRK9FEipseWENTXQVfffv8wE5SG4pwyG5C/GZ/bwwgmOEjETldRJoHvL5SRO4XkW8XU/hod2eUaeOCFTbKELJEc0GxsyNCTyzJv75tPheeMMVvOSMmHBKsH56/tLueQiCNAvADIA4gIm8CbgV+CnRRRL2P9nRFA9EqezAsxltY7OqMADB9fLXPSkaH9T7yn2z4yKecwnBGIayq7e7z9wN3qOr/qupXgLlHcmIRCYvIKhF50H09QUT+LCIb3EfP6rFauiJMDWi5YNgSzQXFXc9tB2D6uMI0Ck7vI4tX+knGUxhf6/2qa5CDURCRTN7hQuCxAe8d6XS7zwDrBry+HnhUVecBj7qv805fLEl3NElzYzAv4pAlmguG1p4Yf1yzh8qyUOCq2HIlZDks39nXE6W+sozKMn/aqw9nFO4CnhSR+4EI8BcAEZmLE0IaFSIyA3gbzmS4DEuBZe7zZcBlo/38kdDSFQUItqdgRqEgWLHVcarv/fhZ2dnohUbYGuL5iqry1Po2TvVp4hoMc7evqreIyKPAVOBh1exoCQGfOoLzfgv4Z6B+wLYpqtrinrdFRDzpSrcn4EbBSgQLh66Is9h6oXoJYJMl/SaVVra39/Pu0/yrhBw2BKSqfx1k2/rRnlBE3g7sU9UXROS8URx/LXAtwMyZM0crI0tLl5MYnBrQ8JF5CoVDxig0VPvTyGwsCFnvI19JuKVflT4u1+rHmd8AvFNEtgJ3AxeIyM+BvSIyFcB93DfYwap6h6ouVtXFkyZNOmIxmfDR5IZgrLZ2KGYUCofuSIKykFAdwKU2c8U8BX+JuwkdP1Zcy+D5mVX1y6o6Q1VnA5cDj6nqh4EHODBz+irgfi/0tHRFmVhbEcg1c8HmKRQS3dEEDdXlBTdhbSDhkNjKaz4STzpGocLH5VqDtFDsrcBFIrIBuMh9nXf2dEWYGtCJa2CeQiHRHUnSUFW4oSOwGc1+k3A9hYqwfzcWvo5gd63nJ9zn+3HKXj2lpSvKjPE1Xp82Z8KhkJUIFgjd0QT1Vf7Ulo8VNi/GXxKlGD4KGi1d0cBWHoGVCBYS/fEUNRXBDEPmis2L8RczCj7TH0/SFUkEevETS/wVDrFEKrC5qVwxT8Ff4knnuzej4BP7e53p5JPqg1l5BFYiWEjEkmkqfUwQjgUhsRnNfpLNKZT5l1Mo7BF8hEQTzsqiQb67M0+hcIgl01QGeCzlQllISFnvI9+w8JHPxDLlXz7+BwxHyKqPCoZoIkVVgXsKVu3mLyU5TyFIZP4Dguzyh8XCR4WC4ykEdyzlghOu9FtF6ZKZ0WxGwSeCMFFkOOzOrXCIJVK+dbYcK8KCjTcfSQQgehHcX0MPyBiFIHsKIVsJq2CIJdNUFYGnYEbBP7I5BUs0+0NBeAq2ElZBkEylSaa1CDwFC1f6ieUUfCaeKgCjYHduBUGsALzOXCgLW+8jP8nkFCx85BPxAMTvhiNkd24FQcYoBLm8ORdEBBtu/mElqT5TEOEj8xQKgsycl0L3FELirP5l+MML2zoAfG2/Xtgj+AiJFUD4yBJ/hUFvLAlAdRH0PrI2F/6QTKX5wystvOPkaTTW+NdYMbi/hh5woPoouBdy2C7SguCr968G4KQZ43xWcmRYQzz/WNvSTV88xUXzp/iqo7Cbvx8hhVCSauGjYJNMpfnPP7zKXze3c3xzPXOaav2WdESELKfgG4+/2grAktkTfNUR3F9DDyiYRLMZhcDy7Ob9/Gj5FgB+/rEzfFZz5NhKf/5w1/Pb+eYj6zlmUq3vXZuD+2voAbFkirKQEAoFd/nEMmtlHGg27usF4PkbLqSpLrjddnPF2lz4w+pdXQD85CNLfFZS4kYhmkgHvoTQSTT7rcIYjFRaufnBtdRXlQW6/fpIEMFuQnxgb3eU45vrmTnR/1UgS9oodEUSNFYHe/lEW3ktuHT0x1GFeZPrEAmutzkSwiJWkuoDe7tjvoeNMpS8UWgIulGw9RQCSyTuzE24/PSZPisZO5zJkn6rKC16Y0m2tvXR3GBGwXe6Iwkaq4NdgBUKWaI5qMSS7oS1Am+CNxBLNHvPk6+10hNLcumCZr+lACVuFLoiCRqqCsBTsIs0kEQTTrLHz9mnY02mzYWFkLyjO5oA4Ljmep+VOJS8UQh+TsHCR0GlEJZzHSkhNzdiQ847+tzZ8LWVwYhalLRR6IkGP6fglAjaFRpEMp5CcRkF59HGnHdkWqTUVphR8J1ESn3tRpgLlmgOLpGspxDsMTQSMnN2zCh4R280SXV5mHBA5ksVz2geBSlVAm4TspOJLMYbPIo5fGTDzTv64snAhI7AB6MgIkeJyOMisk5E1ojIZ9ztE0TkzyKywX0cn28tqbQSDnh9edhivIElYxSKKdFs4SPv6Y2lqKsMzhjy4z45CXxBVU8AzgQ+ISLzgeuBR1V1HvCo+zpvZMo8g9ziAsh6MhZCCh7RTEPFYgofuTchNt68oy9W4p6Cqrao6ovu8x5gHTAdWAosc3dbBlyWTx2ZMs+gewoW4w0usSIMH0nWU/BXRynRW+pGYSAiMhs4FXgOmKKqLeAYDmByPs+dKhRPwb1Kbd3c4JGZ0VwV4PU4Rkom2Wk5LO/oiyWpM6MAIlIH/C/wWVXtHsFx14rIShFZ2draOurzZ+68g5LxH4qMPnPng0c0mSIkUB4O9hgaCTZPwXtKPnwEICLlOAbhF6p6n7t5r4hMdd+fCuwb7FhVvUNVF6vq4kmTJo1aQ3StKpIAABY4SURBVOZHNvDho8xFaldp4Igm0lSXh4umGR5YotkPSj7RLM4V9CNgnar+94C3HgCucp9fBdyfTx1ptx114MNHGU/BLtLAEU2kiiqfAGQNnBkF7+iLJQMzcQ38WY7zDcAVwCsi8jd32w3ArcC9InINsB14bz5FHEg05/MsR0420WyeQuAohPU4RsoBz9RnISVCKq1EEqlAhY88V6Kqy4Ghfoov9EpHNnwUcE+hzDyFwBJNpIqqHBUOlECbp+ANfXGnxYUlmgNAZtAHPnxkdeOBJZpIFVXlEVj4yGuC1gwPStgoFEyiOWTufFCJJlNUVxSXUbA2F97SG80YheCMo5I3CoH3FDIzmu0qDRxOTqG4LiGrPvKW7e39AMwY7//azBmKa0SPgHShzGi28FFgKcbwkY03b9m4rxeAuZPqfFZygOAEsjymUBLNGX2rd3XR0R9HgIUzGqkssh+jQiRShCWpB9qq+CykRNje3s+4mnIaa4KzrkvJGoVCSTRnqhI+e8/fstu+/Jbj+fi5x/glyXCJJdJFV32UuRyszYU39MWSgVsSuGSNQspN3AY9fHTOvEncfe2ZxJNpQiJcfefzdEYSfssqedp6Y7R0RTgqQLHgscDaXHhLXzxFTcCKFUrYKGTCRz4LGYZwSDjz6InZ1xXhEImklSL5ze1PbCKt8NaFU/2WMqZYotlb+uPBaoYHJWwUsuGjgHsKh1IWDlnHVB+JJlI8sm4vdz6zlbefNJXjmuv9ljSmiCWaPaU3lqIxYOvEB/w+OX8USqL5UMrDIRIp8xT84tcv7OSTv1xFMq18cMlMv+WMOTZPwVv6Y0lqLXwUDFIFkmg+lPKwmFHwkbUtTpf3Ff/yZibVV/qsZuyxNhfe0h9PUROgZnhQwp5CukBmNB9KWVhIpuyC9YO7n9/OL5/bzuJZ44vSIIC1ufCavngyUG2zoYSNQiGHj+LmKXhOV3+Cm363hmmNVXzygrl+y8kbVn3kHapKXyxJjSWag0GqQBPN5aGQeQoe0h1N8L7bn2Vvd5RoIs0PrljMwhmNfsvKG1Z95B2rdnSSSClzmmr9lnIQJWsUMg3mCs1TKLOcgqes3tXFq3t6ePMJUzh15jgWTG/wW1JesZX+vOP5Le0AXDx/is9KDqZkjUJ2kZ0CC6CVh0Mk7IL1hFRa+ePqPQDcvPREpo2r9llR/rHwkXfs6YpSX1nGuJoKv6UcRMkahWyiOVRYVqE8LCTNU8g76bTy4R8+x7Ob91NfVUZzQ5XfkjzB2lx4x+7OCFPHBW9claxRKJT1FA6lLGTzFLzgpZ2dPLt5Px974xzes3hGwZUujxZriDc6XtjWwefu+Rud/XEuPGEK33z/KcMes6c7ytTG4HmfhXWbPIYcmKfgs5ARUl4WImGJ5ryzpysKwN+dNoPjm4s7jzCQjO2z9TtGxm2PbmBPd5Tmxiqe3tiW0zG7O6NMbQyep1BgP4ljR7pQS1JDlmj2grbeGABN9cGK9+Ybm6cwOra29XHpic1ceMIUOvrjB4XffrNqJx9btpL97pgCiCfTtPXGzFMIEqkCWWTnUMrDVpLqBa29cURgQsCSgPkmnG1zYWMsV9JppaUrwrRx1UysrSCRUnrctZefXN/K5+55iUfW7WXF1o7sMXu7HU80iJ5CyecUCi1WXBYWErZgc17ojyf5vw+vZ09XlNW7u5hQU0FZoZWnHSEHSlJ9FlJAtPXGSKSU6eOrqXEXXeroi9NQVc7/PLU5u9/uzkj2+cptTjnq9PHB8xRK1igUynKch2IN8XKnrTfG+3/wLN//8CKOnfL6bqZ9sSTLnt1KNJEmnVaWb2zjpZ2dHDOpjurycODqx71AbPLaiNnl/thPH1eF4HyB+/vi9MdTLN/YxufefCzfe2IjLV3Ofm29Mb71yAaOb65nyZwJvukeipI1CplkbcHlFKz3Uc78ZUMrm1r7+K8/vcYdVy5+3fs/eGoz3350A+AkWMtCIb54yXFcd17xtrEYjvG1TrhsjxveMIZnd6fzXU0bV02F61m+tqcn2+L+fafP4P6XdrGlrZ/2vjiXfPMp9vfF+cEViygPoCdaskbh6Y1tNFaXM7mhsBqblZmn8DqWPbOV57e2c+bRE7nizFnZ7ZlQyFMbWkmk0tkLcFdnhJ89u42HXmnhnHlN/OyaM3zRHUSmNVbR3FDFc1vaufKs2X7LCTyqyifvehFwjEJ9ZRlNdZXc8vt1XLqgmcqyEFPqq1gyewK/f7mFB1/ezf6+OLd/eBGXnNjss/rBCZ6Z8ohXdnVx9jETqSwLVofC4ZhcX0l7X5wtbX1+SwkM33pkPX9es5ev/HY1q7YfSOa198UBiCbSPPjy7uz2b/zxVW5/chPb2/t549wmz/UGGRHh/OMn8+i6vbT2xIY/oMTZuK83u/ZEQ1U5IsK7T5tObyzJr1/YyYzx1YRCwiULmumJJfnq/WtorC7nkhODG5oMnFEQkUtF5DUR2Sgi1+frPK3dMaYU4CzVy0+fSW1FGdfcuYJ9Pebix5IpOvoTXP3G2TTVVfLFX7+cLf3rcI3C8c313Py7tWzY20N7X5yHXmkBoL6qjMtOne6b9qByzRvnkFb4wq9eorM/fth9VZVYMuWRsuDw8Z+t5JgbHuJffrMagDuvPj373ucvPpYrz5rFgukNvP/0owA4d94kzj7GWVb3jfOasqW/QUSCVHomImFgPXARsBNYAXxAVdcOtv/ixYt15cqVIz5PJJ7ihK/+kS9echyfOL/w4scrt7ZzxY+ep7oizBVnzuLSBc3MaaollVZqA9aGN9/saO/nnG88ztffvZCjJtRw9U9WUF9VxsUnNvPL57YD8NgXzuXd33+GvliK8rDQF0/xtcsW8LaFU7MxdONgfvncdm74zSsAnDpzHJedMp03zJ3I0U112Yq9fd1RrvvFi6zZ3c2HzpjJW0+ayvypDVSVF5b3PVJ6ogkW3vRw9vX8qQ089Jlzhj1OVWntjdFUW+l71aOIvKCqr0+0EbycwhJgo6puBhCRu4GlwKBGYbRk7rAnF+hCKYtnT+C+687mPx5ax7cf28BtbrIUnLvfqY1VTKqvpK6yjNrKMuoqywiJsLszQiKVprayjPqqMmoqyigLC2ERykJCKHTwY6aS4lBGcpMz1B3RUB8x0huol3d2ATC5oYqzj2nivuvO5msPrssahKvfMJujJ9Xx8OfO5Zbfr+WlnV2869TpfHDJTN8vzCDzwTNmMruphqfWt/HEa/u48YE1gFPoUB4O0dxYxeZWJ4RZWxHmzme28sPlWygLCdPGVTO5vpKmukpqKsNUl4epKg9TVR4iHAoREiffExJnfGSeh0QQGXrMHI6RHJFKK/t6otlxHhYhHAoRDh3ohaYoqs4PuarT9kNR9nRFWbHVKSf98UcW0xVJMHNCTW4aRZhcH/zoRNA8hfcAl6rqx9zXVwBnqOonB+xzLXAtwMyZMxdt27ZtxOdZsbWd997+LMs+uoRzj500NuJ9oqUrwl8372drWz+V5SH2dcdo6YqwrydGXyxJXyxFbyxJOq1MqKugsbqc3miSnliS/liSZFpJpTVbKVGINFaX84fPnHNQF9NYMkUqrYFb6rBQ2dTay4vbOrJVNa09MRTlvOMm877FR9HZH+eZTftZs7uLHe0RWntitPXGiCRSRBMpIvEU0WQ6Oz/IbyrLnB//kY79kMCC6Y001VVy2+WnUF9Vni+JeeVwnkLQjMJ7gUsOMQpLVPVTg+0/2vCRqtIdSVJZHip6V3ckpNNKSg9vJIYaL4NtHXJoDbFdh3pjGGorywJZ2mcMjqqSVmcuRDp7J+5sG5XRGMUhDdVlB3kkaXfMZ87veCyu98KReTFBpJDCRzuBowa8ngHsHmLfUSMiNNYUpoXPJ6GQEEIwO2nkExEhLBAeUdAnv4RCQoWFE4HgVR+tAOaJyBwRqQAuBx7wWZNhGEbJEChPQVWTIvJJ4E9AGPixqq7xWZZhGEbJECijAKCqDwEP+a3DMAyjFAla+MgwDMPwETMKhmEYRhYzCoZhGEYWMwqGYRhGlkBNXhspItIKjHxK8wGagNxW2faOIGqC4OqC4GoLoq4gaoLg6oLgajsSXbNUddB2DgVtFI4UEVk51Kw+vwiiJgiuLgiutiDqCqImCK4uCK62fOmy8JFhGIaRxYyCYRiGkaXUjcIdfgsYhCBqguDqguBqC6KuIGqC4OqC4GrLi66SzikYhmEYB1PqnoJhGIYxADMKhmEYRhYzCoZhGEaWojYKEtBlkkTkBL81DIaIfEFELnafB+a7E5HGAc+DpCswWgZi42tk2Pg6mKI0CiKyVESWASf7reVQROT/AQ+JyGyfpWQRkYtF5E/Al4ArATQAFQgicoGI/A34vojcAIHRZeNrBNj4Ghl+j6/AracwWkREVFVF5Hzg34EEcJaIbFPVDr91Ddg0AegA3iwiP1PVmF+6gHLgq8C5wH8CFcDpIlIOJP28QESkDrgB5//yeWCZiNSo6r/6pMfG1wh1YeNrJHoCM76KwlM45MLYAlwCfBE4AzgpCLpEJLPy8V+B7wMfAub5qUtV48D9qnqOu7hRB3C5qiZ8vmBDQB2wA1ilqjuAjwHvF5HjfdBj42sUumx85awnUOOr4I2Cu3znfSLyORFpVtWtqtqiqo8Be4FzRWS6j7o+KyLTVDXlrjt9KfAb4HHgchH5OxEZtDFVnnV9TkSmquoKd3u5qj4JbBaRt3ilZ4Cu60Tk3QCqmgYUmIRz8aKqm3G+t5vd/T2Jt9r4GrUuG1+56Qrc+CpooyAi7wKuAr6NY1H/VUROGbDLL4BjcSzuwOPy+h9+iK6TgRtEZJF757RSVduADcCngVsArwbgod/Xv4hIJm6ZFJEJOF1nU17ocTXVi8jtOGGGZSJSBqCqe4G1wGcH7H49cIaInOjFnaaNryPSZeNreG2BHF8FbRRwvqzvq+rjwE04rtenM2+q6svACmCBOEmlL7nb8/0fPpiuf3Tfe5uI/AUn6fZbHHe/O896DqfrM+B8J6raDlQD50PWzc4rqtoDPKmqzcCDwHcHvH0zcIqIvFVEKt07vAdxYtVeYOPryHXZ+BqaQI6vgjAKh1rGAa83Ax8EUNVtwO+BWhF554Dd78KJF96D0398zCztCHWNE5GzgNuAZ1T1FFW9EmgGxrSE8Ai/r58DS0Skyr1IvND1gPv4WeADIjLP1dgLfAO4HOdu+GbgHKBlLHUdRqev42uEujwbXyPU5dn4OowuX8dXUH+/hqIgjAKHWO4BlvLXQL+ILHVftwBPAPPFoQ7nInkFOElVv3jI8V7qegx4E/ALVf3SgMPepaqrxkjPaHQ9gft9uduqgbvJj4s/qC5V7RORkKruAb4H/HDAPncD/4ETApkEvMV1/ccUOZCoDdL4GokuL8fXqL4vd1s+x9egugIwvg76nQ3S+BoUVQ3sH3AW8Cv3i5kPhN3tZe6jAFcDf+RAc78vAjdl9gMmB0jXje7zMBAKmq6MNg91Zb+Hgd8HsN09phk4I6M9T7puHmR75rvxc3yNRpcX42vUuvI8vgbV5fP4WoLjGX0DWDhAS3iAPs/H13B/gfUURGQy8B3gIWA/TmzyowCqmnR3qwb+hGNh7xCRacCpODW+qGpSVfcFSFfS3S+lYx+aOWJdGW0e6kqpatq9I2occNjXgaeBp4Aqd98xvTsSkauAZTjJvfe52zJJyMy5/BhfR6Irn+PriHVltHmpy4/xJSIhEbkRxyP5A86P+ydwJ6MN+A48H1854bUVGoGVvQi4y31ei1O7+yBwvLvta+4XeirOhJ2v4bhe3yMPdyOmK2+6/h3nTukc9/VbgFeB/wLK86xrBnAxsH3A9sxd3E0+fl+ma+x03ejT+PoYcJr7fCKOcVg84H1fvq+ctPt58kO+xA8A/wa8033dhFNWN9d9PcH9D/46UAP8EjjmkM+oMV2FrQsnvHRUHnUtdV+HOBBWWw78+4B9J/vwfZkuD3TleXzdPGDcV7vaKt3X9wLv8Pr7GtW/xXcBTlztH4BVOPG113CsbBXwFeDbA/7z3wj8DzBhwPFjHjs1Xb7oysvd0RC6rgbqB+xzItAFTBnkeC+/L9OVP11eja/17mPdgH3KgWeAY736vo7kz/ecgjrfzFnArar6E5zY23nAhThx6LkicpE6MdL9wBQgBk7sTvNU1ma6PNeVl2qUIXS9GTgnUxGjqmtwEuG3unreMuB4L78v05U/XV6Nr+tcXW8aUHF1ArBXVdeLM5luiatP8vV9HQm+GAURuVJEzhVnhiPAOmC6iJSp6iPAauBMoBXHzfqmiMzF+YHJNNoa8wFoukpG18s43sqMzDGq+jHgKhHpAE6WPEysMl0lp2uW+/5EnNLTj+B4DAtdgzBmye2xxLMuqa7VbMb5cUgDm3AmavwjTmOqhcBcnCTQ3cA3gYmq+nMROQpnCvrxwN+raqfpMl1HoOuejC5gh4gcjZN4/AvwCVVdbbpM1xjoGg9sxUlufwDHM/6QOjOVg4sXMSoOVAIcC/zcfV6Gk2lfhnPH+GPgCqDRff9O4JYBn1FhukzXGOu62X3eCCwxXaZrjHV9zX3+BuD9Y60rX3959RTceuGbgbCIPAQ04M5kVNWkOB0CW3AqAn4JXIbjCv4njjV+JvNZ6jT7Ml2mayx1Pefu24XTU990ma6x1PWsu+/TY6XJC/KWUxCRc4EXcFyojRxYOOL8TKJFnVjyzcDX1YnF3QG8UUSec497wnSZLtNlukyXh+TLBcFpLHXFgNffw+nk+BHgBXdbCCdO9ytgtrttHDDddJku02W6TJf3f/msPnoBuFcONKh6GpipqnfiuGOfUsfSzsBZmm8rgKp2quou02W6TJfpMl3ekzejoKr9qhrTA/XBF+GUJoIzueMEEXkQpzXsi/nSYbpMl+kyXcWiywvyXpLqWlrFmayU6Wveg7No9gJgix+W1XSZLtNlugpVVz7xYvJaGqdkqw04ybWuXwHSqrrcxy/UdJku02W6ClVX/hjrJMVgfzizWtM4Dauu8eKcpst0+f1nukxXIf5lFnbIKyIyA2dix3+raizvJ8wR0zUyTNfIMF0jw3QFA0+MgmEYhlEY+N4l1TAMwwgOZhQMwzCMLGYUDMMwjCxmFAzDMIwsZhQMYwSIyDgRuc59Pk1Efu23JsMYS6z6yDBGgIjMBh5U1QU+SzGMvODZymuGUSTcChwjIn8DNgAnqOoCcZZavAwI47Q/+L9ABU59ewx4q6q2i8gxwHeBSUA/zgp0r3r/zzCMwbHwkWGMjOuBTap6CvDFQ95bAHwQWALcAvSr6qk4i61c6e5zB/ApVV0E/BNOS2bDCAzmKRjG2PG4qvYAPSLSBfzO3f4KTt+cOuBs4Fcikjmm0nuZhjE0ZhQMY+wY2AIhPeB1GudaCwGdrpdhGIHEwkeGMTJ6gPrRHKiq3cAWEXkvgDicPJbiDONIMaNgGCNAVfcDT4vIauD/jOIjPgRcIyIvAWuApWOpzzCOFCtJNQzDMLKYp2AYhmFkMaNgGIZhZDGjYBiGYWQxo2AYhmFkMaNgGIZhZDGjYBiGYWQxo2AYhmFkMaNgGIZhZPn/Q38p6Sp08hYAAAAASUVORK5CYII=\n", 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" ] @@ -107,6 +97,9 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "storage['Snow'].plot()" ] }, @@ -114,7 +107,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In this case, let's plot The first layer of soil water:" + "In this case, let's plot the first layer of soil water:" ] }, { @@ -125,7 +118,7 @@ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 4, @@ -134,7 +127,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -194,7 +187,7 @@ "Attributes:\n", " Conventions: CF-1.6\n", " featureType: timeSeries\n", - " history: Created on 2019-06-25 09:46:32 by Raven\n", + " history: Created on 2019-10-29 09:42:54 by Raven\n", " description: Standard Output\n", " title: Simulated river discharge\n", " references: Craig J.R. and the Raven Development Team Raven use...\n", @@ -226,7 +219,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "http://localhost:9099/outputs/a3f8963c-974f-11e9-8b16-b8ca3a8f5177/raven-gr4j-cemaneige-sim-0_WatershedStorage.nc\n" + "http://localhost:9099/outputs/01fe699a-fa52-11e9-b285-b052162515fb/raven-gr4j-cemaneige-sim-0_WatershedStorage.nc\n" ] } ], @@ -234,13 +227,6 @@ "[hydrograph, storage, solution, diagnostics] = resp.get(asobj=False)\n", "print(storage)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -259,7 +245,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/multi_model_simulation.ipynb b/docs/source/notebooks/multi_model_simulation.ipynb index 782a8521..723ec673 100644 --- a/docs/source/notebooks/multi_model_simulation.ipynb +++ b/docs/source/notebooks/multi_model_simulation.ipynb @@ -11,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -23,14 +23,16 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 2, "metadata": { "scrolled": true }, @@ -55,37 +57,81 @@ " )\n", "\n", "# Launch the WPS to get the multi-model results. Note the \"gr4jcn\" and \"hmets\" keys.