Merge pull request #178 from mwcraig/update-notebooks-2.0

Update notebooks

stellarphot/differential_photometry/aij_rel_fluxes.py

@@ -6,6 +6,7 @@
 
 __all__ = ['add_in_quadrature', 'calc_aij_relative_flux']
 
+
 def add_in_quadrature(array):
     """
     Add an array of numbers in quadrature.
@@ -16,19 +17,19 @@ def add_in_quadrature(array):
 def calc_aij_relative_flux(star_data, comp_stars,
                            in_place=True, coord_column=None,
                            star_id_column='star_id',
-                           counts_column_name='aperture_net_counts'):
+                           counts_column_name='aperture_net_cnts'):
     """
     Calculate AstroImageJ-style flux ratios.
 
     Parameters
     ----------
 
-    star_data : '~astropy.table.Table'
-        Table of star data from one or more images.
+    star_data : 'stellarphot.PhotometryData'
+        Photometry data from one or more images.
 
     comp_stars : '~astropy.table.Table'
         Table of comparison stars in the field. Must contain a column
-        called ``RA`` and a column called ``Dec``.
+        called ``ra`` and a column called ``dec``.
         NOTE that not all
         of the comparison stars will necessarily be used. Stars in
         this table are excluded from the comparison set if, in any
@@ -47,7 +48,6 @@ def calc_aij_relative_flux(star_data, comp_stars,
 
     counts_column_name : str,  optional
         If provided, use this column to find counts.
-        If not provided, the column 'aperture_net_counts' is used.
 
     star_id_column : str,  optional
         Name of the column that provides a unique identifier for each
@@ -56,33 +56,33 @@ def calc_aij_relative_flux(star_data, comp_stars,
     Returns
     -------
 
-    `astropy.table.Table` or None
+    `stellarphot.PhotometryData` or None
         The return type depends on the value of ``in_place``. If it is
         ``False``, then the new columns are returned as a separate table,
         otherwise the columns are simply added to the input table.
     """
 
     # Match comparison star list to instrumental magnitude information
-    if star_data['RA'].unit is None:
+    if star_data['ra'].unit is None:
         unit = 'degree'
     else:
         # Pulled this from the source code -- None is ok but need
         # to match the number of coordinates.
         unit = [None, None]
 
-    star_data_coords = SkyCoord(ra=star_data['RA'], dec=star_data['Dec'],
+    star_data_coords = SkyCoord(ra=star_data['ra'], dec=star_data['dec'],
                                 unit=unit)
 
     if coord_column is not None:
         comp_coords = comp_stars[coord_column]
     else:
-        if comp_stars['RA'].unit is None:
+        if comp_stars['ra'].unit is None:
             unit = 'degree'
         else:
             # Pulled this from the source code -- None is ok but need
             # to match the number of coordinates.
             unit = [None, None]
-        comp_coords = SkyCoord(ra=comp_stars['RA'], dec=comp_stars['Dec'],
+        comp_coords = SkyCoord(ra=comp_stars['ra'], dec=comp_stars['dec'],
                                unit=unit)
 
     # Check for matches of stars in star data to the stars in comp_stars
@@ -115,7 +115,7 @@ def calc_aij_relative_flux(star_data, comp_stars,
         this_comp = star_data[star_id_column] == comp
         good[this_comp] = False
 
-    error_column_name = 'noise-aij'
+    error_column_name = 'noise_electrons'
     # Calculate comp star counts for each time
 
     # Make a small table with just counts, errors and time for all of the comparison

stellarphot/differential_photometry/tests/test_aij_rel_fluxes.py

@@ -7,6 +7,7 @@
 from astropy.time import Time
 import astropy.units as u
 
+from stellarphot import PhotometryData
 from stellarphot.differential_photometry.aij_rel_fluxes import calc_aij_relative_flux
 
