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Temp fix for relative import error #72

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Temp fix for relative import error #72

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b2005ac
Temp fix for relative import error
Nov 24, 2023
070eca7
Merge branch 'main' into temp-import-fix
anirudh1666 Dec 21, 2023
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95 changes: 62 additions & 33 deletions demos/demo_ippm.ipynb
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239 changes: 109 additions & 130 deletions demos/demo_plotting.ipynb
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164 changes: 101 additions & 63 deletions demos/demo_save_load.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -3,15 +3,42 @@
{
"cell_type": "code",
"execution_count": 1,
"id": "19b809df-7acd-402b-8f05-d44a68910a79",
"metadata": {},
"outputs": [],
"source": [
"# temporary fix for relative import errors. essentially, the notebook is unable to discern that \n",
"# the kymata directory is in the parent directory. It thinks it is in the current one.\n",
"# SOLUTION: update the PATH variable to point to the parent directory, from which it can locate kymata/.\n",
"\n",
"import sys\n",
"sys.path.insert(1, '..')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "initial_id",
"metadata": {
"collapsed": true,
"ExecuteTime": {
"end_time": "2023-11-24T15:03:28.701768Z",
"start_time": "2023-11-24T15:03:27.973888Z"
}
},
"outputs": [],
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'numpy'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[2], line 6\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtempfile\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m NamedTemporaryFile\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkymata\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdatasets\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msample\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_dataset_kymata_mirror_q3_2023, get_dataset_gm_loudness, \\\n\u001b[1;32m 5\u001b[0m get_dataset_d_ins_loudness_tonop_chan1\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkymata\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mentities\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexpression\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ExpressionSet\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkymata\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mio\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmatlab\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m load_matab_expression_files\n",
"File \u001b[0;32m~/Desktop/kymata/kymata-toolbox/demos/../kymata/entities/expression.py:13\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mwarnings\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m warn\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mzipfile\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ZipFile, ZIP_LZMA\n\u001b[0;32m---> 13\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m int_, float_, str_, array, array_equal, ndarray, frombuffer\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m NDArray\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01msparse\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m SparseArray, COO\n",
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'numpy'"
]
}
],
"source": [
"from os import path\n",
"from pathlib import Path\n",
Expand All @@ -24,6 +51,17 @@
{
"cell_type": "code",
"execution_count": 2,
"id": "4df17a3a727b7c02",
"metadata": {
"ExecuteTime": {
"end_time": "2023-11-10T20:03:00.508482Z",
"start_time": "2023-11-10T20:02:56.738612Z"
},
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [
{
"name": "stdout",
Expand All @@ -40,44 +78,38 @@
}
],
"source": [
"## Download sample data. This cell can be ignored if you wish to load your own\n",
"## data from a gridsearch.\n",
"\n",
"# set location of tutorial data\n",
"sample_data_dir = Path(Path(path.abspath(\"\")).parent, \"data\", \"sample-data\")\n",
"\n",
"# First we'll download a sample .nkg file which loads a range of functions,\n",
"# from the Kymata Research Group. nkg files contain both lefthand and\n",
"# righthand data for a set of functions\n",
"\n",