\n", - "resp=wps.raven_multi_model(ts=str(ts),gr4jcn=gr4jcn,hmets=hmets, **config) \n", - "\n", - "# And get the response\n", - "# With `asobj` set to False, only the reference to the output is returned in the response. \n", - "# Setting `asobj` to True will retrieve the actual files and copy the locally. \n", - "[hydrograph, storage, solution, diagnostics] = resp.get(asobj=False)" + "resp=wps.raven_multi_model(ts=str(ts),gr4jcn=gr4jcn,hmets=hmets, **config) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Let's see the diagnostics\n" + "Let's see the diagnostics and the output hydrograph. " ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "http://localhost:9099/outputs/c45bfe1a-974e-11e9-9eea-b8ca3a8f5177/Hydrographs.zip\n" + "['observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_q_oinb41/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.0371048,36.562,\\n', 'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_q_oinb41/Salmon-River-Near-Prince-George_meteo_daily.nc,-7.03141,101.745,\\n']\n", + "[\n", + "Dimensions: (nbasins: 1, time: 732)\n", + "Coordinates:\n", + " * time (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2002-01-01\n", + " basin_name (nbasins) object ...\n", + "Dimensions without coordinates: nbasins\n", + "Data variables:\n", + " precip (time) float64 ...\n", + " q_sim (time, nbasins) float64 ...\n", + " q_obs (time, nbasins) float64 ...\n", + " q_in (time, nbasins) float64 ...\n", + "Attributes:\n", + " Conventions: CF-1.6\n", + " featureType: timeSeries\n", + " history: Created on 2019-10-29 16:40:01 by Raven\n", + " description: Standard Output\n", + " title: Simulated river discharge\n", + " references: Craig J.R. and the Raven Development Team Raven use...\n", + " comment: Raven Hydrological Framework version 2.9 rev#177\n", + " model_id: gr4jcn\n", + " time_frequency: day\n", + " time_coverage_start: 2000-01-01 00:00:00\n", + " time_coverage_end: 2002-01-01 00:00:00, \n", + "Dimensions: (nbasins: 1, time: 732)\n", + "Coordinates:\n", + " * time (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2002-01-01\n", + " basin_name (nbasins) object ...\n", + "Dimensions without coordinates: nbasins\n", + "Data variables:\n", + " precip (time) float64 ...\n", + " q_sim (time, nbasins) float64 ...\n", + " q_obs (time, nbasins) float64 ...\n", + " q_in (time, nbasins) float64 ...\n", + "Attributes:\n", + " Conventions: CF-1.6\n", + " featureType: timeSeries\n", + " history: Created on 2019-10-29 16:40:01 by Raven\n", + " description: Standard Output\n", + " title: Simulated river discharge\n", + " references: Craig J.R. and the Raven Development Team Raven use...\n", + " comment: Raven Hydrological Framework version 2.9 rev#177\n", + " model_id: hmets\n", + " time_frequency: day\n", + " time_coverage_start: 2000-01-01 00:00:00\n", + " time_coverage_end: 2002-01-01 00:00:00]\n" ] } ], "source": [ - "print(hydrograph)\n", - "\n" + "# And get the response\n", + "# With `asobj` set to False, only the reference to the output is returned in the response. \n", + "# Setting `asobj` to True will retrieve the actual files and copy the locally. \n", + "[hydrograph, storage, solution, diagnostics] = resp.get(asobj=True)\n", + "print(diagnostics)\n", + "print(hydrograph)" ] }, { @@ -97,7 +143,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -120,33 +166,33 @@ " long_name: Simulated outflows" ] }, - "execution_count": 22, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "hydrograph[0].q_sim\n" + "hydrograph[0].q_sim" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 23, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -158,13 +204,16 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph[0].q_sim.plot()\n", "hydrograph[1].q_sim.plot()" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -172,37 +221,34 @@ "output_type": "stream", "text": [ "Max: \n", - "array(89.922826)\n", + "array(89.92282574)\n", "Mean: \n", - "array(24.683159)\n", - "Monthly means: \n", - "array([14.517574, 11.473847, 10.072479, 20.420102, 24.375415, 22.558126,\n", - " 23.561023, 25.30086 , 28.723886, 34.377812, 46.446956, 34.094862])\n", + "array(24.68315926)\n", + "Monthly means: \n", + "array([[14.51757372],\n", + " [11.47384691],\n", + " [10.07247858],\n", + " [20.42010158],\n", + " [24.37541465],\n", + " [22.55812604],\n", + " [23.56102348],\n", + " [25.30086037],\n", + " [28.72388552],\n", + " [34.37781245],\n", + " [46.44695633],\n", + " [34.09486191]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph[0].q_sim.max())\n", "print(\"Mean: \", hydrograph[0].q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph[0].q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph[0].q_sim.groupby('time.month').mean(dim='time'))" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -221,7 +267,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_OSTRICH_gr4jcn.ipynb b/docs/source/notebooks/running_OSTRICH_gr4jcn.ipynb index d45e302d..8300fb61 100644 --- a/docs/source/notebooks/running_OSTRICH_gr4jcn.ipynb +++ b/docs/source/notebooks/running_OSTRICH_gr4jcn.ipynb @@ -23,8 +23,10 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, @@ -53,6 +55,8 @@ " upperbounds=upperBounds,\n", " start_date=dt.datetime(1954, 1, 1),\n", " duration=208,\n", + " # Comment out the random seed to show different results!\n", + " random_seed=6.67408*10**-11\n", " )\n", "\n", "# Let's call Ostrich with the timeseries, calibration parameters and other configuration parameters\n", @@ -80,7 +84,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "1.710416, 5.650431, 248.3489, 1.98572, 2.375021, 0.0123782\n" + "2.423961, 3.758972, 204.3856, 5.866946, 16.60408, 0.3728098\n" ] } ], @@ -104,13 +108,13 @@ "data": { "text/plain": [ "\n", - "array([[ 0. ],\n", - " [ 0.124173],\n", - " [ 0.785578],\n", + "array([[0.000000e+00],\n", + " [2.348830e-02],\n", + " [9.777260e-02],\n", " ...,\n", - " [67.144195],\n", - " [67.785368],\n", - " [78.469867]])\n", + " [6.661881e+01],\n", + " [6.718275e+01],\n", + " [6.856092e+01]])\n", "Coordinates:\n", " * time (time) datetime64[ns] 1954-01-01 1954-01-02 ... 1954-07-28\n", " basin_name (nbasins) object ...\n", @@ -134,22 +138,10 @@ "execution_count": 5, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 5, @@ -158,7 +150,7 @@ }, { "data": { - "image/png": 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\n", 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kkF9UypkDOx4ad1TnlpzaP4P/fb2Ri0dlVtveE+5sj8KYZmZfNR0CNtavjutOl9Yt+MO0pTU23C7YkkdeYSnjjzz8sFNtEmKj+fPEAcy8+SRuObUfwzJb8d+vNzL58VmHGub9NW3RdvKLSrln4gAePHcQt5/ejxlrcjj+b18w/oGZ/PPj1Yd1X+IvVeXxmevplPbja04AfndyHw4cLOOJr/xrywk3ViiMaWYOBKFQJMRGc/dZA1ifc4DHZ1T/Yfji95tJjIvmhN7pDVpHp7QWXDWmJ49eMJRHLxjCku359br2QlV59rtN9MtIYUT31ogIU0b35JPrR3PZ8T3omNaC/3y5jvEPzCQrv7je+eZszGX+5r1MGd2D2Cp7TH3ap3DWwI48891Gdu2r/7JDzQqFMc1MZRtFoJ3Utx0/HdiRf3+xlu83/PgivI27D/Du4h1cdEw3UhJia1iC/04/qgO/Ht2Tl+ds9buh+/uNuazK2selx2X+qH0mMz2JW0/rx3O/GsFbVx/LvuIyrntlIeUV/rddFB0s528frSI9OY5zhx9+zQnA9eP7UFquPPSZ97orsUJhTDMT6DYKX/dOGkC31on89uWFbHKvh1BVHv58LbHRUVx2QveAreuGCb3pl5HCzW8sJffAwTrnf+bbTaQlxnLWoE41zjOkayvumTiA7zfm8p8v6r7nxoac/UxfvINLnp7Dwq153HHGkYcasavKTE/iomO68fKcLX6dIRZOrFAY08wEo42iUkpCLI9fNJSy8gp+9th3vDJnC398ZzlvLdzOpcd1p11K4xuMK8XHRPPA5EHkFx3kD9OW1nr20va8Ij5ZkcW5w7vU+EFe6WdDOvOzwZ146PM1h+0ZVVqTvY/THvqasffP5NqXF7JwSx4PTB5YaxECuG5cb1ISYrn73RWe6tqj1kIhIv1E5EMReV9EeorIMyKSJyJzROSIpgppjAmcYO5RgHM8/q2rjyOtRSy3vrWU52dv5ooTunPzKX0Dvq4jO6byuwl9+WBpFs98t6nG+Z5zp110TDe/lnv3xAF0a5PENS8vZN2ufT+atnRbPuc+MYs9+0u468wj+fj60Sz84wQmDe5cw9J+0Copjt+f0pfv1u/h9Xnb/MoSDup6t0wF/gEkA18AtwCXAmcA/8Hp5dUY4xHlFUpRaXlQ2ih8dU9P4uMbRrMlt5CDZRUc0SE1aOv69egeLNiyl3veX0nf9ikc2+vHjeWbdh/g6e82cebAjnRuVfNV5r6S42N44qKhXPC/7/n547O4/fQjGJHZmplrcvjLBytJT47nxctHkpmeVO+8F4zoynuLd/Dn91dwfO90Oqa1qPcymlpdh55SVPVdVX0ZKFXVV9TxLtCqCfIZYwKorg4BAyk2OoqebZODWiTA6cn2gckD6ZGexJTn57N02w/9Tqkqf5y+nLjoKG4/vX4HQfq0T+HNK48lIzWBm99Ywph/zuDO6csZ0b017/z2uAYVicq8f//50ZRXKFe9MJ/i0vDvB6quQuF7MO+BKtO8d9WIMc1cUxaKppSSEMvzl42kZYtYLvjfbN5dvIOC4lJufmMJX63J4fcn92nQBXVd2yTy4XUn8OqUY7jvZ0fxxpWjePbSEaQnxzcqb7c2Sfzr3EEs3pbPTW8sqdcZVqFQ17vlERFJVtX9qvpo5UgR6QV8FtxoxphAq7yYLBCnqIabjJYJvDLlGK55eSHXvLzw0PjrxvXm4mMzG7xcEWFkjzaM7FH9FecNdUr/DG49rR/3fbgKAR6YPLDWK9ZDqdZCoapPiEg8gIjEq2qJO34dcH0T5DPGBNDeA06haJUYeYUCoEvrRF6/chTTFm5nb+FB+rRPYUzfdqGOVaMrT+yJKvzto1WUllfw0C8GE1dHZ42h4M/+5+MichXwCHBZkPMYY4Iov8i53qBlhBYKcNpGzqnmRkvh6qoxPYmNFu55fyXFz8/jkQuGkBgXXocG6zo99kRgHvA1MF9ERjdJKmNMUOQVOnsUaYnWxBhOLj+hB/dOGsDMNTmc99/v2RNm9+Hwdx8nMP0RG2NCKq/ILRQtInePwqsuGNmNxy4cyqqdBZz92Hds3hM+d/qrtVCo6kxgOHACMExVv2qSVMaYoMgrLCU2WkiMq1/33KZpnNI/g5euGEleUSkTH/mW79bv9vu1n63I5tnvNlFaXhHwXP7sUVypqkXA1QFfuzGmSeUXHSQtMS5gNy0ygTe0W2umXX0cbZLjuejJOTw3a1Od3X1UVCh//3gVL8zeTHQQ/rb+FIrHRCQBpzHbGONheYWldtjJAzLTk3j76mMZ06ctf3xnOTe/sYTCgzXfe+PTldmsyd7Pb07qRVRUExcKt/HaGrONiRB7Cw+SFsFnPEWSlIRYpv5yGNeO7cUbC7ZxxsPfsHxH/mHzlZVX8MiX6+jWJpEzju4QlCx17VFIlUdjjIflFZbSsoWd8eQV0VHC707uy4uXjWR/cRmTHvmO+z9ZzW73rKhdBcVc/tw8lmzL57pxvYN2wV5dF9zNFJFLcRqzH/G9OtsY4z35RaUM6GR7FF5zbK90PrzuBP74znIe/mIdD3+xjtSEGAqKy4iOEv4y6Sh+NqTu3msbyp+rOq5U1WIRscZsYzzO2ii8q01yPI9cMIQbdu3jkxXZ7MgromvrRMb0bUef9ilBXXedhcItEt2Ba0Qk0/c1qvrT4EUzxgRScWk5RaXl1kbhcb3apdCrXXALQ1X+Xic+DXgSeBcI/Em6xpigKyiyq7JNw/hbKIpV9d9BTWKMCapDV2XbHoWpJ38LxUMicifwCXCoExJVXRCUVMaYgDvUz5Od9WTqyd9CcRRwETCWHw49qTtsjPGAvYVOz7G2R2Hqy99CMQnooaoHgxnGGBM8+e4eRUs768nUk79XZywG0oIZxBgTXHlFtkdhGsbfPYr2wCoRmcuP2yjs9FhjPCKvsJSYKIm4+2Wb4PP3HXNnUFMYY4Jub2EpLVvEWs+xpt78KhTufSmMMR6Ws6+YtinxoY5hPKiu3mPfq2sB/szjLxFJE5E3RGSViKwUkVEi0lpEPhWRte5jq0Ctz5jmJKugmIyWCaGOYTyorj2K40Vkei3TBTgygHkeAj5S1Z+LSByQCNwOfK6q94nIrcCtwC0BXKcxzUJWfgkDOrYMdQzjQXUVirP8WEZATpkVkVRgNHAJgHsq7kEROQsY4872LDADKxTG1EtpeQV7DpTQPtX2KEz91dnNeFMFAXoAOcDTIjIQmA9cB7RX1Z1unp0i0q66F4vIFGAKQNeuXZsmsTEesWtfCarYoSfTIMG5y0XDxABDgMdUdTBwAOcwk19UdaqqDlPVYW3btg1WRmM8KSu/GIAM26MwDRBOhWIbsE1Vv3eH38ApHNki0gHAfdwVonzGeFZ2gVMo7NCTaYh6FwoRaSUiRwc6iKpmAVtFpK87ahywApgOXOyOuxh4J9DrNibSHdqjsENPpgH8uo5CRGYAP3XnXwTkiMhMVf1dgPNcA7zonvG0AbgUp5i9JiKXAVuAcwK8TmMiXnZBMXExUbSy7jtMA/h7ZXZLVS0QkcuBp1X1ThFZEugwqroIGFbNpHGBXpcxzUlWQTEZqQl2VbZpEH8PPcW47QOTgYBdYGeMaRo784utIds0mL+F4m7gY2Cdqs4VkR7A2uDFMsYEUnZBMe2tfcI0kL+F4l1VPVpVrwZQ1Q2qenYQcxljAkRVycovJiPV+nkyDeNvG8UyEckGvga+Ar5V1fzgxTLGBMrewlJKyirIaNki1FGMR/m1R6GqvYDzgKXAGcBiEVkUzGDGmMBYk70PgF7tkkOcxHiVv6fHdgaOA04ABgLLgW+CmMsYEyCrs5xC0S8jJcRJjFf5e+hpCzAX+IuqXhnEPMaYAFudvY+WLWJpZ/eiMA3kb2P2YOA54HwRmSUiz7kXwBljwtzqrH30zUixayhMg/nbRrEYp4vvp4EvgBOBO4KYyxgTAKrKmqx9dtjJNIpfhUJE5gGzgEnAKmC0qmYGMZcxzcreAweZv3lvwJe7Pa+IfSVl9GlvhcI0nL9tFKepak5QkxjTTGUXFHPef2ezIecA0397HEd3TgvYsivPeLI9CtMY/rZRHBSRB0Rknvtzv4jYPRWNCYBLn55Ldn4xaYmx/OWDlahqwJa9cqdTKPpYoTCN4G+heArYh9PX02SgAKe9whjTCPlFpazYWcDVJ/XihvF9mL0hlxmrA7fz/uGynRzZIZXUBOs11jScv4Wip6re6XbdsUFV/4Rz61JjTCNs2VMIQM+2SZw/sivd05P464crKSuvaPSyl23PZ9n2An4xokujl2WaN38LRZGIHF85ICLHAUXBiWRM87FpzwEAurVJIjY6iptP6cua7P28uWBbo5f9ytwtxMdEcdbATo1elmne/G3Mvgp41m2XECAXuKTqTCLyMz+WVayqH/id0JgItvlQoUgE4NQBGQzumsYDn67hzIEdSYzz918UysoryC8qJa+olC9X7eKN+ds4/agOtLSbFZlG8utd6N5QaKCIpLrDBTXM+l+cW5XWdmXPaMAKhTHApj2FtE+NP1QQRITbTz+Ccx6fxVPfbOS3Y3tX+7qtuYW8Pn8bX6/NYc/+g+QVHqSguOxH85zYpy23nNov6L+DiXy1FgoRqfZWp5VXeKrqA1Umfaiqv6pjmS/UJ6AxkWzT7gN0a5P0o3HDM1tz8pHteXzmBn4xoivpyT/ueuOdRdu57a2lFJWWM7RrKwZ3TaNVYhwtW8TSKjGWVklxdGmdyJCurZryVzERrK49inqdU6eqFwZiHmOai017Chnbr+1h4285rR+nPvgVV7+wgOcuG0FCbDTFpeXc/d4KXvp+C8MzW/GvcwfRuVViCFKb5qauQpGoqreIyDmq+npjViQiE1T108Ysw5hIsr+kjN37Sw7bowDo2TaZByYP4tpXFjL5iVkc2zOd95bsYNveIq48sSe/P7kPMdH+notiTOPU9U47XURigdsCsK4nA7AMYyJGZUN2ZjWFAuDMgR15YPJADpSU8fjM9XRomcDzl43g1tP6WZEwTaquPYqPgN1Akoj4NmALoKqa6juziEyvYTkCtGlwSmMi0Gb3GorM9JoPH00a3JlJgztzoKSMpHj/z4AyJpBqfeep6k3ATSLyjqqe5cfyTgAuBPZXGS/AiIZFNCYybc11CoU/7QxWJEwo+fvuW1V1hIj8TVVvqTJ6NlCoqjOrmX91A/IZE7GyCopJjIsmNcGKgAlv/h7onFDNuNOqjlDV01T1y+oWoKqj6xPMmEiXXVBMRmqC3VDIhL1aC4WIXCUiS4F+IrLE52cjsMSfFYjIGYEIakykyS4ooX1qQqhjGFOnuvZ5XwI+BP4K3Oozfp+q5vq5jruB9xqQzZiIlpVfzIjurUMdw5g61dWYnQ/ki0jVtohkEUlW1S1+rMP2q42poqJC2bWv2PYojCf424r2PqA4H/oJQHdgNdDfj9f+umHRjIlcuYUHKS1XMlLj657ZmBDzqzFbVY9S1aPdx944p7p+U928InKP+3i3+9o5gQprTKTIyi8GIKOl7VGY8NegyztVdQEwvIbJc0XkEWBeg1MZE+GyC5xCYYeejBf4deipSi+yUcAQ4LD7NYrInUBr4DygTEQGqerdgQhqTCTJKrA9CuMd/u5RpPj8xOO0WRx2pbZ7i1SAUe6wFQljqpGdX4wIh3Uhbkw48vfGRX8CEJEUZ1CrdtHh6ylVXS0iTwUioDGRKLughPTkeGKtcz/jAX69S0VkgIgsBJYBy0VkvogMqGH2c9zHswMR0JhIlOVelW2MF/j7dWYq8DtV7aaq3YAb3XHVaXBjtohEi8hCEXnPHW4tIp+KyFr30W7ZZSJCdoFdQ2G8w99CkeTbh5OqzgAO60Tfbcwei9OYPU5E/ljPPNcBK32GbwU+d0/J/ZwfXx1ujCepKtv3FtEpzQqF8QZ/C8UGEblDRDLdnz8AG6vO1JjGbBHpDPwE+J/P6LOAZ93nzwIT/V2eMeEq98BB9pWUVXtnO2PCkb+F4ldAW+At9ycduLSGeZ8GjgbeBBCRP4jIWyIypI51PAjcDFT4jGuvqjsB3Md2Nb1YRKaIyDwRmZeTc9iZu8aEjc3ufSi6tbH7XRtv8MO/+L8AABwFSURBVPesp73AtX7Ou0hEnlPVo0XkeOAU4J/AY8DI6l7j9jC7S1Xni8gYv5Ifvt6puO0mw4YN04Ysw5imUHkLVCsUxiuCdW5eufv4E+AxVX0HiKtl/uOAn4rIJuAVYKyIvABki0gHAPdxV5DyGtNkNu8pRMS/O9sZEw6CVSi2i8gTwGTgAxGJr21dqnqbqnZW1UzgF8AXqnohMB242J3tYuCdIOU1psls2VNIh9QEEmKjQx3FGL8Eq1BMBj4GTlXVPJxuPW5qwHLuAyaIyFqcu+zdF7iIxoTGpj0H6GqHnYyH1NpGISIP43QvXi1VrbbdQlULcRq9K4d3Ajv9CeSeejvDfb4HGOfP64zxii25hYw/on2oYxjjt7r2KOYB83HuQTEEWOv+DOKHdghjjJ/2l5Sxe/9B26MwnlLXHe6eBRCRS4CTVLXUHX4c+CTo6YyJMIfOeGpt11AY7/C3jaIjTs+xlZLdccaYeti0266hMN7j761Q7wMWikhlNx4nAncFJZExEWzFznyio4Re7ZJDHcUYv/l7wd3TIvIhP1wwd6uqZgUvljGRadn2Anq3S7ZTY42n+NvNuADjgYGVF8+JyIigJjMmwqgqy7bnc1SnlqGOYky9+NtG8ShOR3/nucP7gEeCksiYCJVVUMyeAwcZYIXCeIy/bRQjVXWIe/MiVHWviNTWJYcxpoql2/IBrFAYz/F3j6JURKJxL74Tkbb8uJdXY0wdlu0oIErgyA6poY5iTL34Wyj+DbwNtBORe4FvgL8GLZUxEWjZ9nx6tUumRZw1ZBtv8fespxdFZD5OdxoCTFTVlXW8zBjjKikrZ87GXM4c2CHUUYypN78KhYg8r6oXAauqGWeMqcPsDbnsLymzPp6MJ/l76Km/74DbXjE08HGMiUyfLM8iMS6a43qlhzqKMfVWa6EQkdtEZB9wtIgUiMg+d3gXdm8IY/xSUaF8tjKb0b3b2oV2xpNqLRSq+ldVTQH+oaqpqpri/rRR1duaKKMxnjZ3Uy7ZBSWc3N8OOxlv8rcx+zYRaQX0xulyvHL8V8EKZkwkqKhQ/vLBStqlxHNK/4xQxzGmQfxtzL4cuA7oDCwCjgFmAWODF80Y73tt3lYWb8vnX+cOJCne3+tbjQkv/jZmXwcMBzar6knAYCAnaKmMiQCvzt3CH6YtY0T31kwc1CnUcYxpMH+/4hSrarGIICLxqrpKRPoGNZkxHnWgpIw/vbuc1+ZtY3Sftjxy/mCcfjWN8SZ/C8U2EUkDpgGfisheYEfwYhnjTYu35nHdKwvZnFvI1WN6csOEPsRG+7vjbkx48rcxe5L79C735kUtgY+ClsoYjymvUB6fuZ5/fbqGdinxvHzFMRzTo02oYxkTELUWChFpXc3ope5jMpAb8ETGeMyOvCJueHUR32/M5SdHd+AvE4+iZWJsqGMZEzB17VHMx+kxtroDrAr0CHgiYzzk/SU7ue2tJZRVKP/4+dH8fGhna48wEafWQqGq3ZsqiDFecqCkjLumL+f1+dsY2CWNh84dRGZ6UqhjGRMU/l5HMbq68XbBnWmOFm3N43q3wfq3J/XiuvG9rcHaRDR/z3q6yed5AjAC57CUXXBnmg3fBuv2qQm8csUxjLQGa9MM+HvW05m+wyLSBfh7UBIZE4Z25BVx/auLmLMxlzOO7sC9k46iZQtrsDbNQ0P7FNgGDAhkEGPC1XtLdnD7W0spr1D+ec5Azh7SyRqsTbPibxvFw7j3y8bp9mMQsDhYoYwJB/vdBus35m9jUJc0HvrFILq1sQZr0/z4u0cxz+d5GfCyqn4bhDzGhIVF7hXWW3MLuXZsL64ZZw3Wpvnyt43i2WAHMSYclFcoj81Yx78+W0tGagKvTBnFiO7VXXdqTPPh76GnM4A/A93c1wigqpoaxGzGNKnteUXc8Moi5mzK5cyBHbln4gBrsDYG/w89PQj8DFiqqlrXzMZ4zbuLd3D720tRhQcmD2TSYGuwNqaSv4ViK7DMioSJNPtLyrjzneW8uWAbg7um8dC5g+naJjHUsYwJK/4WipuBD0RkJlBSOVJVHwhKKmOawMIte7nulUVs21vIteN6c+3YXsRYg7Uxh/G3UNwL7Me5KjsuGEHci/ieAzKACmCqqj7k9mD7KpAJbAImq+reYGQwzUN5hfLol+t48HOnwfq1X49iWKY1WBtTE38LRWtVPTmoSZzTbm9U1QUikgLMF5FPgUuAz1X1PhG5FbgVuCXIWUyE2ra3kN+9upg5m3I5a1BH/jxxAKkJ1mBtTG38LRSficjJqvpJsIKo6k5gp/t8n4isBDoBZwFj3NmeBWZghcLUk6ry9sLt3PnOchT417kDmTS4c6hjGeMJ/haK3wA3i0gJUEqQT48VkUxgMPA90N4tIqjqThFpV8NrpgBTALp27RqMWMaj8goP8n9vL+P9pTsZntmKByYPoktra7A2xl/+XnCXEuwglUQkGXgTuF5VC/w9RVFVpwJTAYYNG2ZnZxkAvlm7mxtfX0TugYPcfGpffj26J9FRdtqrMfVR161Q+6nqKhEZUt10VV0QyDAiEotTJF5U1bfc0dki0sHdm+gA7ArkOk1kKi4t528freLpbzfRq10yT148nAGdWoY6ljGeVNcexe9wDufcX800JYD3oxBn1+FJYGWV026nAxcD97mP7wRqnSYyzVyTwx3TlrElt5BLjs3k1tP6kRAbHepYxnhWXbdCneI+ntQEWY4DLgKWisgid9ztOAXiNRG5DNgCnNMEWYwH7dpXzJ/fW8m7i3fQIz2Jl64YybE900MdyxjPq+vQ03Bgq6pmucO/BM4GNgN3qWpuoIKo6jc4jeTVGReo9ZjIU1GhvDhnC3//aBUlpRXcML4PV47pQXyM7UUYEwh1HXp6AhgPh+6bfR9wDc79KKYCPw9qOmPqsHJnAbe/vZSFW/I4tmcb7pk4gB5tk0Mdy5iIUlehiPbZazgX52rpN4E3fQ4PGdPkysorePCztTw2cz0tW8RaR37GBFGdhUJEYlS1DOfwz5R6vNaYoNiZX8S1Ly9k7qa9nD2kM3/4yRG0SgpKzzLGGOr+sH8ZmCkiu4Ei4GsAEekF5Ac5mzGH+XL1Lm58bTHFpeU8eO4gJg7uFOpIxkS8us56uldEPgc6AJ/4dDMehdNWYUyTKCkr528fruapbzfSLyOFRy4YQk9rizCmSdR5+EhVZ1czbk1w4hhzuLXZ+7julUWs2Flg10UYEwLWztDMzNuUS5fWibRPTQh1lDqVlJXz6JfreXTGOlISYnny4mGMO6J9qGMZ0+xYoWhGNu0+wC+mzqZfhxSm/+Z4osK4z6NZ6/dwxzvLWLdrPxMHdeSOM46kTXJ8qGMZ0yxZoWhG/vnJaspVWba9gDcXbOOcYV1CHekwm3Yf4C8frOSTFdl0SmvB05cO56S+1XYYbIxpIlYomonlO/J5b8lOfnNST75dt4d/fLyanw7qGDZXL+cXlvLvL9by3KxNxEVHcdMpfbns+O7WFmFMGLBC0Ux8uDSL6Chhygk9GZ7ZmkuensuM1Tmc0j8jpLkOlJTxzHebmPrVBgqKS5k8tAs3ntKHdinh34ZiTHNhhaKZmL1hD0d1aknLxFiO75VOenI80xZuD1mh2LWvmDfmb+PJrzey58BBxvZrx40n96F/R+sK3JhwY4WiGSg6WM7ibXlcdnwPAGKio/jpwI68MHsz+UWltGzRNPeMLiuv4MvVObw6dytfrt5FeYVyfK90fndyH4Z0bdUkGYwx9WeFohlYsGUvpeXKMT1aHxo3aXAnnvp2I+8v2cn5I4N769j1Oft5bd5W3lqwnZx9JaQnx3P5Cd2ZPKyLXTRnjAdYoWgGZm/YQ3SUMCzzh0IxoFMqfdun8NKczZw3oktQOtP7fsMe7v90DXM25hIdJZzUty2Th3XhpH7tiI2OCvj6jDHBYYWiGZi13mmfSI7/4c8tIlw4qht3TFvGoq15DA7goZ/d+0u4c/py3l+yk4zUBG45tR9nD+lEOw9c5GeMOZwVigiXX1jKwq15XHlij8OmTRrcib99uIrnZ20OSKEoK6/gpTlbeODTNRSWlHPD+D5MGd2DFnF2iqsxXmaFIsLNXJtDeYVW2/VFcnwMZw/pxMtztvL7U/rSMa1Fg9ahqsxYncNfPljJ2l37GdWjDXef1Z/e7VMaG98YEwbsQHGE+2JlNq2T4hjYOa3a6VNO7AnAw1+sq/eyD5ZV8Mb8bZz20Ndc+sxcDpZXMPWiobx0xUgrEsZEENujiGBl5RXMWJPD2H7tiK6hX6dOaS04b0QXXvx+C1ee2INubZJqXaaqsmBLHtMXbee9JTvZc+Agfdun8I+fH81ZgzoRF2PfPYyJNFYoItiCLXnkFZYyrl/tPa7+5qRevD5/Gze9voSXrhhJTJUzkkrLK5i7MZdPVmTz6YpstucVER8Txfgj2jN5eBdG9063W5AaE8GsUESwtxdup0VsNCf2bVvrfO1SE7h30gBueHUxd727nFtO7UdFBXy7fjefrsjmi1W7yC8qJS4mihN6pXP9+N6cOiCDlISmuVDPGBNaVigiVHFpOe8t2cGpAzJ+dFpsTSYN7szirfk8890mXp27ldJy52aGaYmxjDuiHScfmcHoPukkxtlbxpjmxv7rI9SnK7LZV1zG2UM6+/2au37an0mDOzF98Q7Sk+MZ0jWNod1aHXYoyhjTvFihiFCvzdtKh5YJjOrZpl6vG9gljYFdqj9DyhjTPNlXxQi0cMtevl67m4tGdavxbCdjjPGXFYoI9OBna2mVGMvFozJDHcUYEwGsUESYdxfvYOaaHKaM7kmSH43YxhhTF/sk8biDZRUcKCkjt/AgM1bn8NcPVjI8sxWXHpcZ6mjGmAhhhSJAtuYWsnxHPnsOHKS4tILi0nLKK5TyCkVVKVelQqGiQqlwn1c3rbRcKSkr52BZBSVlFe5juc9zZ7i4tILCg2WHTmOtNKxbK566ZLjda9oYEzBWKBqhvEJ5bd5Wnpu1mZU7C2qcTwSiRIgWQQSio4SoKs+dH4iNjiI+Joq4GOcxPiaapPgYWidVjot2x0eRFB9DUnwMiXHRJMfHMLhrGj3bJttV0saYgLJC0UCbdh/g6hcXsGJnAUd1askfzziSod1akdEygYSYaOJjo4iNjiJKsA9uY4ynWaFogBU7CvjlU3OoUOWR84dw+lEZVgyMMRHLCkU9zduUy6XPzCUlPobnLjuGXu3sns/GmMhmhaIevly9i6temE/Hli14/vKRdGrgjX6MMcZLPHEdhYicKiKrRWSdiNza1OtXVV6bu5Urnp1Hr3bJvHblKCsSxphmI+z3KEQkGngEmABsA+aKyHRVXdEU61+4ZS8Pfb6WGatzGNWjDU/8ciip1r22MaYZCftCAYwA1qnqBgAReQU4CwhooVBVnv1uE8VlFewrLmXb3iIWbsljS24hKfEx3HHGkVxybKb1nWSMaXa8UCg6AVt9hrcBI6vOJCJTgCkAXbt2rfdKRIR7P1hJabkSHSVkpCYwoFMqU0b3YOLgTn7d08EYYyKRFz79qvsKr4eNUJ0KTAUYNmzYYdP9Mef28cTHRpEQE02U7TkYYwzgjUKxDejiM9wZ2BGMFbVKigvGYo0xxtO8cNbTXKC3iHQXkTjgF8D0EGcyxphmI+z3KFS1TER+C3wMRANPqeryEMcyxphmI+wLBYCqfgB8EOocxhjTHHnh0JMxxpgQskJhjDGmVlYojDHG1MoKhTHGmFqJaoOuTQtrIpIDbG7gy9OB3QGM0xS8kNkLGavyWmav5a3ktdxeywv+Ze6mqm2rmxCRhaIxRGSeqg4LdY768EJmL2SsymuZvZa3ktdyey0vND6zHXoyxhhTKysUxhhjamWF4nBTQx2gAbyQ2QsZq/JaZq/lreS13F7LC43MbG0UxhhjamV7FMYYY2plhcIYY0ytrFAYY4wPEbG7llVhhcIYDxGR2FBnaAgRSXIfvfAh3BI8k/UwwcjdrAqFiBwtIu1DnaM+RGSsiPxKRHqFOktNRGSCiFwjIoNCncVfIjJCRJ4TkbRQZ/GHiJwiIk8CA0KdpT5E5AwR+RS4AEDD+OwZ939tNfAihHdWXyJyuojcKyKTIDi5m0WhEJE0EZkGLAB+IiIJoc5UFxFpLyJvA38GBgGPicjJ7rSw+KYjIhki8iZwJ863sEdE5NQQx/LXBOBM4HgRCdv7sohIuohMB/4PmK6qC0OdyV8iMh64G3jEvad9WBKRLiLyCnAX8C6wUUTSQ5uqbiISLyL/A27D6bLoARH5eTDWFbb/IAHWGfgS+BroDxwBhPs/3MnAIlX9E4CIXA1MBD4Jo286xwIzVPVhOHR4oTy0kWonIuJuvxKc98MvgRXAhpAGq9kInH56fq+q34lIrKqWhjqUn8YAT6rqNPeQWayqFoY4U3XOB75T1X+LyADgQWBviDP5I9F9PF9Vt7p7x8XBWFHE7lGIyDgROcIdXI1zwcl/gFScb5GtQhauBm7mI93BD4EnfSZHA1nufCH7u1XJOM2nSPwauAo4QkTGuePC4v3lZu4Hzm65+6GVBvwOp2CMdecLiy9OVbbxbOB14DQR+Q3wpoj8QUTOducNi20MP97OrmygWEQuAL4HporI/4Um3Y+5WfsDqOrfVPXf7vNlQDfgJHe+sNh7r1RlG7cHugATROQ6nD2iE0XkikCvNyz+MQJJRLoA03G+EVS4u5RvqGqeO/0tYDKwTERmuB8cEspv6TVkfl1Vd/t8g2yBU+RQ1YowyfgGkOe2TfQALsR5T70gIkerak5T5/RVQ+a3VXWP++0rAeew2ZvuHttvgFlhlvclYCbwEFAK/BXng2yqiMxU1ZD3YlpD7heACmA4zhfSc3C+AT8uIrNU9YtQ/N/VkPVNVd0rInE42/hNnG0cNu0UNeR+Gvg7cDpwCnACzjZ+XkS+UtXVIhIViM+LsPk2EkD9gM9VdSzOP1Vf4IbKiar6IbAHGOUWiYTKYhGauED1mW90p1UeyhmDs5eBiKS4j02ZubaMS1X1FlV9T1Wn4RzSuawJs9WkuszXu9OKcdpV/gB0BHJUNWRFwlU17xHA71R1AXCDqo5V1U9V9X/AJ8ClIczqq7rc1wDPAr2BtsA2VV2KU/QuhJB9CNf4nlDVg26mNkBrABGJDkHG6lS3je9Q1c9x3gv/UdX5qvo18BnwWwjcl8pILBRHA5VnCH2D8+1gqIj4drH7N5xDJO8Dq0QkI8TfHKrLPEREhqlqhYik4uzGzxWRO4C3RaRNE2euLuNgN2N55SEQ9/BNEfBFE2arSU3vhW44ez5fAxuBYUAbd7c+lF8YquZ9HRglIkNUdV6VbVxOeGxjqD73WKAd8CiQA1Se5BAHfNfUAX348/nwAXAegKqGS5tbddt4uHsYqj3O+6SyqJXitMkGjOcLhc8/T+U/+HNAB/efqwRYibPRzvF52XCcBqy9wAmqmtWEkRuSOR6n0XU2kAn8UlX3hFnGdBG5COdNXIrTQNyk/Mw8A/gVzp5Ee1X9s6puBf4EzG/K4utn3i+Ac93pie7x/u9w9ohWN1VWX/XIfYmqvglMAyaJyLdAT5wP53DKWvXzYQewTkS6N1XOqurxXj4XeBXnhJ2nRWQBzp7y54HM48lCISJHiciN8MOulc8/eB7wNk7DKkABsBNQEYkVkXicXcuTVfVC90MibDO7w0cDn+IUiMtUdUcYZszEOUZ6k6perqr7g5ExAJm34xTeUlXNcRu2UdV3K9uxwiyv7zbuBYwCbmzKbdzA3NuBBBGJVtUPgN8DF6vqJFUN6hlFjfh8iHfHbQduU9WNwcxZVQO3cYpbOM7DOWHnSlU9X1XzAxpOVT33g9OoUwyMcYejgRif6T1xdh+nuMNnAM94MPOzHsjoxe36tMfyhnQbey23194TXtjGnupmXERiVLVMRH6Pc/xzlKqeUGWei4EtwEHgYWAuzvHRu1X1yaY+0yJAmQNy5kKQM3pxuzZZZq/lDWRuy1o7T+QOdRX1o8pOAMb7DAvOYZjewFvAZe74VGApzuX3HdxxmcDPgd6W2XsZvZ7Za3m9mNtLWb2cu0k3Tj03ZH/gFZyGpmHuuBj38R8458APwWnQe9PdoP0ts/czej2z1/J6MbeXskZC7rBqzK5s4ReR1sBXQK6qnqSq8wDU2T1LBDrgVNXzcU4Na6eqBbhn2kgTXq3qhcxeyOj1zF7L68XcXsoaCbl9hVWhwKmmqGouTnWNBxCRS0TkZBHppT/0FTMXSME5X7uziBylblnWpr1y2QuZvZDR65m9lteLub2UNRJyHxIWjdkiMgG4GWd36xtVfUVEWuD0D9MWp1uFrcCJwC9wWv/Xquoa9/UXATNVdYtl9lZGr2f2Wl4v5vZS1kjIXa1QHvdyi1QvnA13FjAYp9HmdnfamTjnXlfO+zROK3/lcBQQZZm9mdHrmb2W14u5vZQ1EnLX+PuEaCMe2hA4NzR51Gfar3AuLmnnO7/7eLbvvJbZexm9ntlreb2Y20tZIyG3Pz9N3kYhIpcC23BuyAPOqV/niUimOxwLrAf+Wfkadfo7uhinp8+PmyysywuZvZCxKq9l9lreSl7K7aWsvrya229NXHGTcfp9uQ7nbnP93PEPAi8D3+J0T3wU8D7OxSdtcBqAZgDDQ/AtIewzeyGj1zN7La8Xc3spayTkrtfvGIKN2tV9vA941X0ejdOt7/HucBfgGZwePmOAbiHdSB7I7IWMXs/stbxezO2lrJGQ29+fJj/0pD+04D8IdBeRU9TpyjdfVb9xp10JFLrzl6nq5qbO6csLmb2QsSqvZfZa3kpeyu2lrL68mttvIa7Cv8Y5/atyeATwDk7HVxmhrqJezeyFjF7P7LW8XsztpayRkLu2n5BdRyFuR3ci8gZON78lOHdmWquq60MSqg5eyOyFjFV5LbPX8lbyUm4vZfXl1dx1CdmV2e7GTMRp2DkP2KKqH4XzxvRCZi9krMprmb2Wt5KXcnspqy+v5q5LTIjXfzXOWQIT1Ln5hhd4IbMXMlbltcxey1vJS7m9lNWXV3PXKKRdeEiQ77MQDF7I7IWMVXkts9fyVvJSbi9l9eXV3LUJi76ejDHGhK9w6z3WGGNMmLFCYYwxplZWKIwxxtTKCoUxjSQiaSJytfu8o3sOvTERwxqzjWkkt4fQ91R1QIijGBMUob6OwphIcB/QU0QWAWuBI1R1gIhcAkzE6RxuAHA/EAdchHPF7umqmisiPYFHcO56Vghcoaqrmv7XMKZ6dujJmMa7FVivqoOAm6pMGwCcj9Pfz71AoaoOxrkN5i/deaYC16jqUOD3wKNNktoYP9kehTHB9aWq7gP2iUg+8K47filwtIgkA8cCr4tI5Wvimz6mMTWzQmFMcPl24VDhM1yB8/8XBeS5eyPGhCU79GRM4+0DUhryQlUtADaKyDkA4hgYyHDGNJYVCmMaSVX3AN+KyDKc21vW1wXAZSKyGFgOnBXIfMY0lp0ea4wxpla2R2GMMaZWViiMMcbUygqFMcaYWlmhMMYYUysrFMYYY2plhcIYY0ytrFAYY4yplRUKY4wxtfp/c0heZJVir3kAAAAASUVORK5CYII=\n", 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" ] @@ -170,6 +162,9 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, @@ -183,36 +178,35 @@ "output_type": "stream", "text": [ "Max: \n", - "array(78.469867)\n", + "array(89.70275121)\n", "Mean: \n", - "array(29.931597)\n", - "Monthly means: \n", - "array([ 2.301253, 5.40517 , 6.245654, 21.922752, 45.427603, 61.997416,\n", - " 68.340861])\n", + "array(40.47293208)\n", + "Monthly means: \n", + "array([[ 2.89125547],\n", + " [ 8.4227791 ],\n", + " [16.53605715],\n", + " [37.70563551],\n", + " [72.60713024],\n", + " [74.67078428],\n", + " [71.38016673]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean(dim='time'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Now, let's do a test: Let's run the model again using the same parameters and check to see that the NSE is the same. \n", + "Now, let's do a test: let's run the model again using the same parameters and check to see that the NSE is the same. \n", "\n", "First, lets extract the diagnostics from the optimized run, giving the calibration NSE." ] @@ -225,7 +219,7 @@ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_s_mn5ix1/Salmon-River-Near-Prince-George_meteo_daily.nc,0.296605,43.4541,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_cfi9s05f/Salmon-River-Near-Prince-George_meteo_daily.nc,0.486033,37.1449,\\n'" ] }, "execution_count": 7, @@ -241,7 +235,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Run the GR4J-Cemaneige WPS:" + "Run the GR4J-Cemaneige WPS:" ] }, { @@ -278,7 +272,7 @@ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_10iqayxm/Salmon-River-Near-Prince-George_meteo_daily.nc,0.296605,43.4541,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_srkpkj77/Salmon-River-Near-Prince-George_meteo_daily.nc,0.486033,37.1449,\\n'" ] }, "execution_count": 9, @@ -289,20 +283,6 @@ "source": [ "diagnostics2" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -321,7 +301,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_OSTRICH_hbvec.ipynb b/docs/source/notebooks/running_OSTRICH_hbvec.ipynb index 41688f1a..187ce4ed 100644 --- a/docs/source/notebooks/running_OSTRICH_hbvec.ipynb +++ b/docs/source/notebooks/running_OSTRICH_hbvec.ipynb @@ -23,8 +23,10 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, @@ -55,6 +57,8 @@ " upperbounds=upperBounds,\n", " start_date=dt.datetime(1954, 1, 1),\n", " duration=208,\n", + " # Comment out the random seed to show different results!