Changed iterative fit to only fit to multicomponent data.

2025-12-06 01:48:53 -06:00 · 2020-07-31 10:05:35 -06:00
parent 9fef8b78fb
commit 16382b0145
20 changed files with 2357 additions and 193 deletions
--- a/docs/Examples/iterative_fitter.py
+++ b/docs/Examples/iterative_fitter.py
@@ -22,7 +22,7 @@ ext_h0_filename = "../../data/jsons/min_h0_guess_ext_h0.txt"
 with open(ext_h0_filename) as file:
    ext_h0_dict = json.load(file)
 labeled_data = pd.read_csv("../../data/csvs/"
-                           "zeroes_removed_PC88A_HCL_NdPrCeLaDySmY.csv")
+                           "multicomponent_PC88A_HCL_NdPrCeLaDySmY.csv")
 exp_data = labeled_data.drop(labeled_data.columns[0], axis=1)
 xml_file = "PC88A_HCL_NdPrCeLaDySmY_w_pitzer.xml"
 lin_param_df = pd.read_csv("../../data/csvs"
@@ -237,8 +237,7 @@ while obj_diff1 > eps or obj_diff2 > eps:
    del(output_dict['rel_diff'][-1])
    output_dict['rel_diff'].append(rel_diff)
    output_df = pd.DataFrame(output_dict)
-    output_df.to_csv('outputs/iterative_fitter_output4.csv')
-    obj_diff1 = np.abs(output_dict['best_obj'][-1]-output_dict['best_obj'][-2])
+    output_df.to_csv('outputs/iterative_fitter_output_multicomponent.csv')
+    obj_diff1 = output_dict['best_obj'][-2]-output_dict['best_obj'][-1]
    if i > 2:
-        obj_diff2 = np.abs(
-            output_dict['best_obj'][-1] - output_dict['best_obj'][-3])
+        obj_diff2 = output_dict['best_obj'][-3] - output_dict['best_obj'][-1]
--- a/docs/Examples/iterative_fitter_eval_grapher.py
+++ b/docs/Examples/iterative_fitter_eval_grapher.py
@@ -2,15 +2,30 @@ import llepe
 import pandas as pd
 import numpy as np
 import json
-import matplotlib as plt
+import matplotlib.pyplot as plt
 import matplotlib
+import re
+
+
+def set_size(w, h, ax=None):
+    """ w, h: width, height in inches """
+    if not ax:
+        ax = plt.gca()
+    left = ax.figure.subplotpars.left
+    right = ax.figure.subplotpars.right
+    top = ax.figure.subplotpars.top
+    bottom = ax.figure.subplotpars.bottom
+    fig_width = float(w) / (right - left)
+    fig_height = float(h) / (top - bottom)
+    ax.figure.set_size_inches(fig_width, fig_height)
+

 font = {'family': 'sans serif',
        'size': 24}
 matplotlib.rc('font', **font)
-plt.rc('xtick', labelsize=18)
-plt.rc('ytick', labelsize=18)
-plt.rcParams['lines.linewidth'] = 4
+matplotlib.rc('xtick', labelsize=18)
+matplotlib.rc('ytick', labelsize=18)
+matplotlib.rcParams['lines.linewidth'] = 4
 matplotlib.rcParams['lines.markersize'] = 10


@@ -27,8 +42,8 @@ def mod_lin_param_df(lp_df, input_val, mini_species, mini_lin_param):
    return new_lp_df


-info_df = pd.read_csv('outputs/iterative_fitter_w_mse_output.csv')
-test_row = 3
+info_df = pd.read_csv('outputs/iterative_fitter_output4.csv')
+test_row = -1
 pitzer_params_filename = "../../data/jsons/min_h0_pitzer_params.txt"
 with open(pitzer_params_filename) as file:
    pitzer_params_dict = json.load(file)
@@ -112,57 +127,146 @@ estimator.set_custom_objects_dict({'lin_param_df': lin_param_df})
 estimator.update_custom_objects_dict(info_dict)
 estimator.update_xml(info_dict,
                     dependant_params_dict=dependant_params_dict)
-exp_data = estimator.get_exp_df()
-feed_cols = []
-for col in exp_data.columns:
-    if 'aq_i' in col:
-        feed_cols.append(col)
-exp_data['total_re'] = exp_data[feed_cols].sum(axis=1)
-label_list = []
-for index, row in exp_data[feed_cols].iterrows():
-    bool_list = list((row > 0).values)
-    label = ''
-    for species, el in zip(species_list, bool_list):
-        if el:
-            label = '{0}-{1}'.format(label, species)
-    label = label[1:]
-    label_list.append(label)
-r2s = ""
-for species in species_list:
-    # if species=='La':
-    # save_name = 'outputs' \
-    #             '/parity_iterative_fitter_{0}_org_eq'.format(species)
-    save_name = None
-    # fig, ax = estimator.parity_plot('{0}_org_eq'.format(species),
-    #                                 c_data='z_i',
-    #                                 c_label='Feed total RE '
-    #                                         'molarity (mol/L)',
-    #                                 print_r_squared=True,
-    #                                 save_path=save_name)
-    r2s += str(estimator.r_squared('{0}_org_eq'.format(species))) + ','
+compared_value = 'La_org_eq'
+plot_title = None
+legend = True
+predicted_dict = estimator.get_predicted_dict()
+exp_df = estimator.get_exp_df()
+pred = pd.DataFrame(predicted_dict)[compared_value].fillna(0).values
+meas = exp_df[compared_value].fillna(0).values
+name_breakdown = re.findall('[^_\W]+', compared_value)
+compared_species = name_breakdown[0]
+data_labels = list(labeled_data['label'])
+if compared_species == 'h':
+    feed_molarity = exp_df['h_i'].fillna(0).values
+elif compared_species == 'z':
+    feed_molarity = exp_df['z_i'].fillna(0).values
+else:
+    feed_molarity = exp_df[
+        '{0}_aq_i'.format(compared_species)].fillna(0).values
+combined_df = pd.DataFrame({'pred': pred,
+                            'meas': meas,
+                            'label': data_labels,
+                            'feed_molarity': feed_molarity})
+combined_df = combined_df[(combined_df['feed_molarity'] != 0)]
+meas = combined_df['meas'].values
+pred = combined_df['pred'].values

