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Iolin #221

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25169c7
Fixed grammar in SpectralEnergyDistributions
i-olin May 15, 2024
911604f
corrections to MidInfraredPhotometry and ExploringSMASHDR2
i-olin May 15, 2024
280ace9
Checking for typos in Intro to Desi
i-olin May 15, 2024
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8 changes: 4 additions & 4 deletions 03_ScienceExamples/DESI/01_Intro_to_DESI_EDR.ipynb
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Expand Up @@ -16,7 +16,7 @@
"outputs": [],
"source": [
"__author__ = 'Ragadeepika Pucha <[email protected]>, Stephanie Juneau <[email protected]>'\n",
"__version__ = '20230914' \n",
"__version__ = '20230914' #yyyymmdd\n",
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Update the date to current.

"__datasets__ = ['desi_edr'] \n",
"__keywords__ = ['sparcl', 'spectra', 'database']"
]
Expand Down Expand Up @@ -1638,9 +1638,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "DESI 23.1",
"display_name": "Python 3 (ipykernel)",
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Re-run this NB on the DL NB server, so that it can use the DESI 23.x kernel (this is important, because specific kernels usually have specific S/W installed)/

"language": "python",
"name": "desi_23.1"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -1652,7 +1652,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
"version": "3.12.0"
}
},
"nbformat": 4,
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6 changes: 3 additions & 3 deletions 03_ScienceExamples/DESI/01a_Intro_to_DESI_EDR-Py3.ipynb
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Expand Up @@ -16,7 +16,7 @@
"outputs": [],
"source": [
"__author__ = 'Ragadeepika Pucha <[email protected]>, Stephanie Juneau <[email protected]>'\n",
"__version__ = '20230824' \n",
"__version__ = '20230824' #yyyymmdd\n",
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Update the version whenever you change and NB.

"__datasets__ = ['desi_edr'] \n",
"__keywords__ = ['sparcl', 'spectra', 'database']"
]
Expand Down Expand Up @@ -1480,7 +1480,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
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Re-run on DL's NB server to use the DL Python 3 kernel.

"language": "python",
"name": "python3"
},
Expand All @@ -1494,7 +1494,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
"version": "3.12.0"
}
},
"nbformat": 4,
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10 changes: 5 additions & 5 deletions 03_ScienceExamples/GalacticStructure/ExploringSMASHDR2.ipynb
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Expand Up @@ -75,7 +75,7 @@
"* deep - Same as object but only using the deepest exposures for each field (357,395,383 rows).\n",
"* xmatch - Crossmatches between SMASH and Gaia DR2, 2MASS and ALLWISE (4,155,114,664 rows).\n",
"\n",
"In this notebook, we'll use these some of tables to do some exploration of the SMASH survey.\n"
"In this notebook, we'll use some of these tables to do some exploration of the SMASH survey.\n"
]
},
{
Expand Down Expand Up @@ -1521,7 +1521,7 @@
"source": [
"<a class=\"anchor\" id=\"depth\"></a>\n",
"# Make depth and color maps\n",
"Now we'll get a little fancier with our maps. We'll have the database return average g- and i-band magnitudes and colors, and make some cuts on the magntude errors. We again GROUP BY the nest4096 column.\n"
"Now we'll get a little fancier with our maps. We'll have the database return average g- and i-band magnitudes and colors, and make some cuts on the magnitude errors. We again GROUP BY the nest4096 column.\n"
]
},
{
Expand Down Expand Up @@ -2277,7 +2277,7 @@
"ax1 = fig.add_subplot(121)\n",
"ax2 = fig.add_subplot(122)\n",
"\n",
"# color-magnitude diagram (Hess diagram)\n",
"# color-color diagram\n",
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"Hess diagram" could be put back with a link to the short wikipedia page: https://en.wikipedia.org/wiki/Hess_diagram

"im = ax1.hexbin(df_cmd['gmag']-df_cmd['rmag'],df_cmd['gmag']-df_cmd['imag'], \\\n",
" gridsize=400,cmap=matplotlib.cm.viridis,norm=matplotlib.colors.LogNorm())\n",
"ax1.set_ylabel('g - r',fontsize=15)\n",
Expand Down Expand Up @@ -3342,7 +3342,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
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Re-run on DL's NB server

