Merge pull request #91 from winter-telescope/diffmaglim

add diffmaglim to dataframe
winter-telescope · Aug 18, 2022 · 32b7dd8 · 32b7dd8
2 parents bfbc657 + 640ff76
commit 32b7dd8
Show file tree

Hide file tree

Showing 2 changed files with 23 additions and 16 deletions.
diff --git a/winterdrp/processors/candidates/candidate_detector.py b/winterdrp/processors/candidates/candidate_detector.py
@@ -159,8 +159,10 @@ def generate_candidates_table(self, scorr_catalog_name, sci_resamp_imagename, re
         det_srcs['programid'] = fits.getval(sci_resamp_imagename, 'PROGID')
         det_srcs['fid'] = fits.getval(sci_resamp_imagename, 'FILTERID')
         det_srcs['candid'] = np.array(det_srcs['jd']*100, dtype=int)*10000 + np.arange(len(det_srcs))
+        det_srcs['diffmaglim'] = fits.getval(diff_filename,'DIFFMLIM' )
         det_srcs = det_srcs.to_pandas()
-
+        logger.info(det_srcs['diffmaglim'])
+
         return det_srcs
 
     def _apply_to_images(

diff --git a/winterdrp/processors/zogy/zogy.py b/winterdrp/processors/zogy/zogy.py
@@ -53,38 +53,43 @@ def _apply_to_images(
                                      ref_rms_image, sci_rms, ref_rms, dx=ast_unc_x, dy=ast_unc_y)
 
             diff_image_path = sci_image_path.replace('.fits', '') + '.diff.fits'
+            diff_psf_path = diff_image_path + '.psf'
+            scorr_image_path = sci_image_path.replace('.fits', '') + '.scorr.fits'
+
+            scorr_mean, scorr_median, scorr_std = sigma_clipped_stats(S_corr)
+            logger.info(f"Scorr mean, median, STD is {scorr_mean}, {scorr_median}, {scorr_std}")
+            sci_rms_data, _ = self.open_fits(os.path.join(self.get_sub_output_dir(), sci_rms_image))
+            ref_rms_data, _ = self.open_fits(os.path.join(self.get_sub_output_dir(), ref_rms_image))
+            diff_rms_image = np.sqrt(sci_rms_data ** 2 + ref_rms_data ** 2)
+            diff_rms_mean, diff_rms_median, diff_rms_std = sigma_clipped_stats(diff_rms_image)
+            diff_rms_path = diff_image_path + '.unc'
+
+            header["DIFFIMG"] = diff_image_path
+            header["DIFFPSF"] = diff_psf_path
+            header["DIFFSCR"] = scorr_image_path
+            header["DIFFUNC"] = diff_rms_path
+            noise = np.sqrt(np.nansum(np.square(P_D)*np.square(diff_rms_median)))/np.nansum(np.square(P_D))
+            header["DIFFMLIM"] = -2.5*np.log10(noise*5) + float(header["TMC_ZP"])
+
             self.save_fits(data=D,
                            header=header,
                            path=os.path.join(self.get_sub_output_dir(), diff_image_path))
 
-            diff_psf_path = diff_image_path + '.psf'
             self.save_fits(data=P_D,
                            header=None,
                            path=os.path.join(self.get_sub_output_dir(), diff_psf_path))
 
-            scorr_image_path = sci_image_path.replace('.fits', '') + '.scorr.fits'
             scorr_header = header.copy()
             scorr_header[latest_mask_save_key] = header['SCORMASK']
             self.save_fits(data=S_corr,
                            header=scorr_header,
                            path=os.path.join(self.get_sub_output_dir(), scorr_image_path))
-            scorr_mean, scorr_median, scorr_std = sigma_clipped_stats(S_corr)
-            logger.info(f"Scorr mean, median, STD is {scorr_mean}, {scorr_median}, {scorr_std}")
-            sci_rms_data, _ = self.open_fits(os.path.join(self.get_sub_output_dir(), sci_rms_image))
-            ref_rms_data, _ = self.open_fits(os.path.join(self.get_sub_output_dir(), ref_rms_image))
-            diff_rms_image = np.sqrt(sci_rms_data ** 2 + ref_rms_data ** 2)
 
-            diff_rms_path = diff_image_path + '.unc'
             self.save_fits(data=diff_rms_image,
                            header=header,
                            path=os.path.join(self.get_sub_output_dir(), diff_rms_path))
-
-            header["DIFFIMG"] = diff_image_path
-            header["DIFFPSF"] = diff_psf_path
-            header["DIFFSCR"] = scorr_image_path
-            header["DIFFUNC"] = diff_rms_path
-
-            # for temp_file in temp_files:
+            # logger.info(f"{diff_rms_std}, {diff_rms_median}, {diff_std} DIFFMAGLIM {header['DIFFMLIM']}")
+            # # for temp_file in temp_files:
             #     os.remove(temp_file)
             #     logger.info(f"Deleted temporary file {temp_file}")
             diff_images.append(D)