-    fig, ax = estimator.parity_plot('{0}_org_eq'.format(species),
-                                    data_labels=label_list,
-                                    print_r_squared=True,
-                                    save_path=save_name)
-    ax.legend(loc=4)
-pred_df = pd.DataFrame(estimator.get_predicted_dict())
-new_cols = []
-for col in pred_df.columns:
-    new_cols.append("pred_{0}".format(col))
-pred_df.columns = new_cols
-new_cols = ['label',
-            'h_i',
-            'h_eq',
-            'z_i',
-            'z_eq'
-            ]
-for species in species_list:
-    new_cols.append("{0}_aq_i".format(species))
-    new_cols.append("{0}_aq_eq".format(species))
-    new_cols.append("{0}_d_eq".format(species))
-labeled_data.columns = new_cols
-total_df = labeled_data.join(pred_df)
+min_data = np.min([pred, meas])
+max_data = np.max([pred, meas])
+min_max_data = np.array([min_data, max_data])
+
+if compared_species == 'h':
+    default_title = '$H^+$ eq. conc. (mol/L)'
+elif compared_species == 'z':
+    default_title = '{0} eq. conc. (mol/L)'.format(extractant_name)
+else:
+    phase = name_breakdown[1]
+    if phase == 'aq':
+        extracted_species_charge = extracted_species_charges[
+            extracted_species_list.index(
+                compared_species)]
+        default_title = '$%s^{%d+}$ eq. conc. (mol/L)' \
+                        % (compared_species, extracted_species_charge)
+    elif phase == 'd':
+        default_title = '{0} distribution ratio'.format(
+            compared_species)
+    else:
+        default_title = '{0} complex eq. conc. (mol/L)'.format(
+            compared_species)
+fig, ax = plt.subplots(figsize=(8, 6))
+
+if isinstance(data_labels, list):
+    # unique_labels = list(set(data_labels))
+    unique_labels = ['Li (1987)',
+                     'Kim (2012)',
+                     'Formiga (2016)',
+                     'Banda (2014)',
+                     ]
+    color_list = ['r', 'g', 'b', 'm']
+    marker_list = ['o', 's', 'P', 'X', ]
+    for ind, label in enumerate(unique_labels):
+        filtered_data = combined_df[combined_df['label'] == label]
+        filtered_meas = filtered_data['meas']
+        filtered_pred = filtered_data['pred']
+        if len(filtered_pred) != 0:
+            ax.scatter(filtered_meas,
+                       filtered_pred,
+                       label=label,
+                       color=color_list[ind],
+                       marker=marker_list[ind])
+    if legend:
+        ax.legend(loc=4)
+ax.plot(min_max_data, min_max_data, color="b", label="")
+
+ax.text(min_max_data[0],
+        min_max_data[1] * 0.9,
+        '$R^2$={0:.2f}'.format(estimator.r_squared(compared_value)))
+
+ax.set(xlabel='Measured', ylabel='Predicted')
+if plot_title is None:
+    ax.set_title(default_title)
+set_size(8, 6)
+plt.tight_layout()
+plt.show()
+# exp_data = estimator.get_exp_df()
+# feed_cols = []
+# for col in exp_data.columns:
+#     if 'aq_i' in col:
+#         feed_cols.append(col)
+# exp_data['total_re'] = exp_data[feed_cols].sum(axis=1)
+# label_list = []
+# for index, row in exp_data[feed_cols].iterrows():
+#     bool_list = list((row > 0).values)
+#     label = ''
+#     for species, el in zip(species_list, bool_list):
+#         if el:
+#             label = '{0}-{1}'.format(label, species)
+#     label = label[1:]
+#     label_list.append(label)
+# r2s = ""
+# for species in species_list:
+#     # if species=='La':
+#     # save_name = 'outputs' \
+#     #             '/parity_iterative_fitter_{0}_org_eq'.format(species)
+#     save_name = None
+#     fig, ax = estimator.parity_plot('{0}_org_eq'.format(species),
+#                                     c_data=
+#                                     exp_data['total_re'].values,
+#                                     c_label='Feed total RE '
+#                                             'molarity (mol/L)',
+#                                     print_r_squared=False,
+#                                     plot_title='')
+#     ax.plot([0, 0.05], [0, 0.05], c='b')
+#     ax.text(0.01, 0.04,
+#             '$R^2$={0:.2f}'.format(estimator.r_squared(
+#                 '{0}_org_eq'.format(species))))
+#     ax.set_xlim((0, 0.05))
+#     ax.set_ylim((0, 0.05))
+#     r2s += str(estimator.r_squared('{0}_org_eq'.format(species))) + ','
+#
+#     # fig, ax = estimator.parity_plot('{0}_org_eq'.format(species),
+#     #                                 data_labels=list(labeled_data['label']),
+#     #                                 print_r_squared=True,
+#     #                                 save_path=save_name)
+#     # ax.legend(loc=4)
+# pred_df = pd.DataFrame(estimator.get_predicted_dict())
+# new_cols = []
+# for col in pred_df.columns:
+#     new_cols.append("pred_{0}".format(col))
+# pred_df.columns = new_cols
+# new_cols = ['label',
+#             'h_i',
+#             'h_eq',
+#             'z_i',
+#             'z_eq'
+#             ]
+# for species in species_list:
+#     new_cols.append("{0}_aq_i".format(species))
+#     new_cols.append("{0}_aq_eq".format(species))
+#     new_cols.append("{0}_d_eq".format(species))
+# labeled_data.columns = new_cols
+# total_df = labeled_data.join(pred_df)
 # total_df.to_csv('if_mse_total_df.csv')
 # short_info_dict = {}
 # for key, value in info_dict.items():
--- a/docs/Examples/iterative_fitter_monitor.py
+++ b/docs/Examples/iterative_fitter_monitor.py
@@ -8,7 +8,7 @@ parameters = 'slope,intercept,beta0,beta1'.split(',')
 #     if go != 'y':
 #         break
 #     plt.close('all')
-df = pd.read_csv('outputs/iterative_fitter_output.csv')
+df = pd.read_csv('outputs/iterative_fitter_output4.csv')
 info_cols = {parameter: [] for parameter in parameters}
 for col in df.columns:
    for parameter in parameters:
@@ -48,4 +48,4 @@ ax.plot(df['iter'].values[1:],
 ax.set_xlabel('iteration')
 ax.set_ylabel('Value')
 plt.tight_layout()
-plt.savefig('outputs/rel_diff.png')
+# plt.savefig('outputs/rel_diff.png')
--- a/docs/Examples/outputs/best_obj.png
+++ b/docs/Examples/outputs/best_obj.png
--- a/docs/Examples/outputs/beta0.png
+++ b/docs/Examples/outputs/beta0.png
--- a/docs/Examples/outputs/beta1.png
+++ b/docs/Examples/outputs/beta1.png
--- a/docs/Examples/outputs/intercept.png
+++ b/docs/Examples/outputs/intercept.png
--- a/docs/Examples/outputs/iterative_fitter_output4.csv
+++ b/docs/Examples/outputs/iterative_fitter_output4.csv
@@ -0,0 +1,13 @@
+,iter,best_obj,rel_diff,best_ext_h0,Nd_intercept,Nd_beta0,Nd_beta1,Pr_intercept,Pr_beta0,Pr_beta1,Ce_intercept,Ce_beta0,Ce_beta1,La_intercept,La_beta0,La_beta1,Dy_intercept,Dy_beta0,Dy_beta1,Sm_intercept,Sm_beta0,Sm_beta1,Y_intercept,Y_beta0,Y_beta1
+0,0,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20,1e+20
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+3,3,0.008641080472189547,0.7095542768622557,-1377917.5261387695,-796048.7760914894,1.0825298224626023,6.211283570154922,-807884.6838503737,0.05879107717406858,0.5448320238819658,-799326.8310861788,0.6005020116531858,4.91004437191519,-801737.4462156398,0.5930048961782302,5.277144735292778,-801426.9157177466,0.5532849580804902,9.206773080251143,-795364.1985261647,0.5978087860273482,5.279188095059933,-813457.4899543246,0.8866269789489127,9.867663759220948
+4,4,0.0077116880626842774,0.001045483581763083,-1377917.5261387695,-796123.8048527003,1.082532056501894,6.21126666931227,-807682.864923159,0.05879107717406858,0.5448320238819658,-798906.4762851987,0.6005020116531858,4.91004437191519,-801602.4497529072,0.5930048961782302,5.277144735292778,-801426.3864333024,0.5532852226657412,9.206784416704208,-795364.1985261647,0.5978087860273482,5.279188095059933,-813457.4899543246,0.8866269789489127,9.867663759220948
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--- a/docs/Examples/outputs/iterative_fitter_w_mse_output.csv
+++ b/docs/Examples/outputs/iterative_fitter_w_mse_output.csv
@@ -0,0 +1,10 @@
+,iter,best_obj,rel_diff,best_ext_h0,Nd_intercept,Nd_beta0,Nd_beta1,Pr_intercept,Pr_beta0,Pr_beta1,Ce_intercept,Ce_beta0,Ce_beta1,La_intercept,La_beta0,La_beta1,Dy_intercept,Dy_beta0,Dy_beta1,Sm_intercept,Sm_beta0,Sm_beta1,Y_intercept,Y_beta0,Y_beta1
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--- a/docs/Examples/outputs/slope.png
+++ b/docs/Examples/outputs/slope.png
--- a/docs/Examples/outputs/temp.xml
+++ b/docs/Examples/outputs/temp.xml
@@ -33,7 +33,7 @@
      <thermo>
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>
-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-1376882.0784583509</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-1377917.5269485628</h0>
          <s0 units="J/mol/K"> 558.9824 </s0>
          <cp0 units="J/mol/K"> 0.0</cp0>
        </const_cp>
@@ -50,7 +50,7 @@
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>

