ENH: Add Monte Carlo outputs export to CSV/JSON (#242)

docs/notebooks/monte_carlo_analysis/monte_carlo_class_usage.ipynb

@@ -800,6 +800,34 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also export our Monte Carlo results into .csv and .json files using the method `MonteCarlo.export_results()`.\n",
+    "\n",
+    "Choose a name for the output file and select a format to output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Results saved to monte_carlo_analysis_outputs/monte_carlo_csv_output_example as .csv file\n",
+      "Results saved to monte_carlo_analysis_outputs/monte_carlo_json_output_example as .json file\n"
+     ]
+    }
+   ],
+   "source": [
+    "test_dispersion.export_results(\"monte_carlo_analysis_outputs/monte_carlo_csv_output_example\", \"csv\")\n",
+    "test_dispersion.export_results(\"monte_carlo_analysis_outputs/monte_carlo_json_output_example\", \"json\")"
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",

rocketpy/simulation/monte_carlo.py

@@ -14,6 +14,7 @@
 """
 
 import json
+import csv
 import os
 import traceback
 import warnings
@@ -588,6 +589,41 @@ def __evaluate_flight_outputs(self, flight, sim_idx):
             json.dumps(outputs_dict, cls=RocketPyEncoder, **self._export_config) + "\n"
         )
 
+    def export_results(self, output_filename, output_format):
+        """Converts the default Monte Carlo .txt output to .cvs or .json file
+        depending on the user's choice
+
+        Parameters
+        ----------
+        output_filename : str
+            Name of the file in which the converted data will be saved
+        output_format : str
+            Format of the output file
+
+        Returns
+        -------
+        None
+        """
+        txt_data = []
+        with open(f"{self.filename}.outputs.txt", "r", encoding="utf-8") as f:
+            for line in f:
+                line = line.strip()
+                data = json.loads(line)
+                txt_data.append(data)
+
+        output_format = output_format.strip().lower()
+        if output_format == "json":
+            with open(f"{output_filename}.json", "w", encoding="utf-8") as f:
+                json.dump(txt_data, f, indent=4)
+                _SimMonitor.reprint(f"Results saved to {Path(output_filename)} as .json file")
+        elif output_format == "csv":
+            output_csv_header = txt_data[0].keys()
+            with open(f"{output_filename}.csv", "w", newline= "") as f:
+                output_writer = csv.DictWriter(f, fieldnames=output_csv_header)
+                output_writer.writeheader()
+                output_writer.writerows(txt_data)
+                _SimMonitor.reprint(f"Results saved to {Path(output_filename)} as .csv file")
+
     def __terminate_simulation(self):
         """
         Terminates the simulation, closes the files and prints the results.

tests/unit/simulation/test_monte_carlo.py

@@ -1,6 +1,9 @@
 import matplotlib as plt
 import numpy as np
 import pytest
+import json
+import csv
+import os
 
 from rocketpy.simulation import MonteCarlo
 
@@ -185,3 +188,46 @@ def test_estimate_confidence_interval_raises_type_error_for_invalid_statistic():
 
     with pytest.raises(TypeError):
         mc.estimate_confidence_interval("apogee", statistic="not_a_function")
+
+
+def test_export_results_creates_csv_and_json_files(monte_carlo_calisto, tmp_path):
+    """Checks that the export_results create .csv and .json files
+
+    Parameters
+    ----------
+    monte_carlo_calisto : MonteCarlo
+        Fixture that has the .txt files necessary for the export_results
+    """
+    try:
+        mc = monte_carlo_calisto
+        mc.filename = tmp_path / "mock_output"
+        mock_data = {"apogee": 100, "max_velocity": 255}
+        with open(tmp_path / "mock_output.outputs.txt", "w") as f:
+            f.write(json.dumps(mock_data) + "\n")
+
+        mc.export_results(tmp_path / "mock_outputs_in_csv", "csv")
+        expected_file_in_csv = tmp_path / f"{"mock_outputs_in_csv"}.csv"
+        assert expected_file_in_csv.exists()
+        with open(expected_file_in_csv, "r") as f:
+            reader = csv.DictReader(f)
+            rows = list(reader)
+            assert len(rows) == 1
+            assert rows[0]["apogee"] == "100"
+            assert rows[0]["max_velocity"] == "255"
+
+        mc.export_results(tmp_path / "mock_output_in_json", "json")
+        expected_file_in_json = tmp_path / "mock_output_in_json.json"
+        assert expected_file_in_json.exists()
+        with open(expected_file_in_json, "r") as f:
+            data = json.load(f)
+            assert len(data) == 1
+            assert data[0]["apogee"] == 100
+            assert data[0]["max_velocity"] == 255
+    finally:
+        for filepath in [
+            "monte_carlo_test.errors.txt",
+            "monte_carlo_test.inputs.txt",
+            "monte_carlo_test.outputs.txt",
+        ]:
+            if os.path.exists(filepath):
+                os.remove(filepath)