added rich HTML output for MC_GEOPHIRES. Also fixed bug for when run from command line

Author: malcolm-dsider

src/geophires_monte_carlo/MC_GeoPHIRES3.py

@@ -22,8 +22,12 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
+from rich.console import Console
+from rich.table import Table
 
 from geophires_monte_carlo.common import _get_logger
+from geophires_x.Parameter import OutputParameter
+from geophires_x.Parameter import floatParameter
 from geophires_x_client import GeophiresInputParameters
 from geophires_x_client import GeophiresXClient
 from geophires_x_client import GeophiresXResult
@@ -33,6 +37,184 @@
 from hip_ra_x import HipRaXClient
 
 
+def Write_HTML_Output(
+    html_path: str,
+    df: pd.DataFrame,
+    outputs: list,
+    mins: list,
+    maxs: list,
+    medians: list,
+    averages: list,
+    means: list,
+    std: list,
+    full_names: set,
+    short_names: set,
+) -> None:
+    """
+    Write_HTML_Output - write the results of the Monte Carlo simulation to an HTML file
+    :param html_path: the path to the HTML file to write
+    :type html_path: str
+    :param df: the DataFrame with the results
+    :type df: pd.DataFrame
+    :param outputs: the list of output variable names
+    :type outputs: list
+    :param mins: the list of minimum values for each output variable
+    :type mins: list
+    :param maxs: the list of maximum values for each output variable
+    :type maxs: list
+    :param medians: the list of median values for each output variable
+    :type medians: list
+    :param averages: the list of average values for each output variable
+    :type averages: list
+    :param means: the list of mean values for each output variable
+    :type means: list
+    :param std: the list of standard deviation values for each output variable
+    :type std: list
+    :param full_names: the list of full names for each output variable
+    :type full_names: set
+    :param short_names: the list of short names for each output variable
+    :type short_names: set
+    """
+
+    # Build the tables that will hold those results, along with the columns for the input variables
+    results_table = Table(title='GEOPHIRES/HIR-RA Monte Carlo Results')
+    results_table.add_column('Iteration #', no_wrap=True, justify='center')
+    for output in df.axes[1]:
+        results_table.add_column(output.replace(',', ''), no_wrap=True, justify='center')
+
+    statistics_table = Table(title='GEOPHIRES/HIR-RA Monte Carlo Statistics')
+    statistics_table.add_column('Output Parameter Name', no_wrap=True, justify='center')
+    statistics_table.add_column('minimum', no_wrap=True, justify='center')
+    statistics_table.add_column('maximum', no_wrap=True, justify='center')
+    statistics_table.add_column('median', no_wrap=True, justify='center')
+    statistics_table.add_column('average', no_wrap=True, justify='center')
+    statistics_table.add_column('mean', no_wrap=True, justify='center')
+    statistics_table.add_column('standard deviation', no_wrap=True, justify='center')
+
+    # Iterate over the rows of the DataFrame and add them to the results table
+    for index, row in df.iterrows():
+        data = row.values[0 : len(outputs)]
+
+        # have to deal with the special case where thr last column is actually
+        # a compound string with multiple columns in it that looks like this:
+        # ' (Gradient 1:47.219846973456924;Reservoir Temperature:264.7789623351493;...)'
+        str_to_parse = str(row.values[len(outputs)]).strip().replace('(', '').replace(')', '')
+        fields = str_to_parse.split(';')
+        for field in fields:
+            if len(field) > 0:
+                key, value = field.split(':')
+                data = np.append(data, float(value))
+
+        results_table.add_row(str(int(index)), *[render_default(d) for d in data])
+
+    for i in range(len(outputs)):
+        statistics_table.add_row(
+            outputs[i],
+            render_default(mins[i]),
+            render_default(maxs[i]),
+            render_default(medians[i]),
+            render_default(averages[i]),
+            render_default(means[i]),
+            render_default(std[i]),
+        )
+
+    console = Console(style='bold white on black', force_terminal=True, record=True, width=500)
+    console.print(results_table)
+    console.print(' ')
+    console.print(statistics_table)
+    console.save_html(html_path)
+
+    # Write a reference to the image(s) into the HTML file by inserting before the "</body>" tag
+    # build the string to be inserted first
+    insert_string = ''
+    for _ in range(len(full_names)):
+        name_to_use = short_names.pop()
+        insert_string = insert_string + f'<img src="{name_to_use}.png" alt="{name_to_use}">\n'
+
+    match_string = '</body>'
+    with open(html_path, 'r+', encoding='UTF-8') as html_file:
+        contents = html_file.readlines()
+        if match_string in contents[-1]:  # Handle last line to prevent IndexError
+            pass
+        else:
+            for index, line in enumerate(contents):
+                if match_string in line and insert_string not in contents[index + 1]:
+                    contents.insert(index, insert_string)
+                    break
+        html_file.seek(0)
+        html_file.writelines(contents)
+
+
+def UpgradeSymbologyOfUnits(unit: str) -> str:
+    """
+    UpgradeSymbologyOfUnits is a function that takes a string that represents a unit and replaces the **2 and **3
+    with the appropriate unicode characters for superscript 2 and 3, and replaces "deg" with the unicode character
+    for degrees.
+    :param unit: a string that represents a unit
+    :return: a string that represents a unit with the appropriate unicode characters for superscript 2 and 3, and
+    replaces "deg" with the unicode character for degrees.
+    """
+    return unit.replace('**2', '\u00b2').replace('**3', '\u00b3').replace('deg', '\u00b0')
+
+
+def render_default(p: float, unit: str = '') -> str:
+    """
+    RenderDefault - render a float as a string with 2 decimal places, or in scientific notation if it is greater than
+    10,000 with the unit appended to it if it is not an empty string (the default)
+    :param p: the float to render
+    :type p: float
+    :param unit: the unit to append to the string
+    :type unit: str
+    :return: the string representation of the float
+    :rtype: str
+    """
+    unit = UpgradeSymbologyOfUnits(unit)
+    # if the number is greater than 10,000, render it in scientific notation
+    if p > 10_000:
+        return f'{p:10.2e} {unit}'.strip()
+    # otherwise, render it with 2 decimal places
+    else:
+        return f'{p:10.2f} {unit}'.strip()
+
+
+def render_scientific(p: float, unit: str = '') -> str:
+    """
+    RenderScientific - render a float as a string in scientific notation with 2 decimal places
+    and the unit appended to it if it is not an empty string (the default)
+    :param p: the float to render
+    :type p: float
+    :param unit: the unit to append to the string
+    :type unit: str
+    :return: the string representation of the float
+    :rtype: str
+    """
+    unit = UpgradeSymbologyOfUnits(unit)
+    return f'{p:10.2e} {unit}'.strip()
+
+
+def render_Parameter_default(p: floatParameter | OutputParameter) -> str:
+    """
+    RenderDefault - render a float as a string with 2 decimal places, or in scientific notation if it is greater than
+    10,000 with the unit appended to it if it is not an empty string (the default) by calling the render_default base
+    function
+    :param p: the parameter to render
+    :type p: float
+    :return: the string representation of the float
+    """
+    return render_default(p.value, p.CurrentUnits.value)
+
+
+def render_parameter_scientific(p: floatParameter | OutputParameter) -> str:
+    """
+    RenderScientific - render a float as a string in scientific notation with 2 decimal places
+    and the unit appended to it if it is not an empty string (the default) by calling the render_scientific base function
+    :param p: the parameter to render
+    :type p: float
+    :return: the string representation of the float
+    """
+    return render_scientific(p.value, p.CurrentUnits.value)
+
+
 def check_and_replace_mean(input_value, args) -> list:
     """
     CheckAndReplaceMean - check to see if the user has requested that a value be replaced by a mean value by specifying
@@ -268,7 +450,9 @@ def main(command_line_args=None):
         if 'MC_OUTPUT_FILE' in args and args.MC_OUTPUT_FILE is not None
         else str(Path(Path(args.Input_file).parent, 'MC_Result.txt').absolute())
     )
+    args.MC_OUTPUT_FILE = output_file
     python_path = 'python'
+    html_path = ''
 