-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-4924298.0880370205</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-4929625.060282971</h0>
          <s0 units="J/mol/K"> 1117.965 </s0>
          <cp0 units="J/mol/K">0.0</cp0>
        </const_cp>
@@ -67,7 +67,7 @@
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>

-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-4935685.119723228</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-4941397.084772181</h0>
          <s0 units="J/mol/K"> 1117.965 </s0>
          <cp0 units="J/mol/K">0.0</cp0>
        </const_cp>
@@ -85,7 +85,7 @@
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>

-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-4920369.042961768</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-4932551.489263242</h0>
          <s0 units="J/mol/K"> 1117.965 </s0>
          <cp0 units="J/mol/K">0.0</cp0>
        </const_cp>
@@ -103,7 +103,7 @@
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>

-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-4928639.61964031</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-4935194.142426379</h0>
          <s0 units="J/mol/K"> 1117.965 </s0>
          <cp0 units="J/mol/K">0.0</cp0>
        </const_cp>
@@ -120,7 +120,7 @@
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>

-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-4931991.722599618</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-4935179.480883835</h0>
          <s0 units="J/mol/K"> 1117.965 </s0>
          <cp0 units="J/mol/K">0.0</cp0>
        </const_cp>
@@ -138,7 +138,7 @@
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>

-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-4944682.264585918</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-4947210.070800013</h0>
          <s0 units="J/mol/K"> 1117.965 </s0>
          <cp0 units="J/mol/K">0.0</cp0>
        </const_cp>
@@ -157,7 +157,7 @@
        <const_cp Tmax="300.0" Tmin="298.0">
          <t0 units="K">298.14999999999998</t0>

-          <h0 units="J/mol" updated="Updated at 18:30 7-26-2020">-4924669.3217661735</h0>
+          <h0 units="J/mol" updated="Updated at 19:20 7-29-2020">-4929116.779371853</h0>
          <s0 units="J/mol/K"> 1117.965 </s0>
          <cp0 units="J/mol/K">0.0</cp0>
        </const_cp>
@@ -245,10 +245,10 @@
        </binarySaltParameters>

 		<binarySaltParameters anion="Cl-" cation="Pr+++">
-          <beta0 updated="Updated at 18:30 7-26-2020"> 0.058791091500561485, 0.0, 0.0, 0.0, 0.0 </beta0>
-          <beta1 updated="Updated at 18:30 7-26-2020"> 0.5448322248125199, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta0 updated="Updated at 19:20 7-29-2020"> 0.058791077174068576, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 19:20 7-29-2020"> 0.5448320238819658, 0.0, 0.0, 0.0, 0.0 </beta1>
          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
-          <Cphi updated="Updated at 18:30 7-26-2020"> -0.02066999867229882, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Cphi updated="Updated at 19:20 7-29-2020"> -0.02066999867229882, 0.0, 0.0, 0.0, 0.0 </Cphi>
          <Alpha1> 2 </Alpha1>
          <Alpha2> 0 </Alpha2>
          <source>
@@ -261,10 +261,10 @@
        </binarySaltParameters>
 		
        <binarySaltParameters anion="Cl-" cation="Nd+++">
-          <beta0 updated="Updated at 18:30 7-26-2020"> 1.213717095858249, 0.0, 0.0, 0.0, 0.0 </beta0>
-          <beta1 updated="Updated at 18:30 7-26-2020"> 7.7481294675488375, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta0 updated="Updated at 19:20 7-29-2020"> 1.0825315776813356, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 19:20 7-29-2020"> 6.211262701179254, 0.0, 0.0, 0.0, 0.0 </beta1>
          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
-          <Cphi updated="Updated at 18:30 7-26-2020"> -0.01963615126026457, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Cphi updated="Updated at 19:20 7-29-2020"> -0.01963615126026457, 0.0, 0.0, 0.0, 0.0 </Cphi>
          <Alpha1> 2 </Alpha1>
          <Alpha2> 0 </Alpha2>
          <source>
@@ -277,10 +277,10 @@
        </binarySaltParameters>
 		
 		<binarySaltParameters anion="Cl-" cation="La+++">
-          <beta0 updated="Updated at 18:30 7-26-2020"> 1.0223168335791355, 0.0, 0.0, 0.0, 0.0 </beta0>
-          <beta1 updated="Updated at 18:30 7-26-2020"> 0.5296306654103653, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta0 updated="Updated at 19:20 7-29-2020"> 0.5930048961782302, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 19:20 7-29-2020"> 5.2771447352927785, 0.0, 0.0, 0.0, 0.0 </beta1>
          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
-          <Cphi updated="Updated at 18:30 7-26-2020"> -0.024339999997603376, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Cphi updated="Updated at 19:20 7-29-2020"> -0.024339999997603376, 0.0, 0.0, 0.0, 0.0 </Cphi>
          <Alpha1> 2 </Alpha1>
          <Alpha2> 0 </Alpha2>
          <source>
@@ -293,10 +293,10 @@
        </binarySaltParameters>
 		
        <binarySaltParameters anion="Cl-" cation="Dy+++">
-          <beta0 updated="Updated at 18:30 7-26-2020"> 0.7646372240575223, 0.0, 0.0, 0.0, 0.0 </beta0>
-          <beta1 updated="Updated at 18:30 7-26-2020"> 7.849276225207628, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta0 updated="Updated at 19:20 7-29-2020"> 0.5532852863195881, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 19:20 7-29-2020"> 9.206787175138805, 0.0, 0.0, 0.0, 0.0 </beta1>
          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
-          <Cphi updated="Updated at 18:30 7-26-2020"> -0.019699989216349984, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Cphi updated="Updated at 19:20 7-29-2020"> -0.019699989216349984, 0.0, 0.0, 0.0, 0.0 </Cphi>
          <Alpha1> 2 </Alpha1>
          <Alpha2> 0 </Alpha2>
          <source>
@@ -309,10 +309,10 @@
        </binarySaltParameters>
 		
 		<binarySaltParameters anion="Cl-" cation="Ce+++">
-          <beta0 updated="Updated at 18:30 7-26-2020"> 0.20352350320923904, 0.0, 0.0, 0.0, 0.0 </beta0>
-          <beta1 updated="Updated at 18:30 7-26-2020"> 21.120419048363047, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta0 updated="Updated at 19:20 7-29-2020"> 0.6005020116531858, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 19:20 7-29-2020"> 4.91004437191519, 0.0, 0.0, 0.0, 0.0 </beta1>
          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
-          <Cphi updated="Updated at 18:30 7-26-2020"> -0.02618999999473301, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Cphi updated="Updated at 19:20 7-29-2020"> -0.02618999999473301, 0.0, 0.0, 0.0, 0.0 </Cphi>
          <Alpha1> 2 </Alpha1>
          <Alpha2> 0 </Alpha2>
          <source>
@@ -325,10 +325,10 @@
        </binarySaltParameters>
 		
