Adding text for the URLs in the intro and cutting text up for easier future management

bsipocz · bsipocz · commit 1edbdfdf321b · 2025-03-18T19:07:12.000-07:00
diff --git a/tutorials/euclid_access/1_Euclid_intro_MER_images.md b/tutorials/euclid_access/1_Euclid_intro_MER_images.md
@@ -32,11 +32,17 @@ By the end of this tutorial, you will:
 
 +++
 
-Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe. The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO). On March 19, 2025 the data will be available on the ESA archive (https://easidr.esac.esa.int/sas/) and on the IRSA archive (https://irsa.ipac.caltech.edu).
+Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe.
+The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO).
+On March 19, 2025 the data will be available on the [ESA archive](https://easidr.esac.esa.int/sas/) and on the [IRSA archive](https://irsa.ipac.caltech.edu).
 
-These notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive. At the end of the notebook, we also include some information for how to access the Q1 data from the ESA archive. If you have any issues accessing data from the archives, please contact the helpdesk directly: IRSA (irsasupport@ipac.caltech.edu) and ESA (https://support.cosmos.esa.int/euclid).
+These Q1 notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive.
+If you have any issues accessing data from the archives, please contact the helpdesk directly: [IRSA helpdesk](irsasupport@ipac.caltech.edu) and [ESA Euclid Helpdesk](https://support.cosmos.esa.int/euclid).
 
-MER mosaic images are all the images from Level 2 images in different filters mapped to a common pixel scale. This notebook provides an introduction to MER mosaics released as part of Euclid Q1. Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
+MER mosaic images are all the images from Level 2 images in different filters mapped to a common pixel scale.
+
+This notebook provides an introduction to MER mosaics released as part of Euclid Q1.
+Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
 
 +++
 
diff --git a/tutorials/euclid_access/2_Euclid_intro_MER_catalog.md b/tutorials/euclid_access/2_Euclid_intro_MER_catalog.md
@@ -19,7 +19,7 @@ kernelspec:
 
 +++
 
-By the end of this tutorial, you will: 
+By the end of this tutorial, you will:
 - Understand the basic characteristics of Euclid Q1 MER catalogs.
 - What columns are available in the MER catalog.
 - How to query with ADQL in the MER catalog.
@@ -31,11 +31,17 @@ By the end of this tutorial, you will:
 
 +++
 
-Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe. The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO). On March 19, 2025 the data will be available on the ESA archive (https://easidr.esac.esa.int/sas/) and on the IRSA archive (https://irsa.ipac.caltech.edu).
+Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe.
+The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO).
+On March 19, 2025 the data will be available on the [ESA archive](https://easidr.esac.esa.int/sas/) and on the [IRSA archive](https://irsa.ipac.caltech.edu).
 
-These notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive. At the end of the notebook, we also include some information for how to access the Q1 data from the ESA archive. If you have any issues accessing data from the archives, please contact the helpdesk directly: IRSA (irsasupport@ipac.caltech.edu) and ESA (https://support.cosmos.esa.int/euclid).
+These Q1 notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive.
+If you have any issues accessing data from the archives, please contact the helpdesk directly: [IRSA helpdesk](irsasupport@ipac.caltech.edu) and [ESA Euclid Helpdesk](https://support.cosmos.esa.int/euclid).
 
-Each entry in the MER catalog is a single source containing all its photometry from the MER Mosaics (VIS, Y, J, H and any accompanying external ground observations) along with other basic measurements, like size and shape. This notebook provides an introduction to the MER catalog released as part of Euclid Q1. Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
+Each entry in the MER catalog is a single source containing all its photometry from the MER Mosaics (VIS, Y, J, H and any accompanying external ground observations) along with other basic measurements, like size and shape.
+
+This notebook provides an introduction to the MER catalog released as part of Euclid Q1.
+Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
 
 +++
 
@@ -83,7 +89,7 @@ print(len(columns))
 
 ```{code-cell} ipython3
 for col in columns:
-    print(f'{f"{col.name}":30s}  {col.unit}  {col.description}') 
+    print(f'{f"{col.name}":30s}  {col.unit}  {col.description}')
 ```
 
 ### Define the following ADQL query to find the first 10k stars in the MER catalog
@@ -127,7 +133,7 @@ mag_h_s_irsa=-2.5*np.log10(df_s_irsa["flux_h_templfit"]) + 23.9 # H
 x_s_irsa = mag_y_s_irsa - mag_h_s_irsa # Y - H
 y_s_irsa = mag_y_s_irsa
 