\n", + " random_seed=6.67408*10**-11\n", " )\n", "\n", "# Let's call Ostrich with the timeseries, calibration parameters and other configuration parameters\n", @@ -82,7 +86,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "-2.109419, 2.494735, 4.804567, 0.06091903, 0.9809654, 0.792112, 6.161714, 46.20748, 0.3215812, 0.07319383, 0.05577936, 1.376497, 4.691862, 0.08684631, 0.6341399, 3.674934, 0.1786707, 0.3155837, 0.4050665, 1.259177, 1.375223\n" + "-0.8317931, 4.072232, 2.001574, 0.005736299, 0.09985144, 0.4422529, 3.438486, 80.55843, 0.4440133, 0.08451082, 2.814201, 0.732797, 1.119773, 0.001161223, 0.4597179, 15.45857, 1.223865, 0.4452843, 0.9492006, 0.9948123, 1.110682\n" ] } ], @@ -107,12 +111,12 @@ "text/plain": [ "\n", "array([[ 1. ],\n", - " [ 1.350335],\n", - " [ 1.536331],\n", + " [ 0.747941],\n", + " [ 1.014662],\n", " ...,\n", - " [ 9.204034],\n", - " [28.741458],\n", - " [55.736687]])\n", + " [ 1.419883],\n", + " [ 6.405398],\n", + " [24.354933]])\n", "Coordinates:\n", " * time (time) datetime64[ns] 1954-01-01 1954-01-02 ... 1954-07-28\n", " basin_name (nbasins) object ...\n", @@ -136,22 +140,10 @@ "execution_count": 5, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 5, @@ -160,7 +152,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -172,6 +164,9 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, @@ -185,36 +180,35 @@ "output_type": "stream", "text": [ "Max: \n", - "array(55.736687)\n", + "array(53.46195941)\n", "Mean: \n", - "array(3.622171)\n", - "Monthly means: \n", - "array([ 0.554835, 0. , 0. , 0. , 6.731431, 8.349132,\n", - " 10.024486])\n", + "array(2.70970312)\n", + "Monthly means: \n", + "array([[5.70648088e-01],\n", + " [2.19688243e-03],\n", + " [0.00000000e+00],\n", + " [0.00000000e+00],\n", + " [1.50787290e+01],\n", + " [2.76486850e-01],\n", + " [2.60146947e+00]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean(dim='time'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Now, let's do a test: Let's run the model again using the same parameters and check to see that the NSE is the same. \n", + "Now, let's do a test: let's run the model again using the same parameters and check to see that the NSE is the same. \n", "\n", "First, lets extract the diagnostics from the optimized run, giving the calibration NSE." ] @@ -227,7 +221,7 @@ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_zeodylhi/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.363627,60.5033,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_5ct3x9tp/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.267594,58.3339,\\n'" ] }, "execution_count": 7, @@ -243,7 +237,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Run the HBV-EC WPS:" + "Run the HBV-EC WPS:" ] }, { @@ -280,7 +274,7 @@ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process__jfd2048/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.363627,60.5033,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_ebwf37rr/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.267594,58.3339,\\n'" ] }, "execution_count": 9, @@ -309,7 +303,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_OSTRICH_hmets.ipynb b/docs/source/notebooks/running_OSTRICH_hmets.ipynb index 1a2c3303..2e5677ed 100644 --- a/docs/source/notebooks/running_OSTRICH_hmets.ipynb +++ b/docs/source/notebooks/running_OSTRICH_hmets.ipynb @@ -1,12 +1,5 @@ { "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "markdown", "metadata": {}, @@ -18,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -30,14 +23,16 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -62,6 +57,8 @@ " upperbounds=upperBounds,\n", " start_date=dt.datetime(1954, 1, 1),\n", " duration=208,\n", + " # Comment out the random seed to show different results!\n", + " random_seed=6.67408*10**-11\n", " )\n", "\n", "# Let's call Ostrich with the timeseries, calibration parameters and other configuration parameters\n", @@ -82,14 +79,14 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "13.31983, 3.328057, 12.79472, 0.5403419, 16.85742, 18.08806, 1.399901, 0.0818848, 0.02471968, 0.2873767, 0.06291079, -4.743387, 4.37551, 0.6127615, 0.3647348, 0.6737468, 0.006686769, 0.005365207, 4.287844e-05, 319.23049999999995, 1600.615\n" + "18.06003, 3.510955, 11.9534, 1.413509, 16.62893, 34.57137, -0.2226484, 0.139122, 0.05429963, 0.2904521, 0.02706042, -4.562373, 0.6481391, 0.5493992, 2.509283, 0.421356, 0.0178487, 0.07768531, 0.004568809, 114.7092, 402.8124\n" ] } ], @@ -106,20 +103,20 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\n", - "array([[ 0. ],\n", - " [21.910529],\n", - " [43.569006],\n", + "array([[ 0. ],\n", + " [132.342029],\n", + " [254.357644],\n", " ...,\n", - " [61.20397 ],\n", - " [64.184711],\n", - " [58.771086]])\n", + " [ 88.478696],\n", + " [122.117354],\n", + " [160.636378]])\n", "Coordinates:\n", " * time (time) datetime64[ns] 1954-01-01 1954-01-02 ... 1954-07-28\n", " basin_name (nbasins) object ...\n", @@ -129,7 +126,7 @@ " long_name: Simulated outflows" ] }, - "execution_count": 13, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -140,22 +137,22 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 14, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -167,12 +164,15 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -180,52 +180,51 @@ "output_type": "stream", "text": [ "Max: \n", - "array(190.442999)\n", + "array(254.3576443)\n", "Mean: \n", - "array(49.217406)\n", - "Monthly means: \n", - "array([35.55974 , 58.270092, 55.496248, 43.80036 , 40.752294, 51.621828,\n", - " 60.93403 ])\n", + "array(102.12207978)\n", + "Monthly means: \n", + "array([[112.83436712],\n", + " [122.62511706],\n", + " [105.9590156 ],\n", + " [ 73.66921186],\n", + " [ 76.18933914],\n", + " [110.17983101],\n", + " [116.07413332]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean(dim='time'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Now, let's do a test: Let's run the model again using the same parameters and check to see that the NSE is the same. \n", + "Now, let's do a test: let's run the model again using the same parameters and check to see that the NSE is the same. \n", "\n", "First, lets extract the diagnostics from the optimized run, giving the calibration NSE." ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_cprncb4l/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.296803,59.0022,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_4shfx769/Salmon-River-Near-Prince-George_meteo_daily.nc,-2.2878,93.9472,\\n'" ] }, - "execution_count": 16, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -238,12 +237,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Run the HMETS WPS:" + "Run the HMETS WPS:" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -269,16 +268,16 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_gy_vg0uy/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.296798,59.0021,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_iz6d6pl1/Salmon-River-Near-Prince-George_meteo_daily.nc,-2.28789,93.9485,\\n'" ] }, - "execution_count": 19, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -286,13 +285,6 @@ "source": [ "diagnostics2" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -311,7 +303,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_OSTRICH_mohyse.ipynb b/docs/source/notebooks/running_OSTRICH_mohyse.ipynb index af4d1ec2..497379ca 100644 --- a/docs/source/notebooks/running_OSTRICH_mohyse.ipynb +++ b/docs/source/notebooks/running_OSTRICH_mohyse.ipynb @@ -23,8 +23,10 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, @@ -57,6 +59,8 @@ " duration=208,\n", " hruslowerbounds=low_h,\n", " hrusupperbounds=high_h,\n", + " # Comment out the random seed to show different results!\n", + " random_seed=6.67408*10**-11\n", " )\n", "\n", "# Let's call Ostrich with the timeseries, calibration parameters and other configuration parameters\n", @@ -85,7 +89,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "2.265868, 0.5946992, 3.08262, -1.713234, 0.399964, 0.817625, 0.1728091, 0.2371443\n" + "7.721801, 0.8551484, 17.74571, 1.627677, 0.0770245, 0.94096, 0.6941596, 0.820787\n" ] } ], @@ -102,20 +106,20 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\n", - "array([[0. ],\n", - " [0. ],\n", - " [0. ],\n", + "array([[ 0. ],\n", + " [ 0. ],\n", + " [ 0. ],\n", " ...,\n", - " [0.007406],\n", - " [0.006391],\n", - " [0.005514]])\n", + " [17.875367],\n", + " [17.30535 ],\n", + " [16.747392]])\n", "Coordinates:\n", " * time (time) datetime64[ns] 1954-01-01 1954-01-02 ... 1954-07-28\n", " basin_name (nbasins) object ...\n", @@ -125,7 +129,7 @@ " long_name: Simulated outflows" ] }, - "execution_count": 16, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -136,22 +140,22 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 17, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -163,12 +167,15 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -176,52 +183,51 @@ "output_type": "stream", "text": [ "Max: \n", - "array(146.85637)\n", + "array(61.20512771)\n", "Mean: \n", - "array(28.636496)\n", - "Monthly means: \n", - "array([ 0. , 32.668187, 18.570773, 1.424412, 84.384503, 56.746038,\n", - " 4.771117])\n", + "array(26.91468185)\n", + "Monthly means: \n", + "array([[ 0. ],\n", + " [ 0.26801909],\n", + " [11.08674251],\n", + " [40.6703697 ],\n", + " [59.69526693],\n", + " [48.95010152],\n", + " [26.2431265 ]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean(dim='time'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Now, let's do a test: Let's run the model again using the same parameters and check to see that the NSE is the same. \n", + "Now, let's do a test: let's run the model again using the same parameters and check to see that the NSE is the same. \n", "\n", "First, lets extract the diagnostics from the optimized run, giving the calibration NSE." ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,./model//Salmon-River-Near-Prince-George_meteo_daily.nc,0.651872,30.5704,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,./model//Salmon-River-Near-Prince-George_meteo_daily.nc,0.382681,40.7086,\\n'" ] }, - "execution_count": 19, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -234,12 +240,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Run the MOHYSE WPS:" + "Run the MOHYSE WPS:" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -265,16 +271,16 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_o3sh820c/Salmon-River-Near-Prince-George_meteo_daily.nc,-1.06254,74.4102,\\n'" + "'observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\\nHYDROGRAPH,/tmp/pywps_process_0vaxo6s8/Salmon-River-Near-Prince-George_meteo_daily.nc,-1.81387,86.9127,\\n'" ] }, - "execution_count": 21, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -300,7 +306,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_gr4jcn.ipynb b/docs/source/notebooks/running_gr4jcn.ipynb index 9a3b1e12..e63f25b5 100644 --- a/docs/source/notebooks/running_gr4jcn.ipynb +++ b/docs/source/notebooks/running_gr4jcn.ipynb @@ -23,8 +23,10 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, @@ -76,7 +78,7 @@ "output_type": "stream", "text": [ "observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\n", - "HYDROGRAPH,/tmp/pywps_process_4mgf___s/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.0371048,36.562,\n", + "HYDROGRAPH,/tmp/pywps_process_77cmowdi/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.0371048,36.562,\n", "\n" ] } @@ -131,22 +133,10 @@ "execution_count": 5, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 5, @@ -155,7 +145,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -167,6 +157,9 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, @@ -180,37 +173,34 @@ "output_type": "stream", "text": [ "Max: \n", - "array(89.922826)\n", + "array(89.92282574)\n", "Mean: \n", - "array(24.683159)\n", - "Monthly means: \n", - "array([14.517574, 11.473847, 10.072479, 20.420102, 24.375415, 22.558126,\n", - " 23.561023, 25.30086 , 28.723886, 34.377812, 46.446956, 34.094862])\n", + "array(24.68315926)\n", + "Monthly means: \n", + "array([[14.51757372],\n", + " [11.47384691],\n", + " [10.07247858],\n", + " [20.42010158],\n", + " [24.37541465],\n", + " [22.55812604],\n", + " [23.56102348],\n", + " [25.30086037],\n", + " [28.72388552],\n", + " [34.37781245],\n", + " [46.44695633],\n", + " [34.09486191]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean(dim='time'))" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -229,7 +219,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_hbv_ec.ipynb b/docs/source/notebooks/running_hbv_ec.ipynb index 68c3d6af..07039acb 100644 --- a/docs/source/notebooks/running_hbv_ec.ipynb +++ b/docs/source/notebooks/running_hbv_ec.ipynb @@ -23,8 +23,10 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, @@ -78,7 +80,7 @@ "output_type": "stream", "text": [ "observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\n", - "HYDROGRAPH,/tmp/pywps_process_a34_fcsg/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.075407,37.231,\n", + "HYDROGRAPH,/tmp/pywps_process_5s8wml7k/Salmon-River-Near-Prince-George_meteo_daily.nc,-0.075407,37.231,\n", "\n" ] } @@ -133,22 +135,10 @@ "execution_count": 5, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 5, @@ -157,7 +147,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -169,6 +159,9 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, @@ -182,51 +175,34 @@ "output_type": "stream", "text": [ "Max: \n", - "array(124.863331)\n", + "array(124.86333084)\n", "Mean: \n", - "array(6.545083)\n", - "Monthly means: \n", - "array([ 1.193633, 0.054158, 4.185645, 28.760802, 20.226352, 2.752982,\n", - " 0.368491, 0.036348, 0. , 1.09206 , 16.624839, 3.516866])\n", + "array(6.54508271)\n", + "Monthly means: \n", + "array([[ 1.19363324],\n", + " [ 0.05415771],\n", + " [ 4.18564509],\n", + " [28.76080213],\n", + " [20.22635228],\n", + " [ 2.7529817 ],\n", + " [ 0.36849142],\n", + " [ 0.03634777],\n", + " [ 0. ],\n", + " [ 1.09206023],\n", + " [16.62483913],\n", + " [ 3.51686589]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:631: FutureWarning: Default reduction dimension will be changed to the grouped dimension after xarray 0.12. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean(dim='time'))" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -245,7 +221,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_hmets.ipynb b/docs/source/notebooks/running_hmets.ipynb index 42e0a2aa..484614a4 100644 --- a/docs/source/notebooks/running_hmets.ipynb +++ b/docs/source/notebooks/running_hmets.ipynb @@ -11,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -23,14 +23,16 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -69,7 +71,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -77,7 +79,7 @@ "output_type": "stream", "text": [ "observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\n", - "HYDROGRAPH,/tmp/pywps_process_5taxoom3/Salmon-River-Near-Prince-George_meteo_daily.nc,-7.03141,101.745,\n", + "HYDROGRAPH,/tmp/pywps_process__g9g2ezm/Salmon-River-Near-Prince-George_meteo_daily.nc,-7.03141,101.745,\n", "\n" ] } @@ -95,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -118,7 +120,7 @@ " long_name: Simulated outflows" ] }, - "execution_count": 13, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -129,22 +131,22 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 14, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -156,12 +158,15 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -169,37 +174,34 @@ "output_type": "stream", "text": [ "Max: \n", - "array(338.27671)\n", + "array(338.27670973)\n", "Mean: \n", - "array(114.215205)\n", - "Monthly means: \n", - "array([145.476253, 100.23014 , 72.545359, 100.553173, 158.081297, 131.898128,\n", - " 132.254124, 129.301576, 122.491754, 104.234391, 108.015783, 64.065156])\n", + "array(114.21520508)\n", + "Monthly means: \n", + "array([[145.47625261],\n", + " [100.23013979],\n", + " [ 72.54535855],\n", + " [100.5531725 ],\n", + " [158.08129744],\n", + " [131.89812816],\n", + " [132.25412379],\n", + " [129.30157554],\n", + " [122.49175427],\n", + " [104.23439113],\n", + " [108.01578307],\n", + " [ 64.06515605]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:639: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby(hydrograph.time.dt.month).mean(dim='time'))" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -218,7 +220,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/running_mohyse.ipynb b/docs/source/notebooks/running_mohyse.ipynb index 922d0aec..9e7bfc3a 100644 --- a/docs/source/notebooks/running_mohyse.ipynb +++ b/docs/source/notebooks/running_mohyse.ipynb @@ -23,14 +23,16 @@ "import xarray as xr\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", + "import os\n", "\n", - "url = \"http://localhost:9099/wps\"\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", "wps = WPSClient(url)" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -70,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -78,7 +80,7 @@ "output_type": "stream", "text": [ "observed data series,filename,DIAG_NASH_SUTCLIFFE,DIAG_RMSE,\n", - "HYDROGRAPH,/tmp/pywps_process_ijnz75tu/Salmon-River-Near-Prince-George_meteo_daily.nc,0.194612,32.2196,\n", + "HYDROGRAPH,/tmp/pywps_process_27_cdno5/Salmon-River-Near-Prince-George_meteo_daily.nc,0.194612,32.2196,\n", "\n" ] } @@ -96,7 +98,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -119,7 +121,7 @@ " long_name: Simulated outflows" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -130,34 +132,22 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -169,12 +159,15 @@ } ], "source": [ + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "hydrograph.q_sim.plot()" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -182,44 +175,34 @@ "output_type": "stream", "text": [ "Max: \n", - "array(130.839158)\n", + "array(130.83915822)\n", "Mean: \n", - "array(48.388493)\n", - "Monthly means: \n", - "array([ 6.244476, 2.5561 , 9.116048, 62.749083, 92.796087, 60.448192,\n", - " 59.048115, 57.816124, 63.594515, 53.422058, 80.203944, 32.019845])\n", + "array(48.38849311)\n", + "Monthly means: \n", + "array([[ 6.24447576],\n", + " [ 2.55609967],\n", + " [ 9.11604814],\n", + " [62.74908332],\n", + " [92.79608734],\n", + " [60.44819211],\n", + " [59.04811531],\n", + " [57.81612411],\n", + " [63.59451548],\n", + " [53.42205803],\n", + " [80.20394387],\n", + " [32.01984468]])\n", "Coordinates:\n", - " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ets/miniconda3/lib/python3.7/site-packages/xarray/core/groupby.py:631: FutureWarning: Default reduction dimension will be changed to the grouped dimension after xarray 0.12. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.\n", - " skipna=skipna, allow_lazy=True, **kwargs)\n" + " basin_name (nbasins) object ...\n", + " * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n", + "Dimensions without coordinates: nbasins\n" ] } ], "source": [ "print(\"Max: \", hydrograph.q_sim.max())\n", "print(\"Mean: \", hydrograph.q_sim.mean())\n", - "print(\"Monthly means: \", hydrograph.q_sim.groupby('time.month').mean())" + "print(\"Monthly means: \", hydrograph.q_sim.groupby(hydrograph.time.dt.month).mean(dim='time'))" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -238,7 +221,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/Time series analysis.ipynb b/docs/source/notebooks/time_series_analysis.ipynb similarity index 55% rename from docs/source/notebooks/Time series analysis.ipynb rename to docs/source/notebooks/time_series_analysis.ipynb index a784eef0..7cfecf76 100644 --- a/docs/source/notebooks/Time series analysis.ipynb +++ b/docs/source/notebooks/time_series_analysis.ipynb @@ -13,17 +13,19 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "from birdy import WPSClient\n", - "url = \"http://localhost:9099/wps\"\n", - "wps = WPSClient(url)#, processes='base_flow_index')\n", - "\n", "from example_data import TESTDATA\n", + "import os\n", + "\n", + "# Set environment variable RAVEN_WPS_URL to \"http://localhost:9099\" to run on the default local server\n", + "url = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", + "wps = WPSClient(url)\n", "fn = str(TESTDATA['simfile_single'])" ] }, @@ -38,7 +40,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -54,9 +56,9 @@ " ----------\n", " q : ComplexData:mimetype:`application/x-netcdf`\n", " NetCDF Files or archive (tar/zip) containing netCDF files.\n", - " variable : //www.w3.org/TR/xmlschema-2/#string\n", + " variable : string\n", " Name of variable to analyze in netCDF file.\n", - " freq : {'YS', 'MS', 'QS-DEC', 'AS-JUL'}//www.w3.org/TR/xmlschema-2/#string\n", + " freq : {'YS', 'MS', 'QS-DEC', 'AS-JUL'}string\n", " Resampling frequency\n", " \n", " Returns\n", @@ -82,34 +84,22 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/tjs/miniconda3/envs/raven-dev/lib/python3.6/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n", - "\n", - "To register the converters:\n", - "\t>>> from pandas.plotting import register_matplotlib_converters\n", - "\t>>> register_matplotlib_converters()\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -123,6 +113,10 @@ "source": [ "resp = wps.base_flow_index(fn, variable='q_sim')\n", "out, log = resp.get(asobj=True)\n", + "\n", + "from pandas.plotting import register_matplotlib_converters\n", + "register_matplotlib_converters()\n", + "\n", "out.base_flow_index.plot()" ] }, @@ -135,7 +129,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -149,15 +143,15 @@ " ----------\n", " da : ComplexData:mimetype:`application/x-netcdf`\n", " NetCDF Files or archive (tar/zip) containing netCDF files.\n", - " variable : //www.w3.org/TR/xmlschema-2/#string\n", + " variable : string\n", " Name of variable to analyze in netCDF file.\n", - " op : {'min', 'max', 'mean', 'std', 'var', 'count', 'sum', 'argmax', 'argmin'}//www.w3.org/TR/xmlschema-2/#string\n", + " op : {'min', 'max', 'mean', 'std', 'var', 'count', 'sum', 'argmax', 'argmin'}string\n", " Operation name\n", - " freq : {'YS', 'MS', 'QS-DEC', 'AS-JUL'}//www.w3.org/TR/xmlschema-2/#string\n", + " freq : {'YS', 'MS', 'QS-DEC', 'AS-JUL'}string\n", " Resampling frequency\n", - " season : {'DJF', 'MAM', 'JJA', 'SON'}//www.w3.org/TR/xmlschema-2/#string\n", + " season : {'DJF', 'MAM', 'JJA', 'SON'}string\n", " Season selection specification.