 		<binarySaltParameters anion="Cl-" cation="Y+++">
-          <beta0 updated="Updated at 18:30 7-26-2020"> 0.8852797060008407, 0.0, 0.0, 0.0, 0.0 </beta0>
-          <beta1 updated="Updated at 18:30 7-26-2020"> 9.334636294454038, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta0 updated="Updated at 19:20 7-29-2020"> 0.8866269789489127, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 19:20 7-29-2020"> 9.867663759220948, 0.0, 0.0, 0.0, 0.0 </beta1>
          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
-          <Cphi updated="Updated at 18:30 7-26-2020"> -0.015467323909969704, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Cphi updated="Updated at 19:20 7-29-2020"> -0.015467323909969704, 0.0, 0.0, 0.0, 0.0 </Cphi>
          <Alpha1> 2 </Alpha1>
          <Alpha2> 0 </Alpha2>
          <source>
@@ -341,10 +341,10 @@
        </binarySaltParameters>
 		
 		<binarySaltParameters anion="Cl-" cation="Sm+++">
-          <beta0 updated="Updated at 18:30 7-26-2020"> 0.6989083059080712, 0.0, 0.0, 0.0, 0.0 </beta0>
-          <beta1 updated="Updated at 18:30 7-26-2020"> 6.877881736471866, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta0 updated="Updated at 19:20 7-29-2020"> 0.5978087860273482, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 19:20 7-29-2020"> 5.279188095059934, 0.0, 0.0, 0.0, 0.0 </beta1>
          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
-          <Cphi updated="Updated at 18:30 7-26-2020"> -0.019920000110321332, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Cphi updated="Updated at 19:20 7-29-2020"> -0.019920000110321332, 0.0, 0.0, 0.0, 0.0 </Cphi>
          <Alpha1> 2 </Alpha1>
          <Alpha2> 0 </Alpha2>
          <source>
--- a/docs/Examples/outputs/temp1.xml
+++ b/docs/Examples/outputs/temp1.xml
@@ -0,0 +1,716 @@
+<ctml>
+  <validate reactions="yes" species="yes" />
+                   
+ 
+  <phase dim="3" id="PC88A_liquid">
+    <elementArray datasrc="elementz.xml">
+        Cl O H C P Nd Pr Ce La Dy Y Sm dummy 
+    </elementArray>
+    <speciesArray datasrc="#species_PC88A_liquid">
+      (HA)2(org) dodecane Nd(H(A)2)3(org) Pr(H(A)2)3(org) Ce(H(A)2)3(org) La(H(A)2)3(org) Dy(H(A)2)3(org) Sm(H(A)2)3(org) Y(H(A)2)3(org)
+    </speciesArray>
+    <state>
+      <temperature units="K"> 298.15 </temperature>
+      <pressure units="Pa"> 100000.0 </pressure>
+      <soluteMolalities>
+        (HA)2(org): 0.25
+      </soluteMolalities>
+    </state>
+    <thermo model="IdealSolidSolution">
+       <standardConc model="molar_volume" />
+    </thermo>
+    <standardConc model="molar_volume" />
+    <transport model="None" />
+    <kinetics model="none" />
+  </phase>
+
+ 
+  <speciesData id="species_PC88A_liquid">
+
+
+    <species name="(HA)2(org)">
+      <atomArray> C:16 H:35 O:3 P:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-1376882.3191117246</h0>
+          <s0 units="J/mol/K"> 558.9824 </s0>
+          <cp0 units="J/mol/K"> 0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume updated="Updated at 21:02:32">0.320974226079</molarVolume>
+      </standardState>
+    </species>
+
+
+    <species name="Nd(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 Nd:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-4925566.309854757</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume updated="Updated at 21:02:32">0.973500071223</molarVolume>
+      </standardState>
+    </species>
+
+
+    <species name="Pr(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 Pr:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-4938249.845712334</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume updated="Updated at 21:02:32">0.979936421078</molarVolume>
+      </standardState>
+    </species>
+
+
+
+    <species name="Ce(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 Ce:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-4920387.823199008</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume updated="Updated at 21:02:32">1.0060487218</molarVolume>
+      </standardState>
+    </species>
+
+
+
+    <species name="La(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 La:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-4933548.865580005</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume updated="Updated at 21:02:32">0.981485801577</molarVolume>
+      </standardState>
+    </species>
+
+
+    <species name="Dy(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 Dy:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-4932560.171447597</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume updated="Updated at 21:02:32">0.961666360676</molarVolume>
+      </standardState>
+    </species>
+
+
+
+    <species name="Y(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 Y:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-4944840.781582316</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume updated="Updated at 21:02:32">0.958888814485</molarVolume>
+      </standardState>
+    </species>
+
+
+
+
+    <species name="Sm(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 Sm:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="Updated at 11:58 7-17-2020">-4924696.189921901</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume> 0.9642 </molarVolume>
+      </standardState>
+    </species>
+
+
+
+    <species name="Gd(H(A)2)3(org)">
+      <atomArray> C:48 H:102 O:9 P:3 Gd:1 </atomArray>
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+          <t0 units="K">298.14999999999998</t0>
+
+          <h0 units="J/mol" updated="yep">-4829446.858</h0>
+          <s0 units="J/mol/K"> 1117.965 </s0>
+          <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+      <standardState model="constant_incompressible">
+        <molarVolume>0.9642</molarVolume>
+      </standardState>
+    </species>
+    
+    
+    
+    <species name="dodecane">
+      <atomArray> dummy:1  </atomArray>  
+      
+      <thermo>
+        <const_cp Tmax="300.0" Tmin="298.0">
+	   <t0 units="K">298.14999999999998</t0> 
+	   
+	   <h0 units="J/mol"> 0.0 </h0> 
+	   <s0 units="J/mol/K"> 0.0 </s0>  
+           <cp0 units="J/mol/K">0.0</cp0>
+        </const_cp>
+      </thermo>
+     <standardState model="constant_incompressible">
+	     <molarVolume> 0.227113 </molarVolume>  
+      </standardState>
+    </species>
+
+  </speciesData>
+
+
+
+  <phase dim="3" id="HCl_electrolyte">
+    <speciesArray datasrc="#species_waterSolution">
+      H2O(L) H+ OH- Cl- Nd+++ Pr+++ Ce+++ La+++ Dy+++ Sm+++ Y+++
+    </speciesArray>
+
+    <state>
+      <temperature units="K"> 298.15 </temperature>
+      <pressure units="Pa"> 100000.0 </pressure>
+      <soluteMolalities>
+        Cl-: 1.0E-7
+        H+: 1.0E-7
+      </soluteMolalities>
+    </state>
+
+    <thermo model="HMW">
+      <standardConc model="solvent_volume" />
+      <activityCoefficients TempModel="complex1" model="Pitzer">
+        
+        <A_Debye model="water" />
+        <ionicRadius default="3.042843" units="Angstroms">
+        </ionicRadius>
+        <binarySaltParameters anion="Cl-" cation="H+">
+          <beta0> 0.177000779, 0.000125778, 0.0, -33.4777082, -0.262214535 </beta0>
+          <beta1> 0.292922504, -0.027938838, 0.0, 3402.47027, 19.7936248 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi>  0.000362, -0.00003036, 0.0, -2.91038E-11, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 12 </Alpha2>
+          <source>
+            refit of Holmes, H.F., Busey, J.M., Simonson, J.M., Mesmer, R.E.,
+            Archer, D.G., and Wood, R.H., 1987, The enthalpy of dilution of HCl(aq)
+            to 648 K and 4p MPa.  Thermodynamic properties, Journal of Chemical
+            Thermodynamics, v. 19, p. 863-890.
