Further tweaked MC stuff

docs/index.rst

@@ -23,6 +23,8 @@ Welcome to PySulfSat's documentation!
 
    youtube
 
+    %
+
 .. toctree::
    :maxdepth: 2
    :caption: Data Input Options
@@ -74,6 +76,7 @@ Welcome to PySulfSat's documentation!
 
    Examples/S6_S2_Corrections/S6_S2_Corrections_Nash_Jugo_Kleinsasser
    Examples/S6_S2_Corrections/CS6_S6ST_Correction
+   Examples/S6St_Testing/CalcS6ST_Muth
 
    %
 

src/PySulfSat/_version.py

@@ -5,5 +5,5 @@
 # 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__ = '0.0.12'
+__version__ = '0.0.13'
 

src/PySulfSat/error_prop.py

@@ -9,8 +9,10 @@
 
 from PySulfSat.core_calcs import *
 
+
+
 def add_noise_1var(var, error_var,
-error_type="Abs", error_dist="normal", N_dup=1000, sample_i=0):
+error_type="Abs", error_dist="normal", N_dup=1000, sample_i=0, df_values=None):
 
     """ Takes 1 row of pd series or a float, returns 1000 duplicates following specified error position
     """
@@ -39,9 +41,12 @@ def add_noise_1var(var, error_var,
 
     var_with_noise=Noise_to_add_var+df_c['var'].iloc[sample_i]
 
+
+
     return var_with_noise
 
-def add_noise_series(var, error_var,  error_type="Abs", error_dist="normal", N_dup=1000, Sample_ID=None, no_noise=False):
+
+def add_noise_series(var, error_var,  error_type="Abs", error_dist="normal", N_dup=1000, Sample_ID=None, no_noise=False, df_values=None):
 
 
 
@@ -98,11 +103,19 @@ def add_noise_series(var, error_var,  error_type="Abs", error_dist="normal", N_d
 
     return All_outputs
 
+def duplicate_dataframe(df, N_dup=1000):
+    df_values=df
+    Dupdf = pd.DataFrame(np.repeat(df_values.values,
+    N_dup, axis=0))
+    Dupdf.columns = df_values.columns
+
+    return Dupdf
+
 def add_noise_2_dataframes(df_values, df_noise,
         error_type="Abs", error_dist="normal", N_dups=10):
 
-    df1=df_values
-    df2=df_noise
+    df1=df_values.copy()
+    df2=df_noise.copy()
 
     #def create_noise_2df(df1, df2, error_type="Abs", error_dist="normal", N_dup=3):
 
@@ -138,7 +151,10 @@ def add_noise_2_dataframes(df_values, df_noise,
     df_noisy
 
     # Get sample names
-    s=df1['Sample_ID']
+    if 'Sample_ID' in df1.columns:
+        s=df1['Sample_ID']
+    else:
+        s=df1.index
     s_repeated = pd.Series(np.repeat(s.values, N_dups))
 
     # Tile the repeated values to get the end-on-end repetition

src/PySulfSat/import_data.py

@@ -124,3 +124,64 @@ def import_data(filename, sheet_name=None, Petrolog=False, MELTS=False, sample_l
     return out
 
 
+
+df_ideal_liq_noise = pd.DataFrame(columns=['SiO2_Liq_Err', 'TiO2_Liq_Err', 'Al2O3_Liq_Err',
+'FeOt_Liq_Err', 'MnO_Liq_Err', 'MgO_Liq_Err', 'CaO_Liq_Err', 'Na2O_Liq_Err', 'K2O_Liq_Err',
+'P2O5_Liq_Err', 'H2O_Liq_Err', 'Fe3Fet_Liq_Err', 'Ni_Liq_ppm_Err', 'Cu_Liq_ppm_Err'])
+
+def import_data_noise(filename, sheet_name=None, sample_label=None):
+
+    if 'csv' in filename:
+        my_input = pd.read_csv(filename)
+
+
+
+
+    if 'xls' in filename:
+        if sheet_name is not None:
+            my_input = pd.read_excel(filename, sheet_name=sheet_name)
+            #my_input[my_input < 0] = 0
+        else:
+            my_input = pd.read_excel(filename)
+            #my_input[my_input < 0] = 0
+
+
+
+    my_input_c = my_input.copy()
+
+    if "Sample_ID_Liq" not in my_input_c:
+        my_input_c['Sample_ID_Liq'] = my_input.index
+
+
+
+    if any(my_input.columns.str.contains("FeO_")) and (all(my_input.columns.str.contains("FeOt_")==False)):
+        raise ValueError("No FeOt found. You've got a column heading with FeO. To avoid errors based on common EPMA outputs"
+    " thermobar only recognises columns with FeOt for all phases except liquid"
+    " where you can also enter a Fe3Fet_Liq heading used for equilibrium tests")
+
+    if any(my_input.columns.str.contains("Fe2O3_")) and (all(my_input.columns.str.contains("FeOt_")==False)):
+        raise ValueError("No FeOt column found. You've got a column heading with Fe2O3. To avoid errors based on common EPMA outputs"
+        " thermobar only recognises columns with FeOt for all phases except liquid"
+        " where you can also enter a Fe3Fet_Liq heading used for equilibrium tests")
+
+    if any(my_input.columns.str.contains("FeOT_")) and (all(my_input.columns.str.contains("FeOt_")==False)):
+        raise ValueError("No FeOt column found. You've got a column heading with FeOT. Change to a lower case t")
+
+
+
+    myLiquids1 = my_input_c.reindex(df_ideal_liq_noise.columns, axis=1).fillna(0)
+    myLiquids1 = myLiquids1.apply(pd.to_numeric, errors='coerce').fillna(0)
+    myLiquids1[myLiquids1 < 0] = 0
+    print('We have replaced all missing liquid oxides and strings with zeros. ')
+
+    cols2=myLiquids1.columns
+    #my_input_c=my_input.copy()
+    for col in cols2:
+        if col in my_input_c.columns:
+            my_input_c=my_input_c.drop(columns=col)
+
+    out=pd.concat([myLiquids1, my_input_c], axis=1)
+    return out
+
+
+

src/PySulfSat/s6_corrections.py

@@ -119,7 +119,9 @@ def calculate_S6St_Nash2019(T_K, Fe3Fet_Liq):
     '''
     # First, calculate Fe3/Fe2 from Fe3/Fet
     Fe3Fe2=Fe3Fet_Liq/(1-Fe3Fet_Liq)
-    log_Fe3Fe2=np.log10(Fe3Fe2)
+    #print(Fe3Fe2)
+    log_Fe3Fe2=np.log10(Fe3Fe2.astype(float))
+
 
     log_S6S2=8*log_Fe3Fe2 + 8.7436*10**6/(T_K**2) - 27703/T_K + 20.273
     S6S2=10**(log_S6S2)