\n", - " month : {'1', '2', '3', '4', '5', '6', '7', '8', '9', '10', ...}//www.w3.org/TR/xmlschema-2/#string\n", + " month : {'range(1, 13)'}string\n", " Month selection specification\n", " \n", " Returns\n", @@ -176,22 +170,22 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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USW00s4u7F2Z2kkRtTcS78nDO9WmJVD1dTjBO9asAZva2pM56wtsP+FycfQn4ZbcizHK11RGef+tttu5soaQokbfTOedySyJntp1mtqutmwpJBXQ+TsW3wuqpTknqU20edaMimMG8FVv4t3FDMx2Oc84lXSJXPT0v6VpgoKSTgD8D0zta0czu62pniayTS2qrw6FRvYNA51wflUiiuAZYB8wDvgA8Bvxndw8k6ZYuXi+W9JqkOZIWtJU8JA2R9LSkt8PHrBqoesheAxg1ZJDfoe2c67MS6T02Cvw2nOKSNKSzl4DTuth8J3C8mW2VVAjMCHut/SjwjJndIOkagsR1dVexpFNdTYSZSzdmOgznnEuJRK56OgP4HjA6XF+AmVlZB6uvA94L12lj4fO4Q8GZmQFbw6eF4WTA2cCx4fI7gefIskRRWxPhkTmrWNvQxN5lxZkOxznnkiqRqqefABcBQ82szMxKO0kSAIuBY81sbMy0j5mNBdZ0dSBJ+ZJmA2uBp83sVWC4mdUDhI8dJhxJl0maKWnmunXrEvizkqeuJrjZzvt9cs71RYkkiuXA/PAXf1d+AnTWhvDDrjY2s1YzqwOqgUMlTUngmG3b3mJm08xsWkVFRaKbJcXkqnIK8uQN2s65PimRy2O/ATwm6XmCdgQAzOzH7Vc0s07vkTCznycalJltlvQccAqwRlKlmdVLqiQobWSV4sJ8JlWWeonCOdcnJVKi+D6wHSgGSmOmhHR1tVPMehWSIuH8QOBEYBHwCEHVF+Hjw4keO51qqyPMXb6FaDSRgpdzzuWOREoUQ8zs5F4cY1qC61UCd0rKJ0hg95nZo5JeBu6TdCmwDDi3F7GkTG1NhLteXcbi9dsYv3dJpsNxzrmkSSRR/E3SyWb2VA+PkVBVkZnNBQ7sYPkGOuhXKtscGDM0qicK51xfkkjV0+XAE5J2SGqQ1CipoRvHOE1SZ1dJ9Rn7VJRQUlTgN9455/qcRLoZLzWzPDMbmMDlsQBIultSmaS9gDeANyV9PVlBZ6P8PHHAyHK/8sk51+ckUqJA0lRJZ0n6aNvUxSb7m1kDcA5Blx+jgM/0MtasVzcqwsL6BpqaWzMdinPOJU0id2bfBkwFFgBtg0Mb8Jc4mxWG3XCcA/zCzJol9fnLgWqrIzS3Gm/UN3DQqKzqkso553oskcbsw81s/27u9zcEo+LNAV6QNBroTrtGTqoLG7TnLN/sicI512ckUvX0sqRuJQoz+5mZjTSz08I7upcBx/UowhwyoryY4WVF3qDtnOtTEilR3EmQLFYT3Jnd1ing1EQPEiaLlp6FmFvqaiJ+h7Zzrk9JJFHcRtAQPY89bRSuE7U1EZ5csIbN23cRGTQg0+E451yvJZIolpnZIymPpI+o2z3i3RaOmZDezgmdcy4VEkkUiyTdTTD8aWyngB1e9SRpRPj6akkVwFHAm2a2IAnxZr0DqsuRggZtTxTOub4gkcbsgQQJ4mTgzHA6o6MVJX0BeBl4RdKXgEfDdf8S9tXU55UWFzK+osTbKZxzfUYiQ6F+thv7+zIwmSC5vAeMD0sWg4G/A7f2KMocU1sT4e+L1mJmSOp6A+ecy2KJ3HB3O8ENdu9jZpd0sHqzmW0Htkt618xWh+tu6g833LWpq4lw/6wVrNi0g5ohgzIdjnPO9UoibRSPxswXAx8BVnWyblRSoZk1A6e3LZRUTILdhfQFdTE9yXqicM7lukSqnh6IfS7pHuBvnaz+UcLSh5mtiFk+FLiqhzHmnIkjShlQkMec5Zs5s7Yq0+E451yvJFKiaG9fgk7+PsDMlnWyfCWwsgfHykmF+XlMqSrznmSdc31Cl9VBbeNPtE0El8le3cU2FycpvpxVVzOYeSu30NLq9yg653JbouNRlMVME9pXR8WS9F8E4133a7U15TQ1R3lzTWOmQ3HOuV5JpERxRDgAEZI+LenHYW+wHa17C7AfcGF3A5FUI+nvkhZKWiDpynD59ZJWSpodTqd1d9+ZsKcn2S0ZjsQ553onkSuRfkVwuWst8A2C+yN+38m6FwDfM7Oe1Le0AFeZ2X7A4cDlMb3W/q+Z1YXTYz3Yd9qNGjKIwYMKvSdZ51zOSyRRtIS9v54N/NTMfgqUdrLuGcB9ksZ1NxAzqzez18P5RmAhMLK7+8kWkqj1nmSdc31AIomiUdI3gU8Df5WUDxR2tKKZPQecD/yxN0FJGgMcCLwaLvqypLmSbgvv8s4JtdUR3lrbyNad/aKHdedcH5VIovgEQV9Pl4Z3Wo8EftTZymY2H/hYTwOSVAI8AHw1HHf7V8A4oA6oB27uZLvLJM2UNHPdunU9PXxS1dVEMIP5K72dwjmXuxK56mm1mf3YzF4Mny8zs87aKNq26ezO7bjCcbYfAO5q653WzNaYWWvY7vFb4NBOjnmLmU0zs2kVFdnRa2ttzNCozjmXq3pyw12XJI0FrgDGxB7DzM6Ks40IOg1caGY/jlleaWb14dOPAPNTEXMqDNlrAKOGDPJ2CudcTktJogAeIjjpTyfxUfGOIBxJT9LscNm1wCcl1RF0DbIU+EJyQ02t2poIs5ZuzHQYzjnXY50mCknPmNkJkm40s7h3Ynegycx+1p0NzGwGwXjc7eXE5bCdqauJMH3OKtY2NLF3WXGmw3HOuW6LV6KolHQMcJake2l3Em+7lLUTP5V0HfAU7x8VL942fVJdTTkQ9CR78uQRGY7GOee6L16i+C/gGqAa+HG71ww4Ps62BxBUIx3PnqqnrrbpkyZXlVOQJ+as8EThnMtNnSYKM7sfuF/St83se93c70eAfcxsV6+i6wOKC/OZVFnqXXk453JWIuNRfE/SWcDR4aLnzOzReNsAc4AIsLaX8fUJtdURHpmzimjUyMvzoVGdc7klkU4BfwBcCbwRTleGy+IZDiyS9KSkR9qm3oebm2prIjQ2tbB4/bZMh+Kcc92WyOWxpwN1bR39SboT+BfwzTjbXJeE2PqMupgb78bvXZLhaJxzrnsSvY8iArTdDFDe1cpm9nyPI+qDxlWUUFJUwJwVm/nYwdWZDsc557olkb6efgD8S9IdYWliFvA/Ha0oqau2i4TW6Wvy88QBI8v9Dm3nXE5KpDH7HknPAYcQ3Etxddg5YEeO7KItQsD+cV7vs2prItw6YzFNza0UF+ZnOhznnEtYQlVPYV9LiTRGn53AOv3yktm6mgjNrcbC+gYOHJUzPaU751xy+3rytonOtTVoz16+2ROFcy6nJNJG4ZJgRHkxw8uKvMtx51zOSahEEY5qN5z3dxm+LFVB9VW11RHmrPA7tJ1zuaXLRCHpCoL7Itbw/n6bpqYwrj6pblSEp95Yw+btu4gMGpDpcJxzLiGJlCiuBCaa2YZUB9PX1VWHN96t2MIxE7JjFD7nnOtKIm0UywGvL0mCA6rLkXxoVOdcbkmkRLEYeE7SX3n/2BLtux7fTdI+ZrY4CfH1KaXFhYyvKPFE4ZzLKYkkimXhNCCcEnGHpJHAP4EXgBfNbF7PQuxbamsi/H3RWsyMYJhw55zLboncmf2d7u7UzI6WNIDgbu5jgb9KKjGzIZ1tI6kG+D0wgqDR/BYz+6mkIcCfgDEEY2afZ2abuhtTtqitiXD/rBWs2LSDmiGDMh2Oc851Kd6Y2T8xs69Kmk5wldP7mNlZcbY9EjgqnCLAo8CLXcTSAlxlZq9LKgVmSXoauBh4xsxukHQNwah73R3DO2vsadDe7InCOZcT4pUo/hA+3tSD/T4PzCToUPCxREa6C7sJqQ/nGyUtBEYSdAtybLjancBz5HCimFRZyoCCPOYs38wZU6syHY5zznUp3lCos8LHnnTLMRQ4gmBUvK9IigIvm9m3E9lY0hjgQOBVYHiYRDCzekl79yCerFGYn8eUqjLvSdY5lzMSGeHuDEn/krRRUoOkRkkN8bYxs80EV0stISgljGPPUKpdHa8EeAD4qpnFPU677S6TNFPSzHXr1iW6WUbU1kSYt3ILLa3Rrld2zrkMS+Q+ip8AFwFDzazMzErNrCzeBpLeBW4GhgC/Jrhh75iuDiSpkCBJ3GVmfwkXr5FUGb5eSSfjcJvZLWY2zcymVVRk981sdTURmpqjvLVma6ZDcc65LiVyeexyYL6ZfaBBO45924ZOTZSCa0VvBRa2u0fjEYJEdUP4+HB39puNYnuS3b8qbs51zrmMSyRRfAN4TNLzJHjDHVAl6ecE7RQGzACuNLMVcbY5AvgMME/S7HDZtQQJ4j5JlxLcz3FuAjFntVFDBjF4UCFzlm/mgsNGZToc55yLK5FE8X1gK1BM4jfc3Q7czZ6T+qfDZSd1toGZzSAYAa8jJyR43JwgidqaCHNWeIO2cy77JZIohpjZyd3cb4WZ3R7z/A5JX+3mPvq02uoIL7z1Ntt2trBXUVLHj3LOuaRKpDH7b5K6myjWS/q0pPxw+jTgvc/GqKuJEDWYt9L7W3TOZbdEEsXlwBOSdiR6eSxwCXAesJrg8tiPh8tcaGp1OeA9yTrnsl8ifT2Vdnen4eh3nXbx4WBoSRGjhgzydgrnXNZLauV4eKVTp5fRmtlXknm8XFdbE2HW0o2ZDsM55+JKdivqzCTvr0+rrS5n+pxVrG1oYu+y4kyH45xzHUp2ojjRzD4j6Uoz+2mS993nHDhqz9CoJ+3vicI5l506bcyWNCTe1MlmB0saDVwiaXCC2/Rbk6vKyc+TN2g757JavBLFLIL2ho5ugjNgnw6W/xp4InxtVrttO9um3youzGfSiFLvSdY5l9XidTM+trs7M7OfAT+T9Csz+1KvIusnamsiTJ+zimjUyMvzoVGdc9knkfsoCKuRDpV0dNsUb31PEomrq4nQ2NTCkg3bMh2Kc851qMvGbEmfA64EqoHZwOHAy8DxqQ2tf9jdk+yyzYyrKMlwNM4590GJlCiuBA4B3jOz4whGnsvukYFyyLiKEvYakO833jnnslYiiaLJzJoAJBWZ2SJgYmrD6j/y88TU6ohf+eScy1qJJIoVkiLAQ8DTkh4GVqU2rP6ltibCG/UNNDW3ZjoU55z7gET6evpIOHu9pL8D5QSXwLokqaspp7nVWFjfwIGjBmc6HOece58uSxSSRrVNwBKCBu0RKY+sH6mrCZKDVz8557JRIl14/JU9N94VA2OBN4HJKYyrXxlRXszwsiLmrPCxKZxz2SeRqqcDYp9LOgj4Qsoi6qdqqyN+h7ZzLisldMNdLDN7neBy2aSSdJuktZLmxyy7XtJKSbPD6bRkHzdb1NZEWLJ+G5u378p0KM459z6J3HD3/2Ke5gEHkZr7KO4AfgH8vt3y/zWzm1JwvKxyYHjj3dwVWzh6QkWGo3HOuT0SKVGUxkxFBG0WZyc7EDN7Aei3o/hMqS5HwqufnHNZJ5E2iu+kI5A4vizpQoJBka4ys00ZjiclyooLGVdR4lc+OeeyTiKXx06QdIukpyQ92zalIzjgV8A4oA6oB26OE+dlkmZKmrluXW72MFJXE2HOis2YdTqarHPOpV0il8f+mWCcid8Bab112MzWtM1L+i3waJx1bwFuAZg2bVpOnmlrayLcP2sFKzfvoHrwoEyH45xzQGKJosXMfpXySDogqdLM6sOnHwHmx1s/19VVhz3JLt/sicI5lzUSacyeLunfJVWmclhTSfcQdF8+UdIKSZcCP5Q0T9Jc4DjgP5J93GwycUQpAwryvJ3COZdVEilRXBQ+fj1mWdKHNTWzT3aw+NZkHiPbDSjIY0pVGXOW+x3azrnskchVT90eEtX1XG1NhHtfW05La5SC/G7fD+mcc0mX6FCoH5J0gaQL26ZUB9Zf1dVE2NHcyltrtmY6FOecAxK7M/sPBJeozmbPVU/GB++gdklw0KjB5AkuvO01zphayTkHjqS2uhxJmQ7NOddPJdJGMQ3Y3/zi/rSoGTKIOz57KPe8toy7X1vGHS8tZczQQZxVN5Kz66p8XG3nXNolkijmE4w/Ud/Vii45jp5QwdETKtiyo5knF6zmkdmr+MWzb/OzZ95mysgyzqkbyRlTqxhRXpzpUJ1z/YC6KiiEo9rVAa8BO9uWm9lZqQ2t56ZNm2YzZ87MdBhJtbahielz63lk9krmrNiCBIePHco5B1ZxyuRKygcVZhg2yGIAABaSSURBVDpE51wOkzTLzKZ1+FoCieKYjpab2fNJiC0l+mKiiLV43VYembOKh2evYsn6bQzIz+PYiRWcc+BIjp+0N8WF+ZkO0TmXY3qVKDrY2RHABWZ2eTKCS4W+nijamBnzVm7h4dmrmD5nFWsbd1JSVMCHJ4/gnAOr+Ld9hvolts65hPQ6UUiqAy4AziMYN/sBM/tFUqNMov6SKGK1Ro1XFm/g4dkreXzeahp3tjCspMivnHLOJaRHiULSBOB84JPABuBPwNfMbHSqAk2W/pgoYjU1t/Lcm2t5ePYqnlm0ll0tUUYPHcTZtVWcfeBIv3LKOfcBPU0UUeBF4FIzeydcttjMktp1Ryr090QRq6GpmSfmB1dOvfTueqIGU0aWcXbtSM6s9SunnHOBniaKjxCUKD4EPAHcC/wuF7r08ETRsc6unDq7ropTp/iVU871Z7296mkv4ByCKqjjgTuBB83sqWQHmiyeKLq2ZP02Hp698gNXTp1dN5IT9vMrp5zrb5J21VPYvfi5wCfM7PgkxZd0nigSZ2bMX9nAQ7NXdnjl1BHjhpGX543gzvV1Sb08Nhd4ouiZ1qjx6uINPDR7JY/PX01jUwv7VOzFJUeM5WMHVTNwgJcynOurPFG4bmtqbuXJBau5dcYS5q7YQmRQIRccOoqLPjSG4WXeAO5cX+OJwvWYmTHzvU3c+uISnnxjNQV54oypVVx65FimjCzPdHjOuSSJlygS6RTQ9WOSOGTMEA4ZM4RlG7Zz+0tLuO+fy3nwXys5bOwQLj1yLCfsN5x8b8dwadQaNW7/xxLueGkpVZGB7F9ZxuSqMvavKmPfvYMhhV3yZE2JQtJtwBnAWjObEi4bQnCj3xhgKXCemW3qal9eokithqZm/vTacu54aSkrN+9g9NBBXHLEWD5+cDV7FflvD5daS9Zv4+t/nsPM9zZx6JghtESjLKxvZEdzMFzOgPw89h1esjt5TB5ZzqQRpZQW++Xf8eRE1ZOko4GtwO9jEsUPgY1mdoOka4DBZnZ1V/vyRJEeLa1Rnlywht/NWMy/lm2mrLiAT4btGFWRgZkOz/Ux0ahx58tLufGJRQzIz+O6Myfz0YNGIonWqLF0wzYWrGpgwaotvLGqgTdWNbBh267d248ZOoj9q8qYXFUePFaWsbe3t+2WE4kCQNIY4NGYRPEmcKyZ1UuqBJ4zs4ld7ccTRfq9vmwTt85YwhPzVwNw2gGVXHrkWOpqIhmOzPUFyzZs52v3z+G1JRs5bmIFP/jo1C57FTAz1jbuZMGqLSxY2cAb9Q0sWNXAso3bd68zrKQoTB5h1VVlGWOG7tUvLwnP5USx2cwiMa9vMrPBXe3HE0XmrNi0nTtfWsq9ry2ncWcLB48ezKVHjuXk/Yd7T7a90NwaZcn6bby5upF9h5cwaURZpkNKi2jUuOvV9/jB44vIl/j2mftz7sHVvergsqGpmYWr9iSOBasaeHtNIy3R4Fw4aEA++1XGJo9yJowooaigb18e3i8ShaTLgMsARo0adfB7772X+oBdp7bubOG+fy7n9peWsHzjDqoHD+TiD43hE4fUeF1xF9Zv3cnC+gYW1TeycHXw+M7arexqjQIgwdm1VVx18kRqhgzKcLSps3zjdq5+YC4vvbuBo/Ydxo0fm5qyKs2dLa28vWYrb9QHVVYLVm1hYX0jW3e2AFCQJ8bvXcL+YamjrfqqfGDf+S7ncqLwqqcc1xo1nn5jDbfNWMJrSzdSUlTAJw6p4eIPjenTJ7lE7Gxp5Z21W1lU38ii1Q0sWt3IwvpG1m/dPZAke5cWMamyjP1GlDKpspRxFSU8Pn81t/9jCa1R41OHjeaK48cztKQog39JcpkZd7+2jP/560Ik8a3T9+P8Q2rS3k1+NGos27g9LHlsYUHY7rG2cc/nUz14IJOrytinooSigjwK8/MozFf42Pl8Qb4YkMB8YX4eA/Lz0lIVlsuJ4kfAhpjG7CFm9o2u9uOJIjvNXbGZW2cs4a9z64ma8eHJI/jcUWM5aNTgPj1WhpmxuqHpfSWERasbeHfdNlrD6o4BBXlMHF7KpBGluxPDxBGlnSaA1Vua+Okzb/Gnfy5n0IACLjt6Hy49cmzOX3W2cvMOrnlgLi++vZ4jxg/lxo9NpXpwdv2gWNe4c3fyaGs0X7Zx++6qq1TIE7uTRkGcRDS8rJhbLuzwXN+lnEgUku4BjgWGAWuA64CHgPuAUcAy4Fwz29jVvjxRZLf6LTu486X3uOe1ZWzZ0UxtTYRLjxzLqVNGUJjj7Rjbd7Xw1pqtLKpvKyEEj1t2NO9eZ2RkIPtVljJpRBmTwscxQwf1qA3nnbVbuenJN3liwWqGlRRx5QnjOf/QUTn3PpoZ981czvceXUjUjGtP249PHTYqp35ARKNGczRKS6vR3BplV+ue+WDqeH5Xi9ESDZe3BPtobgnXiYbLWqPvm2+JBtu1319kUCE/Pf/AHsWfE4kimTxR5Ibtu1p4YNYKbvvHUpas30ZleTEXf2gM5x86KuvrfqNRY8WmHe8rISxa3cjSDdto+5caNCD/fSWESZVlTBhempK/7fVlm7jh8UW8tmQjo4cO4msnT+T0Aypz4uqd+i07uOaBeTz/1joO32cIP/p4bb+vlswETxQuq0WjxrOL1nLrjCW8vHgDgwbkc+7B1Xz2iLGMGbZXSo9tZuxqjbKzJcrO5uBX4M7mVna2RNnVEi5vaWVXS5RVm3ewcHUji+obeHN1I9t2BTd4STB6yKD3lRD2qyylZvCgtJ6ozYzn3lzHjU8sYtHqRqaMLOOaU/bjyH2HpS2G7jAzHnh9Jd+ZvoCWVuOaUyfxmcNH50Ry64s8UbicsWDVFm6dsYTpc1bREjVO3G84Z9VWIcHO5mh4Am8NT+BtJ/PW95/oW1pjTvp7Xt9z4n//su4oKy54Xwlh0ohSJgwvzaq2gdao8fDsldz81Fus3LyDo/YdxtWnTMqqvrnWNDRx7V/m8cyitRwyZjA/+nhtyn8UuPg8Ubics7ahiT+88h5/fOU9Nm1v7nS9PEFRQT5FhUFDX1FhHkUF+THzeQwoyKeoIC+c8hnQNl+YR1F+HkWF+eF6HawTs+9hpUVUlRfnTL15U3Mrf3zlPX7593fYtL2ZM2ur+NrJExg9NHMnZDPj4dmruO6RBTQ1t/KNUybx2Q+N8VJEFvBE4XJWU3NwCWnbiXtA28k7nC/IU86cuDOloamZW55fzK0zltDcGuWCw0ZxxfH7UlGa3ktq1zXu5FsPzuOpN9Zw0KgIN51byz4VJWmNwXXOE4VzjrUNTfz0mbe595/LKSrI43NH7cNlR+9DSYqrzcyMR+fW818Pz2fbrla+dvIELj1yH+9xOMt4onDO7bZ43VZufuot/jqvnqF7DeCK48dzwWGjU9I194atO/n2w/N5bN5qamsi3HzuVMbvXZr047je80ThnPuA2cs3c+Pji3h58QZqhgzkaydP5MypVUlrL3h8Xj3/+dB8Gpta+I+TJvD5o8Z6f19ZzBOFc65DZsYLb6/nhscXsbC+gf0ry7j61Ekcve+wHrf9bNy2i/96eD6Pzq3ngJHl3HxeLROGeyki23micM7FFY0a0+eu4qan3mT5xh18aNxQrj5lErXd7Cb+yQWr+daD89iyo5krT9iXLxwzLufuEu+vPFE45xKyqyXK3a++x8+efYeN23Zx+gGVXHXyhC6vTtq8fRfXP7KAh2avYv/KMm4+r5b9KvtHV+h9hScK51y3NDY189sXl/C7FxezsyXK+YfUcOUJ+3Y4ItwzC9dwzV/msWnbLr58/HguP268lyJykCcK51yPrGvcyc+ffZu7X11GYX4elx45lsuO2Yey4kK27Gjmu9Pf4IHXVzBpRCk3nVubVXd/u+7xROGc65Wl67dx89NvMX3OKgYPKuSTh47iL6+vZN3Wnfz7seO44vh9U3J5rUsfTxTOuaSYt2ILP3xyES++vZ599y7h5vNqmVrt46L3BfESRfb0ZOacy3oHVJfzh0sP483VjYwZNqjPjyPtAp4onHPdNnGE3xfRn3ilonPOubg8UTjnnIvLE4Vzzrm4cqKNQtJSoBFoBVo6a5l3zjmXfDmRKELHmdn6TAfhnHP9jVc9OeeciytXEoUBT0maJemyjlaQdJmkmZJmrlu3Ls3hOedc35UTd2ZLqjKzVZL2Bp4GrjCzF+Ksvw54r4eHGwZkQxVXNsSRDTGAx9Gex5FdMUDfiGO0mVV09EJOJIpYkq4HtprZTSna/8xsaCzPhjiyIQaPw+PI9hj6QxxZX/UkaS9JpW3zwMnA/MxG5Zxz/UcuXPU0HHgwHJaxALjbzJ7IbEjOOdd/ZH2iMLPFQG0aD3lLGo8VTzbEkQ0xgMfRnsexRzbEAH08jpxro3DOOZdeWd9G4ZxzLrP6XaJQ2NjhAtnyfmRLHM5lu0z8r/S7RAEUZjqANpKyYdSXbPkOZMXnImlY+JjRz0bSmEweP4xhWnjvUqbjOFHSwVkQR3nMfCZ/2KS9bTlbThIpJ+nfJP0ZuEnS/pk6EYRxfBfAzFozEUMYx6GS/gj8QNIBkjLyXQhPRn8GfiTpyEx8LgoMknQP8DBk7rORdJCkvwHfzeB3dLKkl4DrgIyNcyrpQEmPAw8C4zMYx2GSHgZ+J+kSSUWWgcZdSYdLuovgu7FvOr8f/SJRhL+KfgE8RnDX4pXAJeFraftlIOki4E7gPyWdFy5L668DSXmSrgN+BzxO8OvkctJ7ZVnbyfkG4NfAo8Aa4MvAqHTGAWCB7eHTYZK+FMaYtv+P8P34FnAPcK+ZXdiWrDLw6/VK4EEzO9PM3kp3DJLyJd0C/Bb4DXA3sF/4WlrPWZKmAr8E7gf+DBxPBpKWpCnAz9nzv3IZcGH4Wso/m36RKAhOgm+Z2e3AzcBfgLMlTTAzS+M/wUqCL9opYRyYWUs6/wnNLAqsAC42s7uA7wOjgbT+eg1/kb0InGRmdwK3E/TplfaOuiQVSKok+Ae8FPiSpIiZRdN1Ygrfj2Jghpn9LozrQEkF6fz1Gla9GcEPKyR9RFI1MDB8nvLvapggnwaOMrOHgAeA4yQVh9/fdDoUeMfM/hDGVAwsa3sxjf+7RwCLzOweggS6HfiUpDHpOIf1yctjJX0SmATMMrNHwi//y8ApZvaupCHAV4BSM7sqDXG8bmYPhyedvDA5zAD+bmbfllRoZs0pjmM/YGb4fgwEdgKFZrZT0n3AH8xseqpiiIlj9/sRs/wo4I/AKuBV4K9m9nQa4pgZ+zeH1QuXA1cD24Dfmtm7aYjjX2b2kKQSgl+uC4CjCRLXFoJf9/enOIaZZjY9/G7MAr4OfJKg76DVwC4z67BDziTGsfs7GrNcwAnAJ4CrzWxjqmKIiSP2f3Y4QWK4CbiI4EfWQoKT9o