 
@@ -51,9 +52,10 @@ def _raw_photometry_table():
                             _repeat(star_dec, n_times), _repeat(fluxes, n_times),
                             _repeat(errors, n_times),
                             _repeat(star_ids, n_times)],
-                      names=['date-obs', 'RA', 'Dec', 'aperture_net_counts',
-                             'noise-aij', 'star_id'])
+                      names=['date-obs', 'ra', 'dec', 'aperture_net_cnts',
+                             'noise_electrons', 'star_id'])
 
+    photom = PhotometryData(raw_table)
     return expected_flux_ratios, expected_flux_error, raw_table, raw_table[1:4]
 
 
@@ -71,12 +73,12 @@ def test_relative_flux_calculation(in_place,
     all_expected_error = _repeat(expected_error, n_times)
 
     if not star_ra_dec_have_units:
-        input_table['RA'] = input_table['RA'].data
-        input_table['Dec'] = input_table['Dec'].data
+        input_table['ra'] = input_table['ra'].data
+        input_table['dec'] = input_table['dec'].data
 
     if not comp_ra_dec_have_units:
-        comp_star['RA'] = comp_star['RA'].data
-        comp_star['Dec'] = comp_star['Dec'].data
+        comp_star['ra'] = comp_star['ra'].data
+        comp_star['dec'] = comp_star['dec'].data
 
     output_table = calc_aij_relative_flux(input_table, comp_star,
                                           in_place=in_place)
@@ -106,27 +108,27 @@ def test_bad_comp_star(bad_thing):
 
     if bad_thing == 'RA':
         # "Jiggle" one of the stars by moving it by a few arcsec in one image.
-        coord_inp = SkyCoord(ra=last_one['RA'], dec=last_one['Dec'],
+        coord_inp = SkyCoord(ra=last_one['ra'], dec=last_one['dec'],
                              unit=u.degree)
         coord_bad_ra = coord_inp.ra + 3 * u.arcsecond
-        input_table['RA'][-1] = coord_bad_ra.degree
+        input_table['ra'][-1] = coord_bad_ra.degree
     elif bad_thing == 'NaN':
-        input_table['aperture_net_counts'][-1] = np.nan
+        input_table['aperture_net_cnts'][-1] = np.nan
 
     output_table = calc_aij_relative_flux(input_table, comp_star,
                                           in_place=False)
 
-    old_total_flux = comp_star['aperture_net_counts'].sum()
-    new_flux = old_total_flux - last_one['aperture_net_counts']
+    old_total_flux = comp_star['aperture_net_cnts'].sum()
+    new_flux = old_total_flux - last_one['aperture_net_cnts']
     # This works for target stars, i.e. those never in comparison set
     new_expected_flux = old_total_flux / new_flux * expected_flux
 
     # Oh wow, this is terrible....
     # Need to manually calculate for the only two that are still in comparison
-    new_expected_flux[1] = (comp_star['aperture_net_counts'][0] /
-                            comp_star['aperture_net_counts'][1])
-    new_expected_flux[2] = (comp_star['aperture_net_counts'][1] /
-                            comp_star['aperture_net_counts'][0])
+    new_expected_flux[1] = (comp_star['aperture_net_cnts'][0] /
+                            comp_star['aperture_net_cnts'][1])
+    new_expected_flux[2] = (comp_star['aperture_net_cnts'][1] /
+                            comp_star['aperture_net_cnts'][0])
 
     new_expected_flux[3] = expected_flux[3]
     if bad_thing == 'NaN':