+          </source>
+        </binarySaltParameters>
+
+		<binarySaltParameters anion="Cl-" cation="Pr+++">
+          <beta0 updated="Updated at 11:58 7-17-2020"> 0.05879108748614492, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 11:58 7-17-2020"> 0.5448324180244323, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi updated="Updated at 10:47 7-17-2020"> -0.02066999867229882, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 0 </Alpha2>
+          <source>
+            Table S1: Pitzer parameters for osmotic and activity coeff Supp Info.
+            May, P. M.;  Rowland, D.;  Hefter, G.;  Konigsberger, E. 
+			A generic and updatable Pitzer characterization of aqueous binary electrolyte 
+			solutions at 1 bar and 25 C.
+			Journal of Chemical and Engineering Data 2011,56, 5066&#8211;5077.
+          </source>
+        </binarySaltParameters>
+		
+        <binarySaltParameters anion="Cl-" cation="Nd+++">
+          <beta0 updated="Updated at 11:58 7-17-2020"> 1.2137222016802447, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 11:58 7-17-2020"> 7.748226963005033, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi updated="Updated at 10:47 7-17-2020"> -0.01963615126026457, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 0 </Alpha2>
+          <source>
+            Table S1: Pitzer parameters for osmotic and activity coeff Supp Info.
+            May, P. M.;  Rowland, D.;  Hefter, G.;  Konigsberger, E. 
+			A generic and updatable Pitzer characterization of aqueous binary electrolyte 
+			solutions at 1 bar and 25 C.
+			Journal of Chemical and Engineering Data 2011,56, 5066&#8211;5077.
+          </source>
+        </binarySaltParameters>
+		
+		<binarySaltParameters anion="Cl-" cation="La+++">
+          <beta0 updated="Updated at 11:58 7-17-2020"> 1.022316535866388, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 11:58 7-17-2020"> 0.5296311209773129, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi updated="Updated at 10:47 7-17-2020"> -0.024339999997603376, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 0 </Alpha2>
+          <source>
+            Table S1: Pitzer parameters for osmotic and activity coeff Supp Info.
+            May, P. M.;  Rowland, D.;  Hefter, G.;  Konigsberger, E. 
+			A generic and updatable Pitzer characterization of aqueous binary electrolyte 
+			solutions at 1 bar and 25 C.
+			Journal of Chemical and Engineering Data 2011,56, 5066&#8211;5077.
+          </source>
+        </binarySaltParameters>
+		
+        <binarySaltParameters anion="Cl-" cation="Dy+++">
+          <beta0 updated="Updated at 11:58 7-17-2020"> 0.7646397332938777, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 11:58 7-17-2020"> 7.849320590516409, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi updated="Updated at 10:47 7-17-2020"> -0.019699989216349984, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 0 </Alpha2>
+          <source>
+            Table S1: Pitzer parameters for osmotic and activity coeff Supp Info.
+            May, P. M.;  Rowland, D.;  Hefter, G.;  Konigsberger, E. 
+			A generic and updatable Pitzer characterization of aqueous binary electrolyte 
+			solutions at 1 bar and 25 C.
+			Journal of Chemical and Engineering Data 2011,56, 5066&#8211;5077.
+          </source>
+        </binarySaltParameters>
+		
+		<binarySaltParameters anion="Cl-" cation="Ce+++">
+          <beta0 updated="Updated at 11:58 7-17-2020"> 0.2035235053232368, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 11:58 7-17-2020"> 21.120426174002823, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi updated="Updated at 10:47 7-17-2020"> -0.02618999999473301, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 0 </Alpha2>
+          <source>
+            Table S1: Pitzer parameters for osmotic and activity coeff Supp Info.
+            May, P. M.;  Rowland, D.;  Hefter, G.;  Konigsberger, E. 
+			A generic and updatable Pitzer characterization of aqueous binary electrolyte 
+			solutions at 1 bar and 25 C.
+			Journal of Chemical and Engineering Data 2011,56, 5066&#8211;5077.
+          </source>
+        </binarySaltParameters>
+		
+		<binarySaltParameters anion="Cl-" cation="Y+++">
+          <beta0 updated="Updated at 11:58 7-17-2020"> 0.8852802073165494, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 11:58 7-17-2020"> 9.334653075341238, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi updated="Updated at 10:47 7-17-2020"> -0.015467323909969704, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 0 </Alpha2>
+          <source>
+            Table S1: Pitzer parameters for osmotic and activity coeff Supp Info.
+            May, P. M.;  Rowland, D.;  Hefter, G.;  Konigsberger, E. 
+			A generic and updatable Pitzer characterization of aqueous binary electrolyte 
+			solutions at 1 bar and 25 C.
+			Journal of Chemical and Engineering Data 2011,56, 5066&#8211;5077.
+          </source>
+        </binarySaltParameters>
+		
+		<binarySaltParameters anion="Cl-" cation="Sm+++">
+          <beta0 updated="Updated at 11:58 7-17-2020"> 0.6989081585234721, 0.0, 0.0, 0.0, 0.0 </beta0>
+          <beta1 updated="Updated at 11:58 7-17-2020"> 6.877882600430561, 0.0, 0.0, 0.0, 0.0 </beta1>
+          <beta2> 0.0, 0.0, 0.0, 0.0, 0.0 </beta2>
+          <Cphi updated="Updated at 10:47 7-17-2020"> -0.019920000110321332, 0.0, 0.0, 0.0, 0.0 </Cphi>
+          <Alpha1> 2 </Alpha1>
+          <Alpha2> 0 </Alpha2>
+          <source>
+            Table S1: Pitzer parameters for osmotic and activity coeff Supp Info.
+            May, P. M.;  Rowland, D.;  Hefter, G.;  Konigsberger, E. 
+			A generic and updatable Pitzer characterization of aqueous binary electrolyte 
+			solutions at 1 bar and 25 C.
+			Journal of Chemical and Engineering Data 2011,56, 5066&#8211;5077.
+          </source>
+        </binarySaltParameters>
+
+        
+
+      </activityCoefficients>
+      <solvent> H2O(L) </solvent>
+    </thermo>
+    
+    <elementArray datasrc="elementz.xml"> O H Nd Pr Ce La Dy Y Sm C N Cl P E </elementArray>
+    <kinetics model="none">
+    </kinetics>
+  </phase>
+
+  <speciesData id="species_waterSolution">
+
+    <species name="H2O(L)">
+      
+      <atomArray>H:2 O:1 </atomArray>
+      <thermo>
+        <NASA P0="100000.0" Tmax="600.0" Tmin="273.14999999999998">
+          <floatArray name="coeffs" size="7">
+            7.255750050E+01,  -6.624454020E-01,   2.561987460E-03,  -4.365919230E-06,
+            2.781789810E-09,  -4.188654990E+04,  -2.882801370E+02
+          </floatArray>
+        </NASA>
+      </thermo>
+      <standardState model="waterPDSS">
+        
+        <molarVolume> 0.018068 </molarVolume>
+      </standardState>
+    </species>
+
+
+    <species name="OH-">
+      <speciesChemFormula> OH- </speciesChemFormula>
+      <atomArray> O:1 H:1 </atomArray>
+      <charge> -1 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -37595 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -54977 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -2.56 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> 0.12527 </a1>
+        <a2 units="cal/gmol"> 7.38 </a2>
+        <a3 units="cal-K/gmol/bar"> 1.8423 </a3>
+        <a4 units="cal-K/gmol"> -27821 </a4>
+        <c1 units="cal/gmol/K"> 4.15 </c1>
+        <c2 units="cal-K/gmol"> -103460 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 172460 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> -4.18 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+    <species name="NO3-">
+      <speciesChemFormula> NO3- </speciesChemFormula>
+      <atomArray> N:1 O:3 </atomArray>
