Merge pull request #14 from Morisset/devel

1.1.15

README.rst

@@ -73,6 +73,7 @@ This project is partly supported by grants DGAPA/PAPIIT-107215 and CONACyT-CB201
 PyNeb uses part of Chiantipy:
 
 * Utility functions, many for reading the CHIANTI database files:
+
 Copyright 2009, 2010 Kenneth P. Dere
 This software is distributed under the terms of the GNU General Public License that is found in the LICENSE file
 

docs/Notebooks/PyNeb_manual_7b.ipynb

@@ -257,7 +257,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,

docs/Notebooks/PyNeb_manual_8.ipynb

@@ -221,7 +221,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,

pyneb/__init__.py

@@ -27,11 +27,12 @@
 from .utils.manage_atomic_data import _ManageAtomicData
 atomicData = _ManageAtomicData()
 
-atomicData.defaultDict = 'PYNEB_20_01'
+atomicData.defaultDict = 'PYNEB_21_01'
 atomicData.resetDataFileDict()
 
 from .core.pynebcore import Atom, RecAtom, getAtomDict, getRecEmissivity, EmissionLine, Observation, \
     parseLineLabel, isValid
+#from .core.pipeline import PipeLine
 from .core.icf import ICF 
 from .core.diags import Diagnostics, diags_dict
 from .core.emisGrid import EmisGrid, getEmisGridDict

pyneb/atomic_data/deprecated/fe_iii_coll_Q96.dat

@@ -567,5 +567,5 @@
 *** SPECTRUM 3
 *** N_LEVELS 34
 *** GSCONFIG d6
-*** SOURCE Was wrogly refered to Quinet 1996. Data are actually a subset of Z96
+*** SOURCE Was wrongly referred to Quinet 1996. Data are actually a subset of Z96
 *** NOTE Collision strengths

pyneb/atomic_data/he_i_rec_P91.func

@@ -1,10 +1,10 @@
 PEQ1991
 SOURCE Pequignot, Petitjean & Boisson, 1991, AandA, 251, 680
-4471  447.1  A 0.429 -0.530  1.505  0.779 0.790 A 0.135
-4713  471.3  A 0.019 -0.518 -0.045  0.951 0.626 A 0.013
-5876  587.6  A 1.323 -0.696  1.683  0.667 1.000 A 0.493
-3889  388.9  A 0.511 -0.489  0.719  0.530 0.898 A 0.267
-7065  706.5  A 0.070 -0.509 -0.010 -0.263 1.000 A 0.071
-10830 1083.0 A 0.796 -0.525  0.148  0.719 1.000 A 0.693
-4922  492.2  A 0.135 -0.540  1.505  0.779 0.740 A 0.040
-7281  728.1  A 0.036 -0.503  0.165  0.614 1.000 A 0.031
+4471.  447.1  A 0.429 -0.530  1.505  0.779 0.790 A 0.135
+4713.  471.3  A 0.019 -0.518 -0.045  0.951 0.626 A 0.013
+5876.  587.6  A 1.323 -0.696  1.683  0.667 1.000 A 0.493
+3889.  388.9  A 0.511 -0.489  0.719  0.530 0.898 A 0.267
+7065.  706.5  A 0.070 -0.509 -0.010 -0.263 1.000 A 0.071
+10830. 1083.0 A 0.796 -0.525  0.148  0.719 1.000 A 0.693
+4922.  492.2  A 0.135 -0.540  1.505  0.779 0.740 A 0.040
+7281.  728.1  A 0.036 -0.503  0.165  0.614 1.000 A 0.031

pyneb/atomic_data/o_ii_rec_P91.func

@@ -18,4 +18,9 @@ SOURCE Pequignot, Petitjean & Boisson, 1991, AandA, 251, 680
 4341+ 434.1 A 0.633 -0.609 1.683 0.667 1.000 C 1.766
 4341+ 434.1 B 0.792 -0.620 1.683 0.667 1.000 C 2.244
 3736+ 373.6 A 0.047 -0.506 0.624 0.681 1.000 C 0.153
-3736+ 373.6 B 0.255 -0.565 1.683 0.667 1.000 C 0.669
+3736+ 373.6 B 0.255 -0.565 1.683 0.667 1.000 C 0.669
+3727+ 372.7 A 1.175 -0.6182 0.0097 -0.2717 1.000 B 0.000
+3727+ 372.7 B 1.175 -0.6182 0.0097 -0.2717 1.000 B 0.000
+7325+ 732.5 A 0.657 -0.6166 0.00 1.000 0.80 B 0.000
+7325+ 732.5 B 0.657 -0.6166 0.00 1.000 0.80 B 0.000
+

pyneb/core/continuum.py

@@ -77,11 +77,11 @@ def make_cont_Ercolano(self, tem, case, wl):
                                   4.6, 4.7, 4.8, 4.9, 5. ])
             D = np.loadtxt(ROOT_DIR + '/' + 'atomic_data/coeff_ercolano_He2.txt')
         else:
-            print('Invalid case {0}'.format(case))
-            return None
+            self.log_.warn('Invalid case {0}'.format(case), calling='Continuum.make_cont_Ercolano')
+            return np.nan
         if (tem < np.min(tab_T)).any() or (tem > np.max(tab_T)).any():
-            print('Invalid temperature {0}'.format(tem))
-            return None
+            self.log_.warn('Invalid temperature {0}'.format(tem), calling='Continuum.make_cont_Ercolano')            
+            return np.nan
 
