Include properties in _check_filters, _check_errors, _check_invalid (only...

Include properties in _check_filters, _check_errors, _check_invalid (only extensive) and add_model_error functions in observations.py. rename errors as bands_errors

pcigale/managers/observations.py

@@ -42,8 +42,8 @@ class ObservationsManagerPassbands(object):
         self.table = read_table(config['data_file'])
         self.bands = [band for band in config['bands'] if not
                       band.endswith('_err')]
-        self.errors = [band for band in config['bands'] if
-                       band.endswith('_err')]
+        self.bands_err = [band for band in config['bands'] if
+                          band.endswith('_err')]
         self.intprops = [prop for prop in config['properties'] if (prop not in
                          self.massproportional and not prop.endswith('_err'))]
         self.intprops_err = [prop for prop in config['properties'] if
@@ -54,6 +54,8 @@ class ObservationsManagerPassbands(object):
         self.extprops_err = [prop for prop in config['properties'] if
                              (prop.endswith('_err') and prop[:-4] in
                              self.massproportional)]
+        self.tofit = self.bands + self.intprops + self.extprops
+        self.tofit_err = self.bands_err + self.intprops_err + self.extprops_err
 
         # Sanitise the input
         self._check_filters()
@@ -88,16 +90,16 @@ class ObservationsManagerPassbands(object):
         the fit, a warning is displayed
 
         """
-        for band in self.bands + self.errors:
+        for band in self.tofit + self.tofit_err:
             if band not in self.table.colnames:
                 raise Exception("{} to be taken in the fit but not present "
                                 "in the observation table.".format(band))
 
         for band in self.table.colnames:
-            if (band != 'id' and band != 'redshift' and
-                    band not in self.bands + self.errors):
+            if (band != 'id' and band != 'redshift' and band not in self.tofit +
+                self.tofit_err):
                 self.table.remove_column(band)
-                print("Warning: {} in the input file but not to be taken into "
+                print("Warning: {} in the input file but not to be taken into"
                       "account in the fit.".format(band))
 
     def _check_errors(self, defaulterror=0.1):
@@ -122,16 +124,19 @@ class ObservationsManagerPassbands(object):
         if defaulterror < 0.:
             raise ValueError("The relative default error must be positive.")
 
-        for band in self.bands:
-            banderr = band + '_err'
-            if banderr not in self.errors or banderr not in self.table.colnames:
-                colerr = Column(data=np.fabs(self.table[band] * defaulterror),
-                                name=banderr)
+        for item in self.tofit:
+            error = item + '_err'
+            if item in self.intprops:
+                if error not in self.intprops_err or error not in self.table.colnames:
+                    raise ValueError("Instensive properties errors must be in input file.")
+            elif error not in self.tofit_err or error not in self.table.colnames:
+                colerr = Column(data=np.fabs(self.table[item] * defaulterror),
+                                name=error)
                 self.table.add_column(colerr,
-                                      index=self.table.colnames.index(band)+1)
+                                      index=self.table.colnames.index(item)+1)
                 print("Warning: {}% of {} taken as errors.".format(defaulterror *
                                                                    100.,
-                                                                   band))
+                                                                   item))
 
     def _check_invalid(self, upperlimits=False, threshold=-9990.):
         """Check whether invalid data are correctly marked as such.
@@ -152,25 +157,30 @@ class ObservationsManagerPassbands(object):
         """
         allinvalid = []
 
-        for band in self.bands:
-            banderr = band + '_err'
-            w = np.where((self.table[band] < threshold) |
-                         (self.table[banderr] < threshold))
-            self.table[band][w] = np.nan
+        for item in self.bands + self.extprops:
+            error = item + '_err'
+            w = np.where((self.table[item] < threshold) |
+                         (self.table[error] < threshold))
+            self.table[item][w] = np.nan
             if upperlimits is False:
-                w = np.where(self.table[banderr] <= 0.)
-                self.table[band][w] = np.nan
+                w = np.where(self.table[error] <= 0.)
+                self.table[item][w] = np.nan
             else:
-                w = np.where(self.table[banderr] == 0.)
-                self.table[band][w] = np.nan
-            if np.all(~np.isfinite(self.table[band])):
-                allinvalid.append(band)
-
-        for band in allinvalid:
-            self.bands.remove(band)
-            self.errors.remove(band + '_err')
-            self.table.remove_columns([band, band + '_err'])
-            print("Warning: {} removed as no valid data was found.".format(allinvalid))
+                w = np.where(self.table[error] == 0.)
+                self.table[item][w] = np.nan
+            if np.all(~np.isfinite(self.table[item])):
+                allinvalid.append(item)
+
+        for item in allinvalid:
+            if item in self.bands:
+                self.bands.remove(item)
+                self.bands_err.remove(item + '_err')
+            elif item in self.extprops:
+                self.extprops.remove(item)
+                self.extprops_err.remove(item + '_err')
+            self.table.remove_columns([item, item + '_err'])
+            print("Warning: {} removed as no valid data was found.".format(
+                allinvalid))
 
     def _add_model_error(self, modelerror=0.1):
         """Add in quadrature the error of the model to the input error.
@@ -178,17 +188,18 @@ class ObservationsManagerPassbands(object):
         Parameters
         ----------
         modelerror: float
-            Relative error of the models relative to the flux. By default 10%.
+            Relative error of the models relative to the flux (or property). By
+            default 10%.
 
         """
         if modelerror < 0.:
             raise ValueError("The relative model error must be positive.")
 
-        for band in self.bands:
-            banderr = band + '_err'
-            w = np.where(self.table[banderr] >= 0.)
-            self.table[banderr][w] = np.sqrt(self.table[banderr][w]**2. +
-                                             (self.table[band][w]*modelerror)**2.)
+        for item in self.tofit:
+            error = item + '_err'
+            w = np.where(self.table[error] >= 0.)
+            self.table[error][w] = np.sqrt(self.table[error][w]**2. + (
+                self.table[item][w]*modelerror)**2.)
 
     def generate_mock(self, fits):
         """Replaces the actual observations with a mock catalogue. It is
@@ -241,7 +252,7 @@ class ObservationsManagerVirtual(object):
 
         # We set the other class members to None as they do not make sense in
         # this situation
-        self.errors = None
+        self.bands_err = None
         self.table = None
 
     def __len__(self):