+      <charge> -1 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -26507 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -49429 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> 35.12 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> 0.73161 </a1>
+        <a2 units="cal/gmol"> 678.24 </a2>
+        <a3 units="cal-K/gmol/bar"> -4.6838 </a3>
+        <a4 units="cal-K/gmol"> -30594 </a4>
+        <c1 units="cal/gmol/K"> 7.7 </c1>
+        <c2 units="cal-K/gmol"> -67250 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 109770 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> 29.0 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+
+    
+
+    
+    
+    <species name="Cl-">
+      <speciesChemFormula> Cl- </speciesChemFormula>
+      <atomArray> Cl:1 </atomArray>
+      <charge> -1 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="273.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -31379 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_TR units="cal/gmol"> -39933 </DH0_f_Pr_TR>
+          <S0_Pr_Tr units="cal/gmol/K"> 13.56 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/mol/bar"> 0.4032 </a1>
+        <a2 units="cal/mol"> 480.1 </a2>
+        <a3 units="cal-K/mol/bar"> 5.563 </a3>
+        <a4 units="cal-K/mol"> -28470 </a4>
+        <c1 units="cal/mol/K"> -4.4 </c1>
+        <c2 units="cal-K/mol"> -57140 </c2>
+        <omega_Pr_Tr units="cal/mol"> 145600 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> 17.79 </molarVolume>
+      </standardState>
+      <source> ref:G9 </source>
+    </species>
+
+    <species name="H+">
+      <speciesChemFormula> H+ </speciesChemFormula>
+      <atomArray> H:1 </atomArray>
+      <charge> +1 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="273.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> 0 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_TR units="cal/gmol"> 0 </DH0_f_Pr_TR>
+          <S0_Pr_Tr units="cal/gmol/K"> 0 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/mol/bar"> 0 </a1>
+        <a2 units="cal/mol"> 0 </a2>
+        <a3 units="cal-K/mol/bar"> 0 </a3>
+        <a4 units="cal-K/mol"> 0 </a4>
+        <c1 units="cal/mol/K"> 0 </c1>
+        <c2 units="cal-K/mol"> 0 </c2>
+        <omega_Pr_Tr units="cal/mol"> 0 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> 0 </molarVolume>
+      </standardState>
+      <source> ref:G9 </source>
+    </species>
+
+
+    <species name="Nd+++">
+      <speciesChemFormula> Nd+++ </speciesChemFormula>
+      <atomArray> Nd:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -160600 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -166500 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -49.5 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.33707 </a1>
+        <a2 units="cal/gmol"> -1454.52 </a2>
+        <a3 units="cal-K/gmol/bar"> 8.3211 </a3>
+        <a4 units="cal-K/gmol"> -21777 </a4>
+        <c1 units="cal/gmol/K"> 1.6236 </c1>
+        <c2 units="cal-K/gmol"> -118344 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 225500 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> -43.1 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+    <species name="Pr+++">
+      <speciesChemFormula> Pr+++ </speciesChemFormula>
+      <atomArray> Pr:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -162600 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -168800 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -50 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.32406 </a1>
+        <a2 units="cal/gmol"> -1419.98 </a2>
+        <a3 units="cal-K/gmol/bar"> 8.1257 </a3>
+        <a4 units="cal-K/gmol"> -21920 </a4>
+        <c1 units="cal/gmol/K"> -1.1975 </c1>
+        <c2 units="cal-K/gmol"> -127511 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 223500 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> -42.1 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+
+    <species name="Ce+++">
+      <speciesChemFormula> Ce+++ </speciesChemFormula>
+      <atomArray> Ce:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -161600 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -167400 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -49 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.29292 </a1>
+        <a2 units="cal/gmol"> -1493.38 </a2>
+        <a3 units="cal-K/gmol/bar"> 11.6196 </a3>
+        <a4 units="cal-K/gmol"> -21616 </a4>
+        <c1 units="cal/gmol/K"> 4.0445 </c1>
+        <c2 units="cal-K/gmol"> -108974 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 222510 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> -39.8 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+
+    <species name="La+++">
+      <speciesChemFormula> La+++ </speciesChemFormula>
+      <atomArray> La:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -164000 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -169600 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -52 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.2788 </a1>
+        <a2 units="cal/gmol"> -1438.24 </a2>
+        <a3 units="cal-K/gmol/bar"> 10.9602 </a3>
+        <a4 units="cal-K/gmol"> -21844 </a4>
+        <c1 units="cal/gmol/K"> 4.2394 </c1>
+        <c2 units="cal-K/gmol"> -106122 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 215720 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> -38.6 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+
+
+    <species name="Dy+++">
+      <speciesChemFormula> Dy+++ </speciesChemFormula>
+      <atomArray> Dy:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -158700 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -166500 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -55.2 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.30003 </a1>
+        <a2 units="cal/gmol"> -1510.74 </a2>
+        <a3 units="cal-K/gmol/bar"> 11.6879 </a3>
+        <a4 units="cal-K/gmol"> -21545 </a4>
+        <c1 units="cal/gmol/K"> 9.5076 </c1>
+        <c2 units="cal-K/gmol"> -94919 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 237920 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> -40.7 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+
+    <species name="Y+++">
+      <speciesChemFormula> Y+++ </speciesChemFormula>
+      <atomArray> Y:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -163800 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -170900 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -60 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.30140 </a1>
+        <a2 units="cal/gmol"> -1514.08 </a2>
+        <a3 units="cal-K/gmol/bar"> 11.7010 </a3>
+        <a4 units="cal-K/gmol"> -21531 </a4>
+        <c1 units="cal/gmol/K"> 7.1634 </c1>
+        <c2 units="cal-K/gmol"> -103067 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 237920 </omega_Pr_Tr>
+        <molarVolume units="cm3/mol"> -40.8 </molarVolume>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+    
+    
+
+    <species name="Sm+++">
+      <speciesChemFormula> Sm+++ </speciesChemFormula>
+      <atomArray> Sm:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -159100 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -165200 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -50.7 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.32065 </a1>
+        <a2 units="cal/gmol"> -1561.08 </a2>
+        <a3 units="cal-K/gmol/bar"> 11.8857 </a3>
+        <a4 units="cal-K/gmol"> -21337 </a4>
+        <c1 units="cal/gmol/K"> 1.9385 </c1>
+        <c2 units="cal-K/gmol"> -118548 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 229550 </omega_Pr_Tr>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+
+
+