         BE_E_Ry = D[:,1]
         BE_E_erg = BE_E_Ry * CST.RYD_erg

pyneb/core/diags.py

@@ -25,8 +25,8 @@
 diags_dict['[OI] 5577/6300'] = ('O1', 'L(5577)/L(6300)', 'RMS([E(6300), E(5577)])')
 diags_dict['[OI] 5577/6300+'] = ('O1', 'L(5577)/(L(6300)+L(6364))', 'RMS([E(6300)*L(6300)/(L(6300)+L(6364)), E(6364)*L(6364)/(L(6300)+L(6364)), E(5577)])')
 diags_dict['[OII] 3726/3729'] = ('O2', 'L(3726)/L(3729)', 'RMS([E(3729), E(3726)])')
-diags_dict['[OII] 3727+/7325+c'] =  ('O2', '(B("3727A+"))/(B("7319A+")+B("7330A+"))',
-            'RMS([BE("7319A+")*B("7319A+")/(B("7319A+")+B("7330A+")), BE("7330A+")*B("7330A+")/(B("7319A+")+B("7330A+")), BE("3727A+")])')
+#diags_dict['[OII] 3727+/7325+c'] =  ('O2', '(B("3727A+"))/(B("7319A+")+B("7330A+"))',
+#            'RMS([BE("7319A+")*B("7319A+")/(B("7319A+")+B("7330A+")), BE("7330A+")*B("7330A+")/(B("7319A+")+B("7330A+")), BE("3727A+")])')
 diags_dict['[OII] 3727+/7325+'] = ('O2', '(L(3726)+L(3729))/(B("7319A+")+B("7330A+"))',
               'RMS([E(3726)*L(3726)/(L(3726)+L(3729)), E(3729)*L(3729)/(L(3726)+L(3729)),BE("7319A+")*B("7319A+")/(B("7319A+")+B("7330A+")),BE("7330A+")*B("7330A+")/(B("7319A+")+B("7330A+"))])')
 #diags_dict['[OII] 3727+/7325+'] = ('O2', '(L(3726)+L(3729))/(B("7325A+"))', 'RMS([E(3726)*L(3726)/(L(3726)+L(3729)), E(3729)*L(3729)/(L(3726)+L(3729)),BE("7325A+")])')
@@ -788,17 +788,20 @@ def B(label, I=I, L=L):
                     else:
                         self.ANN = ANN
                 # set the test values to the one we are looking for
-                self.ANN.set_test(np.array((value_tem, value_den)).T)
+                shape = value_tem.shape
+                self.ANN.set_test(np.array((value_tem.ravel(), value_den.ravel())).T)
                 # predict the result and denormalize them
                 self.ANN.predict()
                 if self.ANN.isfin is None:
                     tem = self.ANN.pred[:,0]*1e4
                     den = 10**self.ANN.pred[:,1]
                 else:
-                    tem = np.zeros_like(value_tem) * -10
+                    tem = np.zeros_like(value_tem.ravel()) * -10
                     tem[self.ANN.isfin] = self.ANN.pred[:,0]*1e4
-                    den = np.zeros_like(value_tem) * -10
+                    den = np.zeros_like(value_tem.ravel()) * -10
                     den[self.ANN.isfin] = 10**self.ANN.pred[:,1]
+                tem = np.reshape(tem, shape)
+                den = np.reshape(den, shape)
                 if limit_res:
                     mask = (tem<tem_min) | (tem>tem_max)
                     tem[mask] = np.nan
@@ -862,4 +865,38 @@ def getDiagLimits(self, diag):
         LDR = atom.getLowDensRatio(to_eval = to_eval)
         return(np.sort((LDR, HDR)))
 
-
+    def eval_diag(self, label):
+        """
+
+        Parameters
+        ----------
+        label : diagnostic label(e.g. '[OIII] 4363/5007')
+            A string of a key included in the self.diags dictionnary.
+
+        Returns
+        -------
+        np.array
+            The evaluation of the diagnostic corresponding to the label.
+
+        """
+        if label not in self.diags:
+            self.log_.error('Unknown diagnostic: {}'.format(label), calling='eval_diag')
+        atom, diag_expression, error = self.diags[label]
+        sym, spec, rec = parseAtom2(atom)
+        def I(i, j):
+            wave = atom.wave_Ang[i - 1, j - 1]
+            corrIntens = obs.getLine(sym, spec, wave).corrIntens
+            return corrIntens
+        def L(wave):
+            corrIntens = obs.getLine(sym, spec, wave).corrIntens
+            return corrIntens
+        def B(label):
+            full_label = atom + '_' + label
+            corrIntens = obs.getLine(label=full_label).corrIntens
+            return corrIntens
+        def S(label):
+            full_label = atom + '_' + label + 'A'
+            corrIntens = obs.getLine(label=full_label).corrIntens
+            return corrIntens
+        diag_value = eval(diag_expression)
+        return diag_value