moved _parse_species_list function to tardis.io.util.py

.mailmap

@@ -283,3 +283,5 @@ Israel Roldan <israel.alberto.rv@gmail.com> AirvZxf <israel.alberto.rv@gmail.com
 Israel Roldan <israel.alberto.rv@gmail.com> airv_zxf <israel.alberto.rv@gmail.com>
 
 Michael Zingale <michael.zingale@stonybrook.edu>
+
+Rudraksh Nalbalwar <nalbalwarrudraksh@gmail.com>

tardis/io/util.py

@@ -138,6 +138,51 @@ def yaml_load_file(filename, loader=yaml.Loader):
         return yaml.load(stream, Loader=loader)
 
 
+def _parse_species_list(self, species_list, packets_mode, nelements=None):
+        """
+        Parse user requested species list and create list of species ids to be used.
+
+        Parameters
+        ----------
+        species_list : list of species to plot
+            List of species (e.g. Si II, Ca II, etc.) that the user wants to show as unique colours.
+            Species can be given as an ion (e.g. Si II), an element (e.g. Si), a range of ions
+            (e.g. Si I - V), or any combination of these (e.g. species_list = [Si II, Fe I-V, Ca])
+        packets_mode : str, optional
+            Packet mode, either 'virtual' or 'real'. Default is 'virtual'.
+        nelements : int, optional
+            Number of elements to include in plot. The most interacting elements are included. If None, displays all elements.
+
+        Raises
+        ------
+        ValueError
+            If species list contains invalid entries.
+
+        """
+        from tardis.util.base import atomic_number2element_symbol  
+        self.sdec_plotter._parse_species_list(species_list)
+        self._species_list = self.sdec_plotter._species_list
+        self._species_mapped = self.sdec_plotter._species_mapped
+        self._keep_colour = self.sdec_plotter._keep_colour
+
+        if nelements:
+            interaction_counts = (
+                self.data[packets_mode]
+                .packets_df_line_interaction["last_line_interaction_species"]
+                .value_counts()
+            )
+            interaction_counts.index = interaction_counts.index // 100
+            element_counts = interaction_counts.groupby(
+                interaction_counts.index
+            ).sum()
+            top_elements = element_counts.nlargest(nelements).index
+            top_species_list = [
+                atomic_number2element_symbol(element)
+                for element in top_elements
+            ]
+            self._parse_species_list(top_species_list, packets_mode)
+
+
 def traverse_configs(base, other, func, *args):
     """
     Recursively traverse a base dict or list along with another one

tardis/visualization/tools/liv_plot.py

@@ -99,49 +99,6 @@ def from_hdf(cls, hdf_fpath):
                 velocity,
             )
 
-    def _parse_species_list(self, species_list, packets_mode, nelements=None):
-        """
-        Parse user requested species list and create list of species ids to be used.
-
-        Parameters
-        ----------
-        species_list : list of species to plot
-            List of species (e.g. Si II, Ca II, etc.) that the user wants to show as unique colours.
-            Species can be given as an ion (e.g. Si II), an element (e.g. Si), a range of ions
-            (e.g. Si I - V), or any combination of these (e.g. species_list = [Si II, Fe I-V, Ca])
-        packets_mode : str, optional
-            Packet mode, either 'virtual' or 'real'. Default is 'virtual'.
-        nelements : int, optional
-            Number of elements to include in plot. The most interacting elements are included. If None, displays all elements.
-
-        Raises
-        ------
-        ValueError
-            If species list contains invalid entries.
-
-        """
-        self.sdec_plotter._parse_species_list(species_list)
-        self._species_list = self.sdec_plotter._species_list
-        self._species_mapped = self.sdec_plotter._species_mapped
-        self._keep_colour = self.sdec_plotter._keep_colour
-
-        if nelements:
-            interaction_counts = (
-                self.data[packets_mode]
-                .packets_df_line_interaction["last_line_interaction_species"]
-                .value_counts()
-            )
-            interaction_counts.index = interaction_counts.index // 100
-            element_counts = interaction_counts.groupby(
-                interaction_counts.index
-            ).sum()
-            top_elements = element_counts.nlargest(nelements).index
-            top_species_list = [
-                atomic_number2element_symbol(element)
-                for element in top_elements
-            ]
-            self._parse_species_list(top_species_list, packets_mode)
-
     def _make_colorbar_labels(self):
         """
         Generate labels for the colorbar based on species.