-xerr_s_irsa= 2.5 / np.log(10) * np.sqrt((df_s_irsa["fluxerr_y_templfit"] / df_s_irsa["flux_y_templfit"])**2 
+xerr_s_irsa= 2.5 / np.log(10) * np.sqrt((df_s_irsa["fluxerr_y_templfit"] / df_s_irsa["flux_y_templfit"])**2
                                  + (df_s_irsa["fluxerr_h_templfit"] / df_s_irsa["flux_h_templfit"])**2)
 yerr_s_irsa= 2.5 / np.log(10) * (df_s_irsa["fluxerr_y_templfit"] / df_s_irsa["flux_y_templfit"])
 
diff --git a/tutorials/euclid_access/3_Euclid_intro_1D_spectra.md b/tutorials/euclid_access/3_Euclid_intro_1D_spectra.md
@@ -19,7 +19,7 @@ kernelspec:
 
 +++
 
-By the end of this tutorial, you will: 
+By the end of this tutorial, you will:
 - Understand the basic characteristics of Euclid Q1 SIR 1D spectra.
 - What columns are available in the MER catalog.
 - How to query with ADQL in the MER catalog.
@@ -29,17 +29,27 @@ By the end of this tutorial, you will:
 
 ## Introduction
 
-+++
+++
 
-Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe. The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO). On March 19, 2025 the data will be available on the ESA archive (https://easidr.esac.esa.int/sas/) and on the IRSA archive (https://irsa.ipac.caltech.edu).
+Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe.
+The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO).
+On March 19, 2025 the data will be available on the [ESA archive](https://easidr.esac.esa.int/sas/) and on the [IRSA archive](https://irsa.ipac.caltech.edu).
 
-These notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive. At the end of the notebook, we also include some information for how to access the Q1 data from the ESA archive. If you have any issues accessing data from the archives, please contact the helpdesk directly: IRSA (irsasupport@ipac.caltech.edu) and ESA (https://support.cosmos.esa.int/euclid).
+These Q1 notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive.
+If you have any issues accessing data from the archives, please contact the helpdesk directly: [IRSA helpdesk](irsasupport@ipac.caltech.edu) and [ESA Euclid Helpdesk](https://support.cosmos.esa.int/euclid).
 
-For the Euclid Wide Survey standard operating mode, the telescope undertakes a 4-point dither pattern. At each position VIS and NISP each take a 570s exposure, consisting of a direct visible image and a red grism exposure. This is followed by further NISP exposures in the Y, J, and H band filters (112 seconds each). The telescope is then dithered, and the sequence is repeated starting with a different grism position angle. There are actually two operational grisms oriented 180 degrees from each other. Each grism which will be used twice in this sequence, but with slight angular offsets (+/- 4 degrees), effectively creating the four different grism angles (Scaramella et al. 2022, A&A 662, A112).	
+For the Euclid Wide Survey standard operating mode, the telescope undertakes a 4-point dither pattern.
+At each position VIS and NISP each take a 570s exposure, consisting of a direct visible image and a red grism exposure.
+This is followed by further NISP exposures in the Y, J, and H band filters (112 seconds each).
+The telescope is then dithered, and the sequence is repeated starting with a different grism position angle.
+There are actually two operational grisms oriented 180 degrees from each other. Each grism which will be used twice in this sequence, but with slight angular offsets (+/- 4 degrees), effectively creating the four different grism angles (Scaramella et al. 2022, A&A 662, A112).
 
-Data which can be obtained for SIR include: SIR "images", which effectively show the full image of objects with the spectral traces overlapping, and SIR 1D spectra for individual objects. Below we will describe how to access and process the 1D spectra products. For most users, simply accessing th 1D spectra is probably the preferred option, unless they would like to extract the spectrum again, or inspect the images to see if there is any artifact which might add noise to the spectrum.
+Data which can be obtained for SIR include: SIR "images", which effectively show the full image of objects with the spectral traces overlapping, and SIR 1D spectra for individual objects.
+In this notebook we describe how to access and process the 1D spectra products.
+For most users, simply accessing th 1D spectra is probably the preferred option, unless they would like to extract the spectrum again, or inspect the images to see if there is any artifact which might add noise to the spectrum.
 
-This notebook provides an introduction to the SIR 1D spectra released as part of Euclid Q1. Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
+This notebook provides an introduction to the SIR 1D spectra released as part of Euclid Q1.
+Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
 
 +++
 
@@ -84,7 +94,7 @@ table_galaxy_candidates= 'euclid_q1_spectro_zcatalog_spe_galaxy_candidates'
 ```
 