+    <species name="Gd+++">
+      <speciesChemFormula> Gd+++ </speciesChemFormula>
+      <atomArray> Gd:1 </atomArray>
+      <charge> +3 </charge>
+      <thermo model="HKFT">
+        <HKFT Pref="1 atm" Tmax="625.15" Tmin="298.15">
+          <DG0_f_Pr_Tr units="cal/gmol"> -158600 </DG0_f_Pr_Tr>
+          <DH0_f_Pr_Tr units="cal/gmol"> -164200 </DH0_f_Pr_Tr>
+          <S0_Pr_Tr units="cal/gmol/K"> -49.2 </S0_Pr_Tr>
+        </HKFT>
+      </thermo>
+      <standardState model="HKFT">
+        <a1 units="cal/gmol/bar"> -0.29771 </a1>
+        <a2 units="cal/gmol"> -1505.06 </a2>
+        <a3 units="cal-K/gmol/bar"> 11.6656 </a3>
+        <a4 units="cal-K/gmol"> -21568 </a4>
+        <c1 units="cal/gmol/K"> 6.5606 </c1>
+        <c2 units="cal-K/gmol"> -103474 </c2>
+        <omega_Pr_Tr units="cal/gmol"> 232650 </omega_Pr_Tr>
+      </standardState>
+      <source>
+        ref:G9
+      </source>
+    </species>
+    
+    
+    
+    
+  </speciesData>
+
+</ctml>
--- a/docs/Examples/test_eval.py
+++ b/docs/Examples/test_eval.py
@@ -0,0 +1,330 @@
+# This file tests adding 0.1 M NaCl to the feed.
+import llepe
+import pandas as pd
+import numpy as np
+import json
+import matplotlib as plt
+import matplotlib
+import cantera as ct
+
+
+class ModLLEPE(llepe.LLEPE):
+    def __init__(self,
+                 exp_data,
+                 phases_xml_filename,
+                 phase_names,
+                 aq_solvent_name,
+                 extractant_name,
+                 diluant_name,
+                 complex_names,
+                 extracted_species_ion_names,
+                 extracted_species_list=None,
+                 aq_solvent_rho=None,
+                 extractant_rho=None,
+                 diluant_rho=None,
+                 opt_dict=None,
+                 objective_function='Log-MSE',
+                 optimizer='scipy_minimize',
+                 temp_xml_file_path=None,
+                 dependant_params_dict=None,
+                 custom_objects_dict=None,
+                 nacl_molarity=0):
+        self.nacl_molarity = nacl_molarity
+        super().__init__(exp_data,
+                         phases_xml_filename,
+                         phase_names,
+                         aq_solvent_name,
+                         extractant_name,
+                         diluant_name,
+                         complex_names,
+                         extracted_species_ion_names,
+                         extracted_species_list,
+                         aq_solvent_rho,
+                         extractant_rho,
+                         diluant_rho,
+                         opt_dict,
+                         objective_function,
+                         optimizer,
+                         temp_xml_file_path,
+                         dependant_params_dict,
+                         custom_objects_dict)
+
+
+    def set_in_moles(self, feed_vol):
+        """Function that initializes mole fractions to input feed_vol
+
+                This function is called at initialization
+
+                Sets in_moles to a pd.DataFrame containing initial mole fractions
+
+                Columns for species and rows for different experiments
+
+                This function also calls update_predicted_dict
+
+                :param feed_vol: (float) feed volume of mixture (L)
+                """
+        phases_copy = self._phases.copy()
+        exp_df = self._exp_df.copy()
+        solvent_name = self._aq_solvent_name
+        extractant_name = self._extractant_name
+        diluant_name = self._diluant_name
+        solvent_rho = self._aq_solvent_rho
+        extractant_rho = self._extractant_rho
+        diluant_rho = self._diluant_rho
+        extracted_species_names = self._extracted_species_ion_names
+        extracted_species_list = self._extracted_species_list
+
+        mixed = ct.Mixture(phases_copy)
+        aq_ind = None
+        solvent_ind = None
+        for ind, phase in enumerate(phases_copy):
+            if solvent_name in phase.species_names:
+                aq_ind = ind
+                solvent_ind = phase.species_names.index(solvent_name)
+        if aq_ind is None:
+            raise Exception('Solvent "{0}" not found \
+                                        in xml file'.format(solvent_name))
+
+        if aq_ind == 0:
+            org_ind = 1
+        else:
+            org_ind = 0
+        self._aq_ind = aq_ind
+        self._org_ind = org_ind
+        extractant_ind = phases_copy[org_ind].species_names.index(
+            extractant_name)
+        diluant_ind = phases_copy[org_ind].species_names.index(
+            diluant_name)
+
+        extracted_species_ind_list = [
+            phases_copy[aq_ind].species_names.index(
+                extracted_species_name)
+            for extracted_species_name in extracted_species_names]
+        extracted_species_charges = np.array(
+            [phases_copy[aq_ind].species(
+                extracted_species_ind).charge
+             for extracted_species_ind in extracted_species_ind_list])
+        self._extracted_species_charges = extracted_species_charges
+
+        mix_aq = mixed.phase(aq_ind)
+        mix_org = mixed.phase(org_ind)
+        solvent_mw = mix_aq.molecular_weights[solvent_ind]  # g/mol
+        extractant_mw = mix_org.molecular_weights[extractant_ind]
+        diluant_mw = mix_org.molecular_weights[diluant_ind]
+        if solvent_rho is None:
+            solvent_rho = mix_aq(aq_ind).partial_molar_volumes[
+                              solvent_ind] / solvent_mw * 1e6  # g/L
+            self._aq_solvent_rho = solvent_rho
+        if extractant_rho is None:
+            extractant_rho = mix_org(org_ind).partial_molar_volumes[
+                                 extractant_ind] / extractant_mw * 1e6
+            self._extractant_rho = extractant_rho
+        if diluant_rho is None:
+            diluant_rho = mix_org(org_ind).partial_molar_volumes[
+                              extractant_ind] / extractant_mw * 1e6
+            self._diluant_rho = diluant_rho
+
+        in_moles_data = []
+        aq_phase_solvent_moles = feed_vol * solvent_rho / solvent_mw
+        for index, row in exp_df.iterrows():
+            h_plus_moles = feed_vol * row['h_i']
+            hydroxide_ions = 0
+            extracted_species_moles = np.array(
+                [feed_vol * row['{0}_aq_i'.format(
+                    extracted_species)]
+                 for extracted_species in extracted_species_list])
+            extracted_species_charge_sum = np.sum(
+                extracted_species_charges * extracted_species_moles)
+            chlorine_moles = extracted_species_charge_sum + h_plus_moles
+            extractant_moles = feed_vol * row['z_i']
+            extractant_vol = extractant_moles * extractant_mw / extractant_rho
+            diluant_vol = feed_vol - extractant_vol
+            diluant_moles = diluant_vol * diluant_rho / diluant_mw
+            complex_moles = np.zeros(len(extracted_species_list))
+
+            species_moles_aq = [aq_phase_solvent_moles,
+                                h_plus_moles,
+                                hydroxide_ions,
+                                chlorine_moles]
+            species_moles_aq.extend(list(extracted_species_moles))
+            species_moles_aq.append(self.nacl_molarity * feed_vol)
+            species_moles_aq[3] += self.nacl_molarity * feed_vol
+            species_moles_org = [extractant_moles, diluant_moles]
+            species_moles_org.extend(list(complex_moles))
+            if aq_ind == 0:
+                species_moles = species_moles_aq + species_moles_org
+            else:
+                species_moles = species_moles_org + species_moles_aq