"language": "python",
"name": "python3"
},
Expand All @@ -3356,7 +3356,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
"version": "3.12.0"
}
},
"nbformat": 4,
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10 changes: 5 additions & 5 deletions 03_ScienceExamples/SpectralEnergyDistributions/MidInfraredPhotometry_unWISEdr1_AllWISE.ipynb
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Expand Up @@ -7,7 +7,7 @@
"outputs": [],
"source": [
"__author__ = 'Stephanie Juneau <[email protected]>'\n",
"__version__ = '20230830' # yyyymmdd\n",
"__version__ = '20240515' # yyyymmdd\n",
"__datasets__ = ['unwise_dr1', 'allwise']\n",
"__keywords__ = ['science example', 'plot:cmd', 'plot:histogram']"
]
Expand Down Expand Up @@ -119,7 +119,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Below is an query from the *GettingStartedWithDataLab* notebook to quickly retrieve useful stats from the **tbl_stat** table."
"Below is a query from the *GettingStartedWithDataLab* notebook to quickly retrieve useful stats from the **tbl_stat** table."
]
},
{
Expand Down Expand Up @@ -482,7 +482,7 @@
"<a class=\"anchor\" id=\"chapter2\"></a>\n",
"# Chapter 2 - Color & Magnitude Distributions\n",
"\n",
"For reference, we will compate with the distributions of *W1-W2* color and *W1* magnitude from the cross-matched AllWISE-SDSS DR10 sample from the work of [Kurcz et al (2016)](https://ui.adsabs.harvard.edu/abs/2016A%26A...592A..25K). Below, we will create distributions from our query results."
"For reference, we will compare with the distributions of *W1-W2* color and *W1* magnitude from the cross-matched AllWISE-SDSS DR10 sample from the work of [Kurcz et al (2016)](https://ui.adsabs.harvard.edu/abs/2016A%26A...592A..25K). Below, we will create distributions from our query results."
]
},
{
Expand Down Expand Up @@ -772,7 +772,7 @@
"metadata": {},
"source": [
"### NOTES:\n",
"The Color-Magnitude distributions of the unWISE and AllWISE datasets show that an obvious difference in sensitivity, with unWISE reaching about ~0.5 magnitudes deeper in `W2`. Their respective detection limits are around `W2>17.5` for unWISE (vertical grey line), and around `W2>17` for AllWISE. In addition, there are slight differences between the two bivariate distributions. For instance, the upper-right envelope displays a different shape. Users of this notebook can explore what the origin of the differences might be."
"The Color-Magnitude distributions of the unWISE and AllWISE datasets show an obvious difference in sensitivity, with unWISE reaching about ~0.5 magnitudes deeper in `W2`. Their respective detection limits are around `W2>17.5` for unWISE (vertical grey line), and around `W2>17` for AllWISE. In addition, there are slight differences between the two bivariate distributions. For instance, the upper-right envelope displays a different shape. Users of this notebook can explore what the origin of the differences might be."
]
},
{
Expand Down Expand Up @@ -1038,7 +1038,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.6"
"version": "3.12.0"
}
},
"nbformat": 4,
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10 changes: 5 additions & 5 deletions 03_ScienceExamples/SpectralEnergyDistributions/SpectralEnergyDistributionsInSplusDr1.ipynb
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Expand Up @@ -11,7 +11,7 @@
"outputs": [],
"source": [
"__author__ = 'David Nidever <[email protected]>, Astro Data Lab Team <[email protected]>'\n",
"__version__ = '20230830' # yyymmdd\n",
"__version__ = '20240515' # yyyymmdd\n",
"__datasets__ = ['splus_dr1']\n",
"__keywords__ = ['science example', 'plot:cmd', 'plot:color-color', 'image cutout']"
]
Expand Down Expand Up @@ -126,7 +126,7 @@
" <a class=\"anchor\" id=\"query\"></a>\n",
"# Query the S-PLUS DR1 database\n",
"\n",
"Let's see how we query the S-PLUS DR1 database. With no specific spatial region in mind we'll just take the first 10,000 objects.\n",
"Let's see how we query the S-PLUS DR1 database. With no specific spatial region in mind, we'll just take the first 10,000 objects.\n",
"\n",
"## Construct the query string"
]
Expand Down Expand Up @@ -350,7 +350,7 @@
"\n",
"The many S-PLUS photometric bands can be used to produce color-color diagrams that are useful for measuring properties such as the metallicity or surface gravity of a star.\n",
"\n",
"(g-F515) vs. (g-r) is sensitive to surface gravity and can be used to separate dwarf stars from giant stars. The main locus of points is the dwarfs will the red giant live in the upper right. [See Majewski et al. (2000)](http://adsabs.harvard.edu/abs/2000AJ....120.2550M) for more details on this method."
"(g-F515) vs. (g-r) is sensitive to surface gravity and can be used to separate dwarf stars from giant stars. The main focus of points is the dwarfs, while the red giant live in the upper right. [See Majewski et al. (2000)](http://adsabs.harvard.edu/abs/2000AJ....120.2550M) for more details on this method."
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'locus' was correct, please change back. The sentence had typos though, and I think it should be "The main locus of points is the dwarfs, while the red giants live in the upper right."

]
},
{
Expand Down Expand Up @@ -426,7 +426,7 @@
"<a class=\"anchor\" id=\"sed\"></a>\n",
"# Creating Spectral Energy Distributions\n",
"One of the great advantages of the S-PLUS dataset is the large number of wide and narrow-band filters that can be used\n",
"to study the properties of the objects. Here we show how plot the Spectral Energy Distributions (SEDs) of objects. These can then be compared to spectral models to constrain properties such as Teff, logg and metallicity (for stars) and galaxy type and redshift for galaxies (see [Cennaro et al. 2018](http://adsabs.harvard.edu/abs/2018arXiv180402667C) for some examples)."
"to study the properties of the objects. Here we show how to plot the Spectral Energy Distributions (SEDs) of objects. These can then be compared to spectral models to constrain properties such as Teff, logg and metallicity (for stars) and galaxy type and redshift for galaxies (see [Cennaro et al. 2018](http://adsabs.harvard.edu/abs/2018arXiv180402667C) for some examples)."
]
},
{
Expand Down Expand Up @@ -668,7 +668,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.6"
"version": "3.12.0"
}
},
"nbformat": 4,
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