 ```{code-cell} ipython3
-## Change the settings so we can see all the columns in the dataframe and the full column width 
+## Change the settings so we can see all the columns in the dataframe and the full column width
 ## (to see the full long URL)
 pd.set_option('display.max_columns', None)
 pd.set_option('display.max_colwidth', None)
@@ -100,7 +110,7 @@ pd.set_option('display.max_colwidth', None)
 ```{code-cell} ipython3
 obj_id=2739401293646823742
 
-## Pull the data on these objects 
+## Pull the data on these objects
 adql_object = f"SELECT * \
 FROM {table_1dspectra} \
 WHERE objectid = {obj_id} \
@@ -130,7 +140,7 @@ Currently IRSA has the spectra stored in very large files containing multiple (1
 #### Currently commented out
 
 # ## Complete file url with the irsa url at the start
-# url = file_url  
+# url = file_url
 # response = requests.get(url)
 
 # hdul = fits.open(BytesIO(response.content))  # Open FITS file from memory
diff --git a/tutorials/euclid_access/5_Euclid_intro_SPE_catalog.md b/tutorials/euclid_access/5_Euclid_intro_SPE_catalog.md
@@ -19,7 +19,7 @@ kernelspec:
 
 +++
 
-By the end of this tutorial, you will: 
+By the end of this tutorial, you will:
 - Understand the basic characteristics of Euclid Q1 SPE catalogs.
 - Understand what SPE catalogs are available and how to view the columns in those catalogs.
 - How to query with ADQL in the SPE lines catalog to find strong H-alpha detections.
@@ -31,11 +31,16 @@ By the end of this tutorial, you will:
 
 +++
 
-Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe. The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO). On March 19, 2025 the data will be available on the ESA archive (https://easidr.esac.esa.int/sas/) and on the IRSA archive (https://irsa.ipac.caltech.edu).
+Euclid is a European Space Agency (ESA) space mission with NASA participation, to study the geometry and nature of the dark Universe.
+The Quick Data Release 1 (Q1) are the first data release from the Euclid mission after the Early Release Observations (ERO).
+On March 19, 2025 the data will be available on the [ESA archive](https://easidr.esac.esa.int/sas/) and on the [IRSA archive](https://irsa.ipac.caltech.edu).
 
-These notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive. At the end of the notebook, we also include some information for how to access the Q1 data from the ESA archive. If you have any issues accessing data from the archives, please contact the helpdesk directly: IRSA (irsasupport@ipac.caltech.edu) and ESA (https://support.cosmos.esa.int/euclid).
+These Q1 notebooks focus on how to access, download, and process Euclid Q1 data from the IRSA archive.
+If you have any issues accessing data from the archives, please contact the helpdesk directly: [IRSA helpdesk](irsasupport@ipac.caltech.edu) and [ESA Euclid Helpdesk](https://support.cosmos.esa.int/euclid).
 
-Every one dimensional spectrum is processed through a template and line fitting pipeline, producing several different 'SPE' catalogs. This notebook provides an introduction to the SPE catalogs released as part of Euclid Q1. Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
+Every one dimensional spectrum is processed through a template and line fitting pipeline, producing several different 'SPE' catalogs.
+This notebook provides an introduction to the SPE catalogs released as part of Euclid Q1.
+Other Euclid notebooks show how to use other data products released as part of Euclid Q1.
 
 +++
 
@@ -87,7 +92,7 @@ df_im_irsa=im_table.to_table().to_pandas()
 ```
 
 ```{code-cell} ipython3
-## Change the settings so we can see all the columns in the dataframe and the full column width 
+## Change the settings so we can see all the columns in the dataframe and the full column width
 ## (to see the full long URL)
 pd.set_option('display.max_columns', None)
 pd.set_option('display.max_colwidth', None)
@@ -134,7 +139,7 @@ im_mer_irsa=hdu_mer_irsa[0].data
 #### Make a quick and simple plot to show the full MER image, with its large FOV
 
 ```{code-cell} ipython3
-plt.imshow(im_mer_irsa, cmap='gray', origin='lower', 
+plt.imshow(im_mer_irsa, cmap='gray', origin='lower',
            norm=ImageNormalize(im_mer_irsa, interval=PercentileInterval(99.9), stretch=AsinhStretch()))
 colorbar = plt.colorbar()
 ```
@@ -150,7 +155,7 @@ tables = service.tables
 for tablename in tables.keys():
     if "tap_schema" not in tablename and "euclid" in tablename:
             tables[tablename].describe()
-            
+
 ```
 
 ```{code-cell} ipython3
@@ -175,7 +180,7 @@ for col in columns:
 ```
 
 ```{code-cell} ipython3
-## Change the settings so we can see all the columns in the dataframe and the full column width 
+## Change the settings so we can see all the columns in the dataframe and the full column width
 ## (to see the full long URL)
 pd.set_option('display.max_columns', None)
 pd.set_option('display.max_colwidth', None)
@@ -188,7 +193,7 @@ pd.set_option('display.max_colwidth', None)
 
 ## Find some objects with spectra in our tileID
 
-We specify the following conditions on our search: 
+We specify the following conditions on our search:
 - The two signal to noise ratio columns (spe_line_snr_gf and spe_line_snr_di) should be greater than 5
 - We want to detect H-alpha.
 - We choose in which tileID to search, usign the tileID from the first notebook.
@@ -257,7 +262,7 @@ with fits.open(BytesIO(response.content), memmap=True) as hdul:
     hdu = hdul[df2['hdu'].iloc[0]]
     dat = Table.read(hdu, format='fits', hdu=1)
     df_obj_irsa = dat.to_pandas()
-    
+
 ```
 
 ### Now the data are read in, plot the spectrum with the H-alpha line labeled