1piKPtHFYH/C/weTN7J6wVmBrG8a1UxbGbmfWZCRDwReBfwGeBN4HPEfwK+Dbws3C9POBI4FdAZZri+CxBYmpbZzLBSWB4Gt+PtzqIoxB4CZiQ5s9ldxzAAQTjjRAuvx2YlMY49iIoVf0kXO8soAF4HSgiSKipjuPz4WsfB54Fjg6ff4GgmjCpn08XMXyV4OT4mfD5yPA7cmoaP5OSmHWqgcVAVds2aYrjsvC1scAPgQvD58cA04F/S0McbxEkqOHA9whK4Q+Fxz8fuBEoTnYcH4gr1QdI90TQBvCJcP5Egl+qpwMHE7RRnBi+th/wCDAojXGcFvslD08At4fzSf8nTCQOgmq5B8P5UuDQNH8uee3W24eg8bI6TXHcRVAVWEbQkD09PElMb3tf0hTH3cCHw+eRmPXGhXFVpSmGtvdiFXBVzLo/bIsv3d/RcPk9wFdS9XnE+W6cGj7/C3B8OF8C3AoclMb3o+27MRn4SDg/DXg8le9J25TzbRSSLpR0TFidBEGxcGRYt/s3gg4EDyeo+74b+Imk8QTFWQED0hTHPIJSTHXbNmb2OeAiSZuA2mTUh3cjjtHh60OA7ZIuJvjVeEAy6jsTjOMIoKrdpicTlPgaextDgnHMJXg/JhC0IS0GDjazM4EaJemyzATimAMcK6nGzDbHbHoSQZvB1jTEMBc4FtgFXEHw3awLG/dPBJb2NoYE43jf/4qkQuBtgurApEn0/QgvhnkSuC783zif4IS9IU1xzCNoo6k2swVm9mC43vHAK+loJ8n6vp46Er4xIwhO/FHgXWCv8Au9nKAqYzywCLiXoG5vqJn9UVINcA1B/d/n2/1TpjKOP7XFASyXtA9BveeLwOVm1uMecXsYx2CCf/xTCeqidwKfMrO5aY5jGLBC0ocJGtZXAd8wsy1piuM+ggsL/gx81cx2xezqhDTG0f77cVwY13KCuvmGNMRwL/ATYH8ze0BSEXAewUnxM2b2Zk9i6EEcsd+N5WbWHLbfjOnp8XsZR5WZ/UbSMey5UvASM+vpmDe9/V85lKDKKUpQPZb6huZ0FFuSXCzLDx8nAH8M5wuA/yMoshUCtwGfAcrD1+8Avh+zjwEZjOO74Xw5Sajm6UUc/x3OH0FYzM1QHN8J56cCZ2QojjtjPhfRrjosQ9+P8cBZmfxutL0fmf5uZDiOO4HvhfOFwIgs+G4MA47pbRzdmXKmRKHgfoPvAvmSHiOoR22F3ZeYfhmoB/YnyNLnEBRdf0CQeV9q25e9/1djuuN4NVx3C/BaBuN4OVz3Hz2NIUlxvBauO5egqJ+JOFrZ87kYQVVPJuKI/X68A7yToRhebttX+H70SLK+GxmOoxV4JVy3meAKsEzEEfvdWA8839M4eiIn2ijCIt8sguqSdwha/5sJ6u0Ohd33B3wXuNGCer1bgCMlvRpu95zH4XH09TiyIQaPI3vj6LF0Fl96UVQ7ivBSvfD5/wFfAi4muM4YgqQ3gqCueUy4LAKM9Dg8jv4SRzbE4HFkbxw9nXKiREGQie/Tnr5N/gGMMrM7CIpxV1iQjauBFjNbCmBmm81spcfhcfSjOLIhBo8je+PokZxIFGa23cx22p6O2k5iT1cPnwX2k/QowbXWr3scHkd/jSMbYvA4sjeOHst0kaY7E0F/RHkEl6iND5eNJyieHUmaimgeh8eR7XFkQwweR/bG0d0pJ0oUMaIEl46tB6aGGfjbQNTMZlj6imgeh8eR7XFkQwweR/bG0T2ZzlQ9yMiHE7zZM4BLPQ6Pw+PI3hg8juyNoztTzvUeq6DL488APzaznR6Hx+FxZG8MHkf2xtEdOZconHPOpVeutVE455xLM08Uzjnn4vJE4ZxzLi5PFM455+LyROGccy4uTxTO9ZKkiKR/D+erJN2f6ZicSya/PNa5XpI0BnjUzKZkOBTnUiJnBi5yLovdAIyTNJtgbOf9zGyKgnHIzyHo32cKwdCmAwhuttoJnGZmGyWNA34JVADbCYboXZT+P8O5jnnVk3O9dw3wrpnVAV9v99oU4ALgUIIxwbeb2YEEo8hdGK5zC3CFmR0MfI1grALnsoaXKJxLrb+bWSPQKGkLMD1cPo+gU7gS4EPAnyW1bVOU/jCd65wnCudSK7Yvn2jM8yjB/18esDksjTiXlbzqybneawRKe7KhmTUASySdC6BAbTKDc663PFE410tmtgH4h6T5wI96sItPAZdKmgMsAM5OZnzO9ZZfHuuccy4uL1E455yLyxOFc865uDxROOeci8sThXPOubg8UTjnnIvLE4Vzzrm4PFE455yLyxOFc865uP4/H5yqDoOcyuoAAAAASUVORK5CYII=\n", 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" ] @@ -220,7 +214,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -234,21 +228,21 @@ " ----------\n", " da : ComplexData:mimetype:`application/x-netcdf`\n", " NetCDF Files or archive (tar/zip) containing netCDF files.\n", - " variable : //www.w3.org/TR/xmlschema-2/#string\n", + " variable : string\n", " Name of variable to analyze in netCDF file.\n", - " mode : {'min', 'max'}//www.w3.org/TR/xmlschema-2/#string\n", + " mode : {'min', 'max'}string\n", " Mode\n", - " t : //www.w3.org/TR/xmlschema-2/#integer\n", + " t : integer\n", " Return period\n", - " dist : //www.w3.org/TR/xmlschema-2/#string\n", + " dist : string\n", " Distribution\n", - " window : //www.w3.org/TR/xmlschema-2/#integer\n", + " window : integer\n", " Window size\n", - " freq : {'YS', 'MS', 'QS-DEC', 'AS-JUL'}//www.w3.org/TR/xmlschema-2/#string\n", + " freq : {'YS', 'MS', 'QS-DEC', 'AS-JUL'}string\n", " Resampling frequency\n", - " season : {'DJF', 'MAM', 'JJA', 'SON'}//www.w3.org/TR/xmlschema-2/#string\n", + " season : {'DJF', 'MAM', 'JJA', 'SON'}string\n", " Season selection specification.\n", - " month : {'1', '2', '3', '4', '5', '6', '7', '8', '9', '10', ...}//www.w3.org/TR/xmlschema-2/#string\n", + " month : {'range(1, 13)'}string\n", " Month selection specification\n", " \n", " Returns\n", @@ -274,7 +268,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -283,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -305,10 +299,10 @@ " standard_name: discharge\n", " cell_methods: \n", " mode: min\n", - " history: [2019-07-26 11:04:10] freq_analysis: freq_analysis(da, mo..." + " history: [2019-10-29 13:56:36] freq_analysis: freq_analysis(da, mo..." ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -327,22 +321,22 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -370,7 +364,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -386,7 +380,7 @@ "Attributes:\n", " units: \n", " long_name: gumbel_r distribution parameters\n", - " history: [2019-07-26 11:04:16] ts_stats: ts_stats(da, op, freq='YS...\n", + " history: [2019-10-29 13:56:37] ts_stats: ts_stats(da, op, freq='YS...\n", " cell_methods: time: fit\n", " standard_name: gumbel_r parameters\n", " description: Parameters of the gumbel_r distribution fitted \n", @@ -395,7 +389,7 @@ " scipy_dist: gumbel_r" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -419,7 +413,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -429,22 +423,15 @@ "" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "resp = wps.graph_fit(ts, pa_fn)\n", + "resp = wps.graph_fit(ts=ts, params=pa_fn)\n", "resp.get(asobj=True)[0]" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -463,7 +450,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/watershed_subset.ipynb b/docs/source/notebooks/watershed_subset.ipynb index 20988759..971ab091 100644 --- a/docs/source/notebooks/watershed_subset.ipynb +++ b/docs/source/notebooks/watershed_subset.ipynb @@ -13,20 +13,7 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "birdy: 0.6.2 \n", - "json: 2.0.9 \n", - "xarray: 0.12.1 \n", - "requests: 2.21.0 \n", - "matplotlib: 3.0.2 \n", - "geopandas: 0.4.0\n" - ] - } - ], + "outputs": [], "source": [ "# Import the necessary libraries to format, send, and parse our returned results\n", "\n", @@ -39,16 +26,8 @@ "import matplotlib\n", "import matplotlib.pyplot as plt\n", "import geopandas as gpd\n", - "\n", - "\n", - "print(\n", - " 'birdy:', birdy.__version__, '\\n'\n", - " 'json:', json.__version__, '\\n'\n", - " 'xarray:', xr.__version__, '\\n'\n", - " 'requests:', requests.__version__, '\\n'\n", - " 'matplotlib:', matplotlib.__version__, '\\n'\n", - " 'geopandas:', gpd.__version__\n", - ")" + "from example_data import TESTDATA\n", + "import os\n" ] }, { @@ -65,58 +44,15 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [ - { - "ename": "ConnectionError", - "evalue": "HTTPConnectionPool(host='localhost', port=8093): Max retries exceeded with url: /wps?service=WPS&request=GetCapabilities&version=1.0.0 (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused',))", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mConnectionRefusedError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 158\u001b[0m conn = connection.create_connection(\n\u001b[0;32m--> 159\u001b[0;31m (self._dns_host, self.port), self.timeout, **extra_kw)\n\u001b[0m\u001b[1;32m 160\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0merr\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 80\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 81\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m 69\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource_address\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msa\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 71\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mConnectionRefusedError\u001b[0m: [Errno 111] Connection refused", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mNewConnectionError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m 599\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 600\u001b[0;31m chunked=chunked)\n\u001b[0m\u001b[1;32m 601\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m 353\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 354\u001b[0;31m \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mhttplib_request_kw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 355\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/http/client.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m 1238\u001b[0m \u001b[0;34m\"\"\"Send a complete request to the server.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1239\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1240\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/http/client.py\u001b[0m in \u001b[0;36m_send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m 1284\u001b[0m \u001b[0mbody\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_encode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m 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"\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/connection.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 180\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m \u001b[0mconn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_new_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 182\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_prepare_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 167\u001b[0m raise NewConnectionError(\n\u001b[0;32m--> 168\u001b[0;31m self, \"Failed to establish a new connection: %s\" % e)\n\u001b[0m\u001b[1;32m 169\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNewConnectionError\u001b[0m: : Failed to establish a new connection: [Errno 111] Connection refused", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mMaxRetryError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/requests/adapters.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m 448\u001b[0m \u001b[0mretries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax_retries\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 450\u001b[0m )\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m 637\u001b[0m retries = retries.increment(method, url, error=e, _pool=self,\n\u001b[0;32m--> 638\u001b[0;31m _stacktrace=sys.exc_info()[2])\n\u001b[0m\u001b[1;32m 639\u001b[0m \u001b[0mretries\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/urllib3/util/retry.py\u001b[0m in \u001b[0;36mincrement\u001b[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[1;32m 397\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnew_retry\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_exhausted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 398\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mMaxRetryError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_pool\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merror\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mResponseError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 399\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mMaxRetryError\u001b[0m: HTTPConnectionPool(host='localhost', port=8093): Max retries exceeded with url: /wps?service=WPS&request=GetCapabilities&version=1.0.0 (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused',))", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mConnectionError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mraven\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbirdy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mWPSClient\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl_raven\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprogress\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mfp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbirdy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mWPSClient\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl_flyingpigeon\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 87\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m\"AccessForbidden\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/owslib/wps.py\u001b[0m in \u001b[0;36mgetcapabilities\u001b[0;34m(self, xml)\u001b[0m\n\u001b[1;32m 262\u001b[0m self._capabilities = reader.readFromUrl(\n\u001b[1;32m 263\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0musername\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0musername\u001b[0m\u001b[0;34m,\u001b[0m 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}\n\u001b[1;32m 532\u001b[0m \u001b[0msend_kwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msettings\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 533\u001b[0;31m \u001b[0mresp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0msend_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 534\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 535\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mresp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/raven-dev/lib/python3.6/site-packages/requests/sessions.