MR: Updating readthedocs and correcting stuff in plotting and nested_…

…sampling

ForMoSA/nested_sampling/nested_modif_spec.py

@@ -448,7 +448,7 @@ def modif_spec(global_params, theta, theta_index,
         else: # If you want 1 common rv for all observations
             if global_params.rv != "NA":
                 if global_params.rv[0] == "constant":
-                    alpha_picked = float(global_params.rv[1])
+                    rv_picked = float(global_params.rv[1])
                 else:
                     ind_theta_rv = np.where(theta_index == 'rv')
                     rv_picked = theta[ind_theta_rv[0][0]]

ForMoSA/plotting/plotting_class.py

@@ -272,7 +272,7 @@ def _get_posteriors(self):
                     tot_list_param_title.append(extra_parameters[2][1] + fr'$_{indobs}$' + ' ' + extra_parameters[2][2])
                     theta_index.append(f'alpha_{indobs}')
         else: # If you want 1 common alpha for all observations
-            if self.global_params.alpha != 'NA' and self.global_params.alpha != 'constant':
+            if self.global_params.alpha != 'NA' and self.global_params.alpha[0] != 'constant':
                 tot_list_param_title.append(extra_parameters[2][1] + ' ' + extra_parameters[2][2])
                 theta_index.append('alpha')
         if len(self.global_params.rv) > 3: # If you want separate rv for each observations
@@ -282,7 +282,7 @@ def _get_posteriors(self):
                     tot_list_param_title.append(extra_parameters[3][1] + fr'$_{indobs}$' + ' ' + extra_parameters[3][2])
                     theta_index.append(f'rv_{indobs}')
         else: # If you want 1 common rv for all observations
-            if self.global_params.rv != 'NA' and self.global_params.rv != 'constant':
+            if self.global_params.rv != 'NA' and self.global_params.rv[0] != 'constant':
                 tot_list_param_title.append(extra_parameters[3][1] + ' ' + extra_parameters[3][2])
                 theta_index.append('rv')
         if len(self.global_params.vsini) > 4: # If you want separate vsini for each observations
@@ -292,7 +292,7 @@ def _get_posteriors(self):
                     tot_list_param_title.append(extra_parameters[5][1] + fr'$_{indobs}$' + ' ' + extra_parameters[5][2])
                     theta_index.append(f'vsini_{indobs}')
         else: # If you want 1 common vsini for all observations
-            if self.global_params.vsini != 'NA' and self.global_params.vsini != 'constant':
+            if self.global_params.vsini != 'NA' and self.global_params.vsini[0] != 'constant':
                 tot_list_param_title.append(extra_parameters[5][1] + ' ' + extra_parameters[5][2])
                 theta_index.append('vsini')
         if len(self.global_params.ld) > 3: # If you want separate ld for each observations
@@ -302,7 +302,7 @@ def _get_posteriors(self):
                     tot_list_param_title.append(extra_parameters[6][1] + fr'$_{indobs}$' + ' ' + extra_parameters[6][2])
                     theta_index.append(f'ld_{indobs}')
         else: # If you want 1 common vsini for all observations
-            if self.global_params.ld != 'NA' and self.global_params.ld != 'constant':
+            if self.global_params.ld != 'NA' and self.global_params.ld[0] != 'constant':
                 tot_list_param_title.append(extra_parameters[6][1] + ' ' + extra_parameters[6][2])
                 theta_index.append('ld')
 

RELEASE_NOTES.txt

@@ -390,4 +390,20 @@ Comments:
       - New approach in the lsq function, we can now use the lsq in each sub wavelength separatly (eg. '1.4, 1.5', '1.6, 1.7', '1.8, 1.9' ...) and merge the results into a single array to compute the loglikelihood on one array only. This gives the advantage of limiting flux error calibration that can arrise between order for data such as CRIRES, HiRISE ... and being fast at the same time. Previously, the use had to define separated windows in 'wave_fit' (eg : '1.4, 1.5', '1.6, 1.7', '1.8, 1.9' ...) and one loglikelihood one computed for each of these windows. Now the user has to define separated windows in the format '1.4, 1.5 / 1.6, 1.7 / 1.8, 1.9 / ...' 
 
 Tests tha have been done to checkup the changes:
-     - High resolution datasets (HiRISE, CRIRES)
+     - High resolution datasets (HiRISE, CRIRES)
+
+
+- - -
+
+26/09/2024
+
+Matthieu Ravet
+
+Comments:
+      - Updating / correting the readthedocs
+      - Correction of the rv input loop if you want to set it to constant during the ns
+      - Correction of the plotting function (for constant extra grid and for the custom resolution grid)
+
+
+Tests tha have been done to checkup the changes:
+     - Test with constant priors on the rv

docs/_build/html/_modules/ForMoSA/nested_sampling/nested_modif_spec.html

@@ -243,7 +243,7 @@ <h1>Source code for ForMoSA.nested_sampling.nested_modif_spec</h1><div class="hi
     <span class="k">if</span> <span class="n">analytic</span> <span class="o">==</span> <span class="s1">&#39;no&#39;</span><span class="p">:</span>
         <span class="n">r_picked</span> <span class="o">*=</span> <span class="n">u</span><span class="o">.</span><span class="n">Rjup</span>
         <span class="n">d_picked</span> <span class="o">*=</span> <span class="n">u</span><span class="o">.</span><span class="n">pc</span>
-        <span class="n">ck</span> <span class="o">=</span> <span class="n">alpha</span> <span class="o">*</span> <span class="p">(</span><span class="n">r_picked</span><span class="o">.</span><span class="n">value</span><span class="o">/</span><span class="n">d_picked</span><span class="o">.</span><span class="n">value</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span>
+        <span class="n">ck</span> <span class="o">=</span> <span class="n">alpha</span> <span class="o">*</span> <span class="p">(</span><span class="n">r_picked</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">u</span><span class="o">.</span><span class="n">m</span><span class="p">)</span><span class="o">.</span><span class="n">value</span><span class="o">/</span><span class="n">d_picked</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">u</span><span class="o">.</span><span class="n">m</span><span class="p">)</span><span class="o">.</span><span class="n">value</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span>
     <span class="c1"># Calculation of the dilution factor ck analytically</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flx_obs_spectro</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
@@ -551,7 +551,7 @@ <h1>Source code for ForMoSA.nested_sampling.nested_modif_spec</h1><div class="hi
         <span class="k">else</span><span class="p">:</span> <span class="c1"># If you want 1 common rv for all observations</span>
             <span class="k">if</span> <span class="n">global_params</span><span class="o">.</span><span class="n">rv</span> <span class="o">!=</span> <span class="s2">&quot;NA&quot;</span><span class="p">:</span>
                 <span class="k">if</span> <span class="n">global_params</span><span class="o">.</span><span class="n">rv</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="s2">&quot;constant&quot;</span><span class="p">:</span>
-                    <span class="n">alpha_picked</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">global_params</span><span class="o">.</span><span class="n">rv</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
+                    <span class="n">rv_picked</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">global_params</span><span class="o">.</span><span class="n">rv</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
                 <span class="k">else</span><span class="p">:</span>
                     <span class="n">ind_theta_rv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">theta_index</span> <span class="o">==</span> <span class="s1">&#39;rv&#39;</span><span class="p">)</span>
                     <span class="n">rv_picked</span> <span class="o">=</span> <span class="n">theta</span><span class="p">[</span><span class="n">ind_theta_rv</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]]</span>