stellarphot/notebooks/photometry/03-photometry-template.ipynb

@@ -3,7 +3,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "from pathlib import Path\n",
@@ -31,7 +33,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "##\n",
@@ -41,7 +45,7 @@
     "                      read_noise = 10.0 * u.electron,\n",
     "                      dark_current=0.01 * u.electron / u.second,\n",
     "                      pixel_scale = 0.563 * u.arcsec / u.pix)\n",
-    "feder_filters = {'up':'SU', 'gp':'SG', 'rp':'SR', 'zp':'SZ', 'ip':'SI'}\n",
+    "feder_filters = {'up':'SU', 'gp':'SG', 'rp':'SR', 'zp':'SZ', 'ip':'SI', 'V': 'V', 'B': 'B'}\n",
     "feder_obs = EarthLocation(lat = 46.86678, lon=-96.45328, height=311)\n",
     "\n",
     "# Maxmimum ADU for the images before we should consider pixels saturated\n",
@@ -60,7 +64,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "ps = PhotometrySettings()\n",
@@ -77,7 +83,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "##\n",
@@ -109,7 +117,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# The maximum allowed shift in an object position (in pixels) when comparing\n",
@@ -138,7 +148,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "photometry_table = multi_image_photometry(image_directory,\n",
@@ -151,13 +163,15 @@
     "                                             reject_too_close=True,\n",
     "                                             reject_background_outliers=True,\n",
     "                                             passband_map=feder_filters,\n",
-    "                                             fwhm_by_fit=True)"
+    "                                             fwhm_by_fit=False)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "photometry_table.write(photometry_file)"
@@ -166,7 +180,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "photometry_table\n"
@@ -196,7 +212,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,

stellarphot/notebooks/photometry/04-transform-pared-back.ipynb

@@ -3,7 +3,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "from pathlib import Path\n",
@@ -67,14 +69,15 @@
     "c_min = -0.5\n",
     "d_min = -1e-6\n",
     "\n",
-    "our_filters = ['B', 'V', 'rp']\n",
+    "our_filters = ['SI']\n",
     "\n",
     "aavso_band_names = dict(\n",
     "    B='B', \n",
     "    V='V',\n",
     "    gp='SG',\n",
     "    rp='SR',\n",
-    "    ip='SI'\n",
+    "    ip='SI',\n",
+    "    SI='SI'\n",
     ")\n",
     "\n",
     "cat_color_colums = dict(\n",
@@ -83,30 +86,34 @@
     "    gp=('g_mag', 'r_mag'),\n",
     "    rp=('r_mag', 'i_mag'),\n",
     "    ip=('r_mag', 'i_mag'),\n",
-    "    \n",
+    "    SI=('r_mag', 'i_mag'),\n",
     ")\n",
     "\n",
     "cat_filter = dict(\n",
     "    B='Bmag', \n",
     "    V='Vmag',\n",
     "    gp='g_mag',\n",
     "    rp='r_mag',\n",
-    "    ip='i_mag')\n",
+    "    ip='i_mag',\n",
+    "    SI='i_mag',\n",
+    ")\n",
     "\n",
-    "input_photometry_file = 'm13-2021-09-28.csv'\n",
-    "output_photometry_file = 'some_name.csv'"
+    "input_photometry_file = 'TIC-402828941-2021-09-28.ecsv'\n",
+    "output_photometry_file = 'some_name.ecsv'"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "all_mags = Table.read(input_photometry_file)\n",
     "\n",
     "# Ensure we have the right table ordering later\n",
-    "all_mags.sort(['filter', 'BJD'])"
+    "all_mags.sort(['passband', 'bjd'])"
    ]
   },
   {
@@ -119,10 +126,12 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "filter_groups = all_mags.group_by('filter')\n",
+    "filter_groups = all_mags.group_by('passband')\n",
     "\n",
     "\n",
     "# Check: do we have any unexpected filters?\n",
@@ -140,14 +149,16 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "output_table = [] \n",
     "\n",
     "for k, group in zip(our_filters, filter_groups.groups):\n",
     "    print(f'Transforming band {k}')\n",
-    "    by_bjd = group.group_by('BJD')\n",
+    "    by_bjd = group.group_by('bjd')\n",
     "    \n",
     "    transform_to_catalog(by_bjd, f'mag_inst', aavso_band_names[k], \n",
     "                     obs_error_column='mag_error', \n",
@@ -213,7 +224,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,