     for line in flist:
         clean = line.strip()
@@ -284,6 +468,8 @@ def main(command_line_args=None):
             output_file = pair[1]
         elif pair[0].startswith('PYTHON_PATH'):
             python_path = pair[1]
+        elif pair[0].startswith('HTML_PATH'):
+            html_path = pair[1]
 
     # check to see if there is a "#" in an input, if so, use the results file to replace it with the value
     for input_value in inputs:
@@ -375,6 +561,8 @@ def main(command_line_args=None):
     # write them out
     annotations = ''
     outputs_result: dict[str, dict] = {}
+    full_names: set = set()
+    short_names: set = set()
     with open(output_file, 'a') as f:
         if iterations != actual_records_count:
             f.write(
@@ -408,10 +596,17 @@ def main(command_line_args=None):
             f.write(f'bin values (as percentage): {ret[0]!s}\n')
             f.write(f'bin edges: {ret[1]!s}\n')
             fname = df.columns[i].strip().replace('/', '-')
-            plt.savefig(Path(Path(output_file).parent, f'{fname}.png'))
-
+            save_path = Path(Path(output_file).parent, f'{fname}.png')
+            if html_path:
+                save_path = Path(Path(html_path).parent, f'{fname}.png')
+            plt.savefig(save_path)
+            full_names.add(save_path)
+            short_names.add(fname)
             annotations = ''
 
+    if html_path:
+        Write_HTML_Output(html_path, df, outputs, mins, maxs, medians, averages, means, std, full_names, short_names)
+
     with open(Path(output_file).with_suffix('.json'), 'w') as json_output_file:
         json_output_file.write(json.dumps(outputs_result))
         logger.info(f'Wrote JSON results to {json_output_file.name}')