+            in_moles_data.append(species_moles)
+
+        self._in_moles = pd.DataFrame(
+            in_moles_data, columns=mixed.species_names)
+        self.update_predicted_dict()
+        return None
+
+
+font = {'family': 'sans serif',
+        'size': 24}
+matplotlib.rc('font', **font)
+plt.rc('xtick', labelsize=18)
+plt.rc('ytick', labelsize=18)
+plt.rcParams['lines.linewidth'] = 4
+matplotlib.rcParams['lines.markersize'] = 10
+
+
+def ext_to_complex(h0, custom_obj_dict, mini_species):
+    linear_params = custom_obj_dict['lin_param_df']
+    row = linear_params[linear_params['species'] == mini_species]
+    return row['slope'].values[0] * h0[0] + row['intercept'].values[0]
+
+
+def mod_lin_param_df(lp_df, input_val, mini_species, mini_lin_param):
+    new_lp_df = lp_df.copy()
+    index = new_lp_df.index[new_lp_df['species'] == mini_species].tolist()[0]
+    new_lp_df.at[index, mini_lin_param] = input_val
+    return new_lp_df
+
+
+info_df = pd.read_csv('outputs/multi_only_iterative_fitter_output.csv')
+test_row = -1
+pitzer_params_filename = "../../data/jsons/min_h0_pitzer_params.txt"
+with open(pitzer_params_filename) as file:
+    pitzer_params_dict = json.load(file)
+pitzer_params_df = pd.DataFrame(pitzer_params_dict)
+species_list = 'Nd,Pr,Ce,La,Dy,Sm,Y'.split(',')
+pitzer_param_list = ['beta0', 'beta1']
+labeled_data = pd.read_csv("../../data/csvs/"
+                           "no_formiga_or_5_oa_PC88A_HCL_NdPrCeLaDySmY.csv")
+labeled_data = labeled_data.sort_values(['Feed Pr[M]', 'Feed Ce[M]'],
+                                        ascending=True)
+exp_data = labeled_data.drop(labeled_data.columns[0], axis=1)
+xml_file = "test_PC88A_HCL_NdPrCeLaDySmY_w_pitzer.xml"
+lin_param_df = pd.read_csv("../../data/csvs"
+                           "/zeroes_removed_min_h0_pitzer_lin_params.csv")
+estimator_params = {'exp_data': exp_data,
+                    'phases_xml_filename': xml_file,
+                    'phase_names': ['HCl_electrolyte', 'PC88A_liquid'],
+                    'aq_solvent_name': 'H2O(L)',
+                    'extractant_name': '(HA)2(org)',
+                    'diluant_name': 'dodecane',
+                    'complex_names': ['{0}(H(A)2)3(org)'.format(species)
+                                      for species in species_list],
+                    'extracted_species_ion_names': ['{0}+++'.format(species)
+                                                    for species in
+                                                    species_list],
+                    'aq_solvent_rho': 1000.0,
+                    'extractant_rho': 960.0,
+                    'diluant_rho': 750.0,
+                    'temp_xml_file_path': 'outputs/temp.xml',
+                    'objective_function': llepe.lmse_perturbed_obj,
+                    'nacl_molarity': 0
+                    }
+dependant_params_dict = {}
+for species, complex_name in zip(species_list,
+                                 estimator_params['complex_names']):
+    inner_dict = {'upper_element_name': 'species',
+                  'upper_attrib_name': 'name',
+                  'upper_attrib_value': complex_name,
+                  'lower_element_name': 'h0',
+                  'lower_attrib_name': None,
+                  'lower_attrib_value': None,
+                  'input_format': '{0}',
+                  'function': ext_to_complex,
+                  'kwargs': {"mini_species": species},
+                  'independent_params': '(HA)2(org)_h0'}
+    dependant_params_dict['{0}_h0'.format(complex_name)] = inner_dict
+info_dict = {'(HA)2(org)_h0': {'upper_element_name': 'species',
+                               'upper_attrib_name': 'name',
+                               'upper_attrib_value': '(HA)2(org)',
+                               'lower_element_name': 'h0',
+                               'lower_attrib_name': None,
+                               'lower_attrib_value': None,
+                               'input_format': '{0}',
+                               'input_value':
+                                   info_df.iloc[test_row, :]['best_ext_h0']}}
+for species in species_list:
+    for pitzer_param in pitzer_param_list:
+        pitzer_str = "{0}_{1}".format(species, pitzer_param)
+        value = info_df.iloc[test_row, :][pitzer_str]
+        pitzer_params_dict[pitzer_str]['input_value'] = value
+    lin_str = "{0}_slope".format(species)
+    inner_dict = {'custom_object_name': 'lin_param_df',
+                  'function': mod_lin_param_df,
+                  'kwargs': {'mini_species': species,
+                             'mini_lin_param': 'slope'},
+                  'input_value': 3
+                  }
+    info_dict[lin_str] = inner_dict
+    lin_str = "{0}_intercept".format(species)
+    value = info_df.iloc[test_row, :][lin_str]
+    inner_dict = {'custom_object_name': 'lin_param_df',
+                  'function': mod_lin_param_df,
+                  'kwargs': {'mini_species': species,
+                             'mini_lin_param': 'intercept'},
+                  'input_value': value
+                  }
+    info_dict[lin_str] = inner_dict
+
+info_dict.update(pitzer_params_dict)
+estimator = ModLLEPE(**estimator_params)
+estimator.set_custom_objects_dict({'lin_param_df': lin_param_df})
+estimator.update_custom_objects_dict(info_dict)
+estimator.update_xml(info_dict,
+                     dependant_params_dict=dependant_params_dict)
+exp_data = estimator.get_exp_df()
+feed_cols = []
+for col in exp_data.columns:
+    if 'aq_i' in col:
+        feed_cols.append(col)
+exp_data['total_re'] = exp_data[feed_cols].sum(axis=1)
+label_list = []
+for index, row in exp_data[feed_cols].iterrows():
+    bool_list = list((row > 0).values)
+    label = ''
+    for species, el in zip(species_list, bool_list):
+        if el:
+            label = '{0}-{1}'.format(label, species)
+    label = label[1:]
+    label_list.append(label)
+r2s = ""
+for species in species_list:
+    # if species=='La':
+    # save_name = 'outputs' \
+    #             '/parity_iterative_fitter_{0}_org_eq'.format(species)
+    save_name = None
+    # fig, ax = estimator.parity_plot('{0}_org_eq'.format(species),
+    #                                 c_data='z_i',
+    #                                 c_label='Feed total RE '
+    #                                         'molarity (mol/L)',
+    #                                 print_r_squared=True,
+    #                                 save_path=save_name)
+    r2s += str(estimator.r_squared('{0}_org_eq'.format(species))) + ','
+
+    fig, ax = estimator.parity_plot('{0}_org_eq'.format(species),
+                                    data_labels=list(labeled_data['label']),
+                                    print_r_squared=True,
+                                    save_path=save_name)
+    ax.legend(loc=4)
+pred_df = pd.DataFrame(estimator.get_predicted_dict())
+new_cols = []
+for col in pred_df.columns:
+    new_cols.append("pred_{0}".format(col))
+pred_df.columns = new_cols
+new_cols = ['label',
+            'h_i',
+            'h_eq',
+            'z_i',
+            'z_eq'
+            ]
+for species in species_list:
+    new_cols.append("{0}_aq_i".format(species))
+    new_cols.append("{0}_aq_eq".format(species))
+    new_cols.append("{0}_d_eq".format(species))
+labeled_data.columns = new_cols
+total_df = labeled_data.join(pred_df)
+# total_df.to_csv('if_mse_total_df.csv')
+# short_info_dict = {}
+# for key, value in info_dict.items():
+#     short_info_dict[key] = value['input_value']
+# with open("outputs/iterative_fitter_short_info_dict.txt", 'w') as file:
+#     json.dump(short_info_dict, file)