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m 644\u001b[0m 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/wps?service=WPS&request=GetCapabilities&version=1.0.0 (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused',))" - ] - } - ], + "outputs": [], "source": [ - "url_raven = \"http://localhost:9099/wps\"\n", - "url_flyingpigeon = \"http://localhost:8093/wps\"\n", + "# url_raven = \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\"\n", + "url_flyingpigeon = os.environ.get(\"FLYINGPIGEON_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/flyingpigeon/wps\")\n", "\n", - "raven = birdy.WPSClient(url_raven, progress=True)\n", - "fp = birdy.WPSClient(url_flyingpigeon, progress=True)" + "url_raven = os.environ.get(\"RAVEN_WPS_URL\", \"https://pavics.ouranos.ca/twitcher/ows/proxy/raven/wps\")\n", + "\n", + "raven = birdy.WPSClient(url_raven) #, progress=True)\n", + "fp = birdy.WPSClient(url_flyingpigeon) # , progress=True)" ] }, { @@ -130,24 +66,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "7e19176570a74532a37f21cc6c369cb2", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Processing:'), Button(button_style='danger'…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "basin_process = raven.hydrobasins_select(\n", " location=\"-73.621, 51.000\", aggregate_upstream=True)\n", @@ -157,22 +78,22 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -186,24 +107,16 @@ "source": [ "# Collecting the response\n", "\n", - "url = basin_process.get(asobj=False)\n", - "\n", - "feature = requests.get(url[0]).content\n", - "upstream_ids = json.loads(requests.get(url[1]).content)\n", - "\n", - "# Write our feature to a GeoJSON\n", - "file_name = \"mistassini.geojson\"\n", - "with open(file_name, \"wb\") as f:\n", - " f.write(feature)\n", + "feature, upstream_ids = basin_process.get(asobj=True)\n", "\n", "# Plot our vector shapefile\n", - "df = gpd.read_file(file_name)\n", + "df = gpd.GeoDataFrame.from_features([feature])\n", "df.plot()" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -554,36 +467,25 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "792e6628edea4ae0a8cfacfe1164c16c", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Processing:'), Button(button_style='danger'…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ + "# NBVAL_SKIP\n", + "\n", + "# *FlyingPigeon deployed in PAVICS does not have `subset_wfs_polygon` installed*\n", + "\n", "# Address of the GeoServer where the HydroBASINS data is pulled from\n", "geoserver = \"https://boreas.ouranos.ca/geoserver/wfs\"\n", "\n", "# A local address of a NetCDF file\n", - "nc1 = \"/home/tjs/Desktop/tas/tas_Amon_CanESM2_rcp85_r1i1p1_200601-210012.nc\"\n", + "# A link to a remote file or the path to a local file. \n", + "nc1 = str(TESTDATA[\"cmip5_subset\"])\n", "\n", "# The first sub-basin where our point was taken\n", "primary_basin = upstream_ids[0]\n", "\n", - "\n", - "x = fp.subset_wfs_polygon(\n", + "resp = fp.subset_wfs_polygon(\n", " resource=nc1,\n", " typename=\"public:USGS_HydroBASINS_lake_na_lev12\", # The store and name of the data set \n", " geoserver=geoserver, # The address of the GeoServer\n", @@ -594,36 +496,22 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# Collecting the file\n", - "\n", - "file_url, meta = x.get(asobj=False)\n", - "response = requests.get(file_url).content\n", - "with open('mistassini.nc', 'wb') as f:\n", - " f.write(response)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 21, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -635,18 +523,12 @@ } ], "source": [ - "# Open with xarray and plot with matplotlib\n", + "# NBVAL_SKIP\n", "\n", - "ds = xr.open_dataset('mistassini.nc')\n", + "# Collecting the file\n", + "ds, meta = resp.get(asobj=True)\n", "plt.plot(ds.tas)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -665,7 +547,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/docs/source/output_sanitize.cfg b/docs/source/output_sanitize.cfg new file mode 100644 index 00000000..d3794b54 --- /dev/null +++ b/docs/source/output_sanitize.cfg @@ -0,0 +1,51 @@ +[regex1] +regex: \/.+\/envs\/birdy\/lib\/python\d+\.\d+\/site-packages +replace: PYTHON_SITE_PACKAGES + +[regex2] +regex: \/[a-z0-9]{8}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{12} +replace: /STATUS_FILE + +[regex3] +regex: \d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}Z +replace: DATE_TIME_TZ + +[regex4] +regex: \[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\] +replace: [DATE_TIME] + +[regex5] +regex: [\/| ]\d{4}-\d{2}-\d{2}[\/| ] +replace: /DATE/ + +[regex6] +regex: [\/| ]\d{2}:\d{2}:\d{2}[\/| ] +replace: /TIME/ + +[regex7] +regex: nc_dump_[a-zA-Z0-9_]+.txt +replace: NC_DUMP_TXT + +[regex8] +regex: __[a-zA-Z0-9_]{6}.json +replace: __RANDOM_JSON_FILE_SUFFIX + +[regex9] +regex: +replace: 0xOBJECT_HASH> + +[regex11] +regex: pywps_process_[a-z0-9_]{8} +replace: PYWPS_PROCESS_CODE + +[regex12] +regex: \/\/www\.w3\.org\/TR\/xmlschema-2\/#[a-z]+ +replace: W3_DATA_TYPE + +[regex13] +regex: \/home/[a-zA-Z0-9_]+\/[.]?[a-zA-Z0-9_]+\/ +replace: /home/USERNAME/ANACONDA_LOCATION/ diff --git a/environment.yml b/environment.yml index c7d9319a..5febf9ec 100644 --- a/environment.yml +++ b/environment.yml @@ -4,14 +4,20 @@ channels: - defaults dependencies: - pip -- pywps>=4.2 +- six +- pywps>=4.2.3 - unidecode -- owslib>=0.17 +- birdy +- owslib>=0.18 - poppler - jinja2 - click - psutil +- numpy +- scipy<1.3 - xarray==0.13 +- xclim>=0.11 +- matplotlib - dask - pandas - geopandas @@ -21,17 +27,17 @@ dependencies: - gdal~=2.4 - fiona - pyproj +- descartes +- cartopy - affine - rasterio - rasterstats - rtree - shapely - bump2version -- scipy<1.3 - statsmodels -- matplotlib -- xclim>=0.11 - pandoc +- nbval - ipyleaflet - pysheds - psycopg2 diff --git a/raven/__init__.py b/raven/__init__.py index 18cfcda5..648fc90f 100644 --- a/raven/__init__.py +++ b/raven/__init__.py @@ -9,7 +9,7 @@ __author__ = """David Huard""" __email__ = 'huard.david@ouranos.ca' -__version__ = '0.8.2-beta' +__version__ = '0.8.3-beta' if 'DO_NOT_CHECK_EXECUTABLE_EXISTENCE' not in os.environ: raven_exec = Path(__file__).parent.parent / 'bin' / 'raven' diff --git a/raven/processes/wps_graph_fit.py b/raven/processes/wps_graph_fit.py index cab9b54c..db45404d 100644 --- a/raven/processes/wps_graph_fit.py +++ b/raven/processes/wps_graph_fit.py @@ -21,16 +21,18 @@ def __init__(self): abstract='Statistical distribution parameters fitted to time series', supported_formats=[FORMATS.NETCDF]), LiteralInput('variable', "Variable name", - abstract="Name of time series variable. If none will default to the first data variable" + abstract="Name of time series variable. If none will default to the first data variable " "found in file.", data_type='string', min_occurs=0, - default=""), + max_occurs=1 + ), LiteralInput('format', "Output graphic format", abstract="Graphic format.", data_type='string', default='png', min_occurs=0, + max_occurs=1, allowed_values=['png', 'jpeg', 'pdf']) ] @@ -60,15 +62,18 @@ def __init__(self): store_supported=True) def _handler(self, request, response): + print(request.inputs) ts_fn = request.inputs['ts'][0].file p_fn = request.inputs['params'][0].file - v = request.inputs['variable'][0].data + v = request.inputs['variable'][0].data if 'variable' in request.inputs else None format = request.inputs['format'][0].data # Create and save graphics ds = xr.open_dataset(ts_fn) - if v == '': + + if v is None: v = list(ds.data_vars.keys())[0] + ts = ds[v] p = xr.open_dataset(p_fn)['params'] # Name of variable is hard-coded diff --git a/raven/processes/wps_hydrobasins_shape_selection.py b/raven/processes/wps_hydrobasins_shape_selection.py index 1ee6a908..65c2652d 100644 --- a/raven/processes/wps_hydrobasins_shape_selection.py +++ b/raven/processes/wps_hydrobasins_shape_selection.py @@ -143,8 +143,10 @@ def _handler(self, request, response): gdf = gpd.read_file(upfile) agg = gis.hydrobasins_aggregate(gdf) - feat = json.loads(agg.to_json())['features'][0] - response.outputs['feature'].data = json.dumps(feat) + # The aggregation returns a FeatureCollection with one feature. We select the first feature so that the + # output is a Feature whether aggregate is True or False. + afeat = json.loads(agg.to_json())['features'][0] + response.outputs['feature'].data = json.dumps(afeat) response.outputs['upstream_ids'].data = json.dumps(up['id'].tolist()) else: diff --git a/requirements.txt b/requirements.txt index 3d769cd5..30c40cb1 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,6 @@ six -pywps>=4.2 -owslib>=0.17 +pywps>=4.2.3 +owslib>=0.18 lxml jinja2 click @@ -13,17 +13,17 @@ pandas requests netCDF4 dask -pathlib toolz spotpy statsmodels # GIS LIBRARIES # pycrs --- Depends on online database requests --> SLOW -gdal~=2.4 +gdal>=2.4 pysheds affine rtree fiona +descartes geopandas pyproj rasterio @@ -32,7 +32,8 @@ shapely unidecode geojson pandoc +ipython +ipyleaflet ipython # needed for the parsing of Jupyter Notebooks psycopg2 # to use postgres to log pywps requests like in Prod # xclim It seems to be installed by pip in src/ and confuse pytest. - diff --git a/requirements_dev.txt b/requirements_dev.txt index b95d3060..706310bd 100644 --- a/requirements_dev.txt +++ b/requirements_dev.txt @@ -1,10 +1,10 @@ -r requirements.txt pytest pytest-dependency +pytest-notebook flake8 bump2version sphinx>=1.7 sphinx-autoapi nbsphinx - - +nbval diff --git a/setup.cfg b/setup.cfg index 605a48ce..80a62dd3 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 0.8.2-beta +current_version = 0.8.3-beta commit = False tag = False parse = (?P\d+)\.(?P\d+).(?P\d+)(\-(?P[a-z]+))? diff --git a/tests/test_wps_graph_fit.py b/tests/test_wps_graph_fit.py index 33958b4f..f5e581fe 100644 --- a/tests/test_wps_graph_fit.py +++ b/tests/test_wps_graph_fit.py @@ -10,7 +10,6 @@ def test_graph_fit(ts_stats, params): datainputs = "ts=files@xlink:href=file://{ts};" \ "params=files@xlink:href=file://{params};" \ - "format={format}" \ .format(ts=ts_stats, params=params, format='png') resp = client.get( diff --git a/tests/test_wps_hydrobasins_shape_selection.py b/tests/test_wps_hydrobasins_shape_selection.py index 87718db4..50ef3cec 100644 --- a/tests/test_wps_hydrobasins_shape_selection.py +++ b/tests/test_wps_hydrobasins_shape_selection.py @@ -1,6 +1,7 @@ from pywps import Service from pywps.tests import assert_response_success from .common import client_for, CFG_FILE, get_output +import json from raven.processes import HydroBasinsSelectionProcess @@ -71,6 +72,9 @@ def test_lac_saint_jean(self): assert {'feature', 'upstream_ids'}.issubset([*out_upstream]) assert {'feature', 'upstream_ids'}.issubset([*out_subbasin]) + assert json.loads(out_subbasin['feature'])['type'] == 'Feature' + assert json.loads(out_upstream['feature'])['type'] == 'Feature' + def test_smallwood_reservoir(self): client = client_for(Service(processes=[HydroBasinsSelectionProcess(), ], cfgfiles=CFG_FILE)) diff --git a/tests/testdata/cmip5/tas_Amon_CanESM2_rcp85_r1i1p1_200601-210012_subset.nc b/tests/testdata/cmip5/tas_Amon_CanESM2_rcp85_r1i1p1_200601-210012_subset.nc new file mode 100644 index 00000000..eed87af5 Binary files /dev/null and b/tests/testdata/cmip5/tas_Amon_CanESM2_rcp85_r1i1p1_200601-210012_subset.nc differ