"sample_dataset = KymataMirror2023Q3Dataset(data_root=sample_data_dir, download=True)\n",
"nkg_path = Path(sample_dataset.path, sample_dataset.filenames[0])\n",
"print(nkg_path.name)\n",
"\n",
"# Second we will download two .nkg files which only contain one\n",
"# function each - 'ins_loudness' and 'd_ins_tc1_loudness':\n",
"ins_loudness_only_dataset = TVLInsLoudnessOnlyDataset(data_root=sample_data_dir, download=True)\n",
"ins_loudness_path = Path(ins_loudness_only_dataset.path, ins_loudness_only_dataset.filenames[0])\n",
"\n",
"d_ins_tc1_loudness_only_dataset = TVLDeltaInsTC1LoudnessOnlyDataset(data_root=sample_data_dir, download=True)\n",
"d_ins_tc1_loudness_path = Path(d_ins_tc1_loudness_only_dataset.path, d_ins_tc1_loudness_only_dataset.filenames[0])"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-11-24T15:03:28.707981Z",
"start_time": "2023-11-24T15:03:28.704356Z"
}
},
"id": "1f36e2e91b52522f"
"# Start with sample dataset\n",
"dataset_q3_2023 = get_dataset_kymata_mirror_q3_2023()\n",
"expression_data_kymata_mirror = ExpressionSet.load(from_path_or_file=Path(dataset_q3_2023.path, dataset_q3_2023.filenames[0]))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"outputs": [],
"source": [
"# Let's load the KymataMirror2023Q3 .nkg file. This contains around 30 functions.\n",
"expression_data_kymata_mirror = load_expression_set(from_path_or_file=nkg_path)"
"id": "681594ea282bf0f",
"metadata": {
"ExecuteTime": {
"end_time": "2023-11-10T20:03:11.535225Z",
"start_time": "2023-11-10T20:03:00.507022Z"
},
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Downloading dataset: GMLoudness\n",
"Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n",
"Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n",
"Downloading dataset: GMLoudness\n",
"Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n",
"Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n"
]
}
],
"metadata": {
"collapsed": false,
Expand All @@ -93,23 +125,37 @@
"execution_count": 4,
"outputs": [],
"source": [
"# Let's seperately load the 'ins_loudness' .nkg file, and then load and add the\n",
"# d_ins_tc1_loudness to it using '+='. 'expression_data_new_results' now contains two functions.\n",
"expression_data_new_results = load_expression_set(from_path_or_file=ins_loudness_path)\n",
"expression_data_new_results += load_expression_set(from_path_or_file=d_ins_tc1_loudness_path)"
],
"# Get a second sample dataset\n",
"\n",
"# Create new expression set object for the new results (or you can just add to an existing expressionSet directly using '+=' ).\n",
"dataset_gm_loudness = get_dataset_gm_loudness()\n",
"expression_data_new_results = load_matab_expression_files(\n",
" function_name=\"ins_loudness_2020\",\n",
" lh_file=Path(dataset_gm_loudness.path, dataset_gm_loudness.filenames[0]),\n",
" rh_file=Path(dataset_gm_loudness.path, dataset_gm_loudness.filenames[1]),\n",
")\n",
"dataset_d_ins_loudness_tonop_chan1 = get_dataset_d_ins_loudness_tonop_chan1()\n",
"expression_data_new_results += load_matab_expression_files(\n",
" function_name=\"delta_ins_loudness_tonotop_chan1_2020\",\n",
" lh_file=Path(dataset_d_ins_loudness_tonop_chan1.path, dataset_d_ins_loudness_tonop_chan1.filenames[0]),\n",
" rh_file=Path(dataset_d_ins_loudness_tonop_chan1.path, dataset_d_ins_loudness_tonop_chan1.filenames[1]),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "77c6c3617357edbb",
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-11-24T15:03:33.159669Z",
"start_time": "2023-11-24T15:03:32.309852Z"
"end_time": "2023-11-10T20:03:18.279668Z",
"start_time": "2023-11-10T20:03:11.536073Z"
},
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"id": "681594ea282bf0f"
},
{
"cell_type": "code",
"execution_count": 5,
"outputs": [
{
"name": "stderr",
Expand All @@ -126,35 +172,27 @@
"\n",
"# Save new expressionSet for use again in the future.\n",
"with NamedTemporaryFile() as tf:\n",
" save_expression_set(expression_data_extended, tf)"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-11-24T15:03:44.793458Z",
"start_time": "2023-11-24T15:03:33.162168Z"
}
},
"id": "77c6c3617357edbb"
" expression_data_extended.save(tf)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
"pygments_lexer": "ipython3",
"version": "3.12.0"
}
},
"nbformat": 4,
Expand Down