some tweaks to allow Opx equilibrium + testing PyPI for Diadfit issues

src/Thermobar/_version.py

@@ -5,4 +5,4 @@
 # 1) we don't load dependencies by storing it in __init__.py
 # 2) we can import it in setup.py for the same reason
 # 3) we can import it into your module
-__version__ = '1.0.45dev'
+__version__ = '1.0.46'

src/Thermobar/import_export.py

@@ -307,7 +307,7 @@ def import_lepr_file(filename):
 
 
 # Loading Excel, returns a disctionry
-def import_excel(file_name, sheet_name,  path=None, sample_label=None, GEOROC=False, suffix=None):
+def import_excel(file_name, sheet_name,  path=None, sample_label=None, GEOROC=False, suffix=None, df=None):
     '''
     Import excel sheet of oxides in wt%, headings should be of the form SiO2_Liq (for the melt/liquid), SiO2_Ol (for olivine comps), SiO2_Cpx (for clinopyroxene compositions). Order doesn't matter
 
@@ -321,6 +321,9 @@ def import_excel(file_name, sheet_name,  path=None, sample_label=None, GEOROC=Fa
     filename: str
         specifies the file name (e.g., Python_OlLiq_Thermometers_Test.xlsx)
 
+    OR
+    enter a dataframe instead of an excel file.
+
     Optional:
 
     path: provide a pathlib path to where the file is stored
@@ -344,25 +347,30 @@ def import_excel(file_name, sheet_name,  path=None, sample_label=None, GEOROC=Fa
         Amps=pandas dataframe of amphibole oxides
         Sps=pandas dataframe of spinel oxides
     '''
-    if path is not None:
-        file_path = Path(path) / file_name
-    else:
-        file_path = Path(file_name)
 
-    # Convert to string if needed
-    if isinstance(file_path, Path):
-        file_path = str(file_path)
+    if df is None:
 
-    # Check the file extension and read the file accordingly
-    if file_path.endswith('.csv'):
-        my_input = pd.read_csv(file_path)
-    elif file_path.endswith(('.xls', '.xlsx')):
-        if sheet_name is not None:
-            my_input = pd.read_excel(file_path, sheet_name=sheet_name)
+        if path is not None:
+            file_path = Path(path) / file_name
         else:
-            my_input = pd.read_excel(file_path)
+            file_path = Path(file_name)
+
+        # Convert to string if needed
+        if isinstance(file_path, Path):
+            file_path = str(file_path)
+
+        # Check the file extension and read the file accordingly
+        if file_path.endswith('.csv'):
+            my_input = pd.read_csv(file_path)
+        elif file_path.endswith(('.xls', '.xlsx')):
+            if sheet_name is not None:
+                my_input = pd.read_excel(file_path, sheet_name=sheet_name)
+            else:
+                my_input = pd.read_excel(file_path)
+        else:
+            raise ValueError(f"Unsupported file extension: {Path(file_path).suffix}")
     else:
-        raise ValueError(f"Unsupported file extension: {Path(file_path).suffix}")
+        my_input=df
 
 
     if any(my_input.columns.str.startswith(' ')):
@@ -437,11 +445,16 @@ def import_excel(file_name, sheet_name,  path=None, sample_label=None, GEOROC=Fa
 
 
  #   myLabels=my_input.Sample_ID
+    duplicates = df_ideal_exp.columns[df_ideal_exp.columns.duplicated()]
+
+    # If duplicates are found, return them to the user
+    if not duplicates.empty:
+        print("Duplicate columns found:", duplicates)
+        return "Duplicate columns detected. Please handle them before reindexing."
 
