Typo

fsl_mrs_mce/mc_in.py

@@ -1,4 +1,4 @@
-# mc_sim.py - Helpers for Monte-Carlo style simulations
+# mc_in.py - Helpers for Monte-Carlo style simulations
 #
 # Author: Konstantin E Bosbach <konstantin.bosbach@mars.uni-freiburg.de>
 
@@ -29,11 +29,13 @@ def load_config(input_folder="input/", section="default"):
         print(f"No {configFilePath} provided.")
 
 
-def conc_df_from_file(input_path="input/", foundation="vivo_average"):
+def conc_df_from_file(input_path="input/", foundation="vivo_average",
+                      include_molecules=[], save_df=True):
     sections = load_config(input_path, "")
     """Generates concentration dataframe for mc method.
     Supports different variation types (absolute/delta/relative)
-    Returns data_frame of different concentrations"""
+    Returns data_frame of different concentrations.
+    include_molecules needed for option some_molecules"""
     # Load all relevant sections
     list_parser_parameter = []
 
@@ -43,12 +45,36 @@ def conc_df_from_file(input_path="input/", foundation="vivo_average"):
 
     # Load foundation file, a line with e.g. in-vivo averages
     # The code expects a one-line-foundation.
+    molecule_names = ['Ala', 'Asc', 'Asp', 'Cr', 'GABA', 'GPC', 'GSH',
+                      'Glc', 'Gln', 'Glu', 'Ins', 'Lac', 'NAA', 'NAAG',
+                      'PCho', 'PCr', 'PE', 'Scyllo', 'Tau',
+                      'mm', 'Glu+Gln', 'GPC+PCho', 'Cr+PCr',
+                      'Glc+Tau', 'NAA+NAAG']
+
     if foundation == "vivo_average":
         try:
             df_foundation = pd.read_csv(
                 "basis/fit_conc_result.csv").mean().to_frame().transpose()
         except:
             print("No basis/fit_conc_result.csv file supplied")
+    # Sets all initial molecules, including some groups, to 0
+    if foundation == "flat":
+        try:
+            df_foundation = pd.read_csv(
+                "basis/fit_conc_result.csv").mean().to_frame().transpose()
+            for molecule in molecule_names:
+                df_foundation[molecule] = 0
+        except:
+            print("No basis/fit_conc_result.csv file supplied")
+    if foundation == "some_molecules":
+        try:
+            df_foundation = pd.read_csv(
+                "basis/fit_conc_result.csv").mean().to_frame().transpose()
+            for molecule in molecule_names:
+                if molecule not in include_molecules:
+                    df_foundation[molecule] = 0
+        except:
+            print("No basis/fit_conc_result.csv file supplied")
     else:
         print("Only foundation mode vivo_average not chosen")
 
@@ -92,4 +118,7 @@ def conc_df_from_file(input_path="input/", foundation="vivo_average"):
         df_conc[parameter_name] = parameter_values
         i = i+1
 
+    if save_df:
+        df_conc.to_csv(str(input_path+"df_conc.csv"))
+
     return df_conc