tag converting table and code

stile/dictionary.py

@@ -0,0 +1,111 @@
+"""
+This is a small script to solve the problem casued by new
+naming system of the data columns since S17A, which is different
+from S16A.
+
+If your code is based on S16A and want to read S17A and after, you
+just need to import this dictionary and specify your code is for
+S16A but want to read S17A data. If your code is already new for
+S17A, and want to read S16A for some reason. This can also help you.
+
+Example:
+
+import dictionary as dict
+
+"""
+import numpy as np
+
+s16_tags =np.array(['object_id','parent_id','ira','idec',\
+        'iflux_kron','iflux_kron_err','iflux_kron_flags',\
+        'imag_kron','imag_kron_err',\
+        'imag_cmodel','imag_cmodel_err','iflux_cmodel_flags',\
+        'iflux_cmodel','iflux_cmodel_err','merge_measurement_i',\
+	'a_g','a_r','a_i','a_z','a_y','gmag_forced_kron',\
+	'gmag_forced_kron_err','gflux_forced_kron_flags','rmag_forced_kron',\
+	'rmag_forced_kron_err','rflux_forced_kron_flags','imag_forced_kron',\
+	'imag_forced_kron_err','iflux_forced_kron_flags','zmag_forced_kron',\
+	'zmag_forced_kron_err','zflux_forced_kron_flags','ymag_forced_kron',\
+	'ymag_forced_kron_err','yflux_forced_kron_flags','gmag_forced_cmodel',\
+	'gmag_forced_cmodel_err','gflux_forced_cmodel','gflux_forced_cmodel_err',\
+	'gflux_forced_cmodel_flags','rmag_forced_cmodel','rmag_forced_cmodel_err',\
+	'rflux_forced_cmodel','rflux_forced_cmodel_err','rflux_forced_cmodel_flags',\
+	'imag_forced_cmodel','imag_forced_cmodel_err','iflux_forced_cmodel',\
+	'iflux_forced_cmodel_err','iflux_forced_cmodel_flags','zmag_forced_cmodel',\
+	'zmag_forced_cmodel_err','zflux_forced_cmodel','zflux_forced_cmodel_err',\
+	'zflux_forced_cmodel_flags','ymag_forced_cmodel','ymag_forced_cmodel_err',\
+	'yflux_forced_cmodel','yflux_forced_cmodel_err','yflux_forced_cmodel_flags',\
+	'ishape_hsm_regauss_e1','ishape_hsm_regauss_e2','ishape_hsm_regauss_sigma',\
+	'ishape_hsm_reguass_resolution','ishape_hsm_regauss_derived_rms_e',\
+	'ishape_sdss_ixx','ishape_sdss_iyy',\
+	'ishape_sdss_ixy','ishape_sdss_psf_ixx','ishape_sdss_psf_iyy',\
+	'ishape_sdss_psf_ixy','tract','patch','merge_peak_g','merge_peak_r',\
+	'merge_peak_i','merge_peak_z','merge_peak_y','gcountinputs',\
+	'rcountinputs','icountinputs','zcountinputs','ycountinputs',\
+	'iflags_pixel_bright_object_center','iflags_pixel_bright_object_any',\
+	'iblendedness_flags','iblendedness_abs_flux',\
+	'ishape_hsm_reguass_derived_shape_weight',\
+	'ishape_hsm_regauss_derived_shear_bias_m',\
+	'ishape_hsm_regauss_derived_shear_bias_c1',\
+	'ishape_hsm_regauss_derived_shear_bias_c2'])
+
+snw_tags =np.array(['object_id','parent_id','i_ra','i_dec',\
+        'i_kronflux_flux','i_kronflux_fluxsigma','i_kronflux_flags',\
+        'i_kronflux_mag','i_kronflux_magsigma',\
+        'i_cmodel_mag','i_cmodel_magsigma','i_cmodel_flags',\
+        'i_cmodel_flux','i_cmodel_fluxsigma','merge_measurement_i',\
+	'a_g','a_r','a_i','a_z','a_y','g_kronflux_mag',\
+	'g_kronflux_magsigma','g_kronflux_flags','r_kronflux_mag',\
+	'r_kronflux_magsigma','r_kronflux_flags','i_kronflux_mag',\
+	'i_kronflux_magsigma','i_kronflux_flags','z_kronflux_mag',\
+	'z_kronflux_magsigma','z_kronflux_flags','y_kronflux_mag',\
+	'y_kronflux_magsigma','y_kronflux_flags','g_cmodel_mag',\
+	'g_cmodel_magsigma','g_cmodel_flux','g_cmodel_fluxsigma',\
+	'g_cmodel_flags','r_cmodel_mag','r_cmodel_magsigma',\
+	'r_cmodel_flux','r_cmodel_fluxsigma','r_cmodel_flags',\
+	'i_cmodel_mag','i_cmodel_magsigma','i_cmodel_flux',\
+	'i_cmodel_fluxsigma','i_cmodel_flags','z_cmodel_mag',\
+	'z_cmodel_magsigma','z_cmodel_flux','z_cmodel_fluxsigma',\
+	'z_cmodel_flags','y_cmodel_mag','y_cmodel_magsigma',\
+	'y_cmodel_flux','y_cmodel_fluxsigma','y_cmodel_flags',\
+	'i_hsmshaperegauss_e1','i_hsmshaperegauss_e2','i_hsmshaperegauss_sigma',\
+	'i_hsmshapereguass_resolution','i_hsmshaperegauss_derived_rms_e',\
+	'i_sdssshape_shape11','i_sdssshape_shape22',\
+	'i_sdssshape_shape12','i_sdssshape_psf_shape11','i_sdssshape_psf_shape22',\
+	'i_sdssshape_psf_shape12','tract','patch','merge_peak_g','merge_peak_r',\
+	'merge_peak_i','merge_peak_z','merge_peak_y','g_inputcount_value',\
+	'r_inputcount_value','i_inputcount_value','z_inputcount_value',\
+	'y_inputcount_value',\
+	'i_pixelflags_bright_objectcenter','i_pixelflag_bright_object',\
+	'i_blendedness_flags','i_blendedness_abs_flux',\
+	'i_hsmshapereguass_derived_shape_weight',\
+	'i_hsmshaperegauss_derived_shear_bias_m',\
+	'i_hsmshaperegauss_derived_shear_bias_c1',\
+	'i_hsmshaperegauss_derived_shear_bias_c2'])
+
+
+def _crossfind(code_for,data_version,colname):
+   if code_for=='S16A' and data_version=='S17A' or data_version=='S18A':
+      if isinstance(colname,str):
+        ix      = s16_tags==colname
+        newtags = snw_tags[ix][0]
+      if isinstance(colname,list):
+	nx      = len(colname)
+	newtags = []
+	for i in range(nx):
+            ix  = s16_tags==colname[i]	
+	    newtags.append(snw_tags[ix][0])
+	newtags = np.array(newtags)
+   if code_for=='S17A' or code_for=='S18A' and data_version=='S16A':
+      if isinstance(colname,str): 
+        ix      = snw_tags==colname
+        newtags = s16_tags[ix][0]
+      if isinstance(colname,list):
+	nx      = len(colname)
+	newtags = []
+	for i in range(nx):
+            ix  = snw_tags==colname[i]	
+	    newtags.append(s16_tags[ix][0])
+	newtags = np.array(newtags)
+
+   return newtags
+