+    # Proceed with reindexing if no duplicates are found
     Experimental_press_temp1 = my_input.reindex(df_ideal_exp.columns, axis=1)
-# This deals with the fact almost everyone will enter as FeO, but the code uses FeOt for these minerals.
-# E.g., if users only enter FeO (not FeOt and Fe2O3), allocates a FeOt
-# column. If enter FeO and Fe2O3, put a FeOt column
+
 
 
     if GEOROC is True:

src/Thermobar/mineral_equilibrium.py

@@ -305,6 +305,87 @@ def calculate_eq_ol_content(liq_comps, Kd_model, ol_comps=None, T=None, P=None,
 
         return Kd_out
 
+## Same for Orhopyroxene
+def calculate_eq_px_content(liq_comps,
+Fe3Fet_Liq=None, px='Opx'):
+    '''calculates equilibrium pyroxene contents based on inputtted liquid compositions.
+
+
+   Parameters
+    -------
+
+    liq_comps: pandas.DataFrame
+        Liquid compositions with column headings SiO2_Ol, MgO_Ol etc.
+
+    px: 'Opx' or 'Cpx'
+
+    Fe3FeT: optional, float or int.
+        overwrites Fe3Fet_Liq in liq_comps DataFrame
+
+
+
+    Returns
+    -------
+    pandas DataFrame
+        returns equilibrium Px Mg#s (+- sigma) from Putirka 2008
+
+    '''
+    liq_comps_c=liq_comps.copy()
+    if Fe3Fet_Liq is not None:
+        liq_comps_c['Fe3Fet_Liq'] = Fe3Fet_Liq
+
+
+    liq = calculate_anhydrous_cat_fractions_liquid(liq_comps_c)
+    Mgno = liq['Mg_Number_Liq_Fe3']
+    Mgno_noFe3 = liq['Mg_Number_Liq_NoFe3']
+
+
+
+
+    if px == 'Opx':
+
+        # These values are 0.29+0-.06, which is from Putirka, He also gives an expression in terms of the si content of the liquid.
+
+        Eq_023 = 1 / ((0.23 / Mgno) + (1 - 0.23))
+        Eq_029 = 1 / ((0.29 / Mgno) + (1 - 0.29))
+        Eq_035 = 1 / ((0.35 / Mgno) + (1 - 0.35))
+
+
+        # Or calculating as a function of the Si content.
+        cat_frac = calculate_anhydrous_cat_fractions_liquid(liq_comps_c)
+        Si_mean_frac = np.nanmean(cat_frac['Si_Liq_cat_frac'])
+        Kd = 0.4805 - 0.3733 * Si_mean_frac
+        Eq_Opx = 1 / ((Kd / Mgno) + (1 - Kd))
+        Kd_p_1_s = Kd + 0.06
+        Kd_m_1_s = Kd - 0.06
+        Eq_Opx_p1sigma = 1 / ((Kd_p_1_s / Mgno) + (1 - Kd_p_1_s))
+        Eq_Opx_m1sigma = 1 / ((Kd_m_1_s / Mgno) + (1 - Kd_m_1_s))
+
+
+        Kd_out= pd.DataFrame(data={'Kd_XSi_P2008': Kd,
+        'Eq_Opx_Mg# (Kd_XSi_P2008)': Eq_Opx,
+         'Eq_Opx_Mg# (Kd_XSi_P2008)+0.06': Eq_Opx_p1sigma,
+        'Eq_Opx_Mg# (Kd_XSi_P2008)-0.06': Eq_Opx_m1sigma,
+        'Eq_Opx_Mg# (Kd=0.23)': Eq_023,
+        'Eq_Opx_Mg# (Kd=0.29)': Eq_029,
+        'Eq_Opx_Mg# (Kd=0.35)': Eq_035
+
+        })
+
+
+
+
+
+        Kd_out.insert(0, 'Mg#_Liq_Fe2', Mgno)
+        Kd_out.insert(1, 'Mg#_Liq_Fet', Mgno_noFe3)
+
+
+        return Kd_out
+
+    if px == 'Cpx':
+        raise TypeError('Penny still needs to add this, if you need it , please message me!')
+
+
 
 def calculate_ol_rhodes_diagram_lines(
         Min_Mgno, Max_Mgno, KdMin=None, KdMax=None):