From 9b9eaa656615cd12c6b2278de51f7a07b25d01b3 Mon Sep 17 00:00:00 2001
From: Andreas Tsouchlos <an.tsouchlos@gmail.com>
Date: Mon, 5 Dec 2022 14:52:14 +0100
Subject: [PATCH] Implemented pgf_reformat_data_3d

---
 sw/utility/misc.py | 45 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 45 insertions(+)

diff --git a/sw/utility/misc.py b/sw/utility/misc.py
index 93912e2..401c2d9 100644
--- a/sw/utility/misc.py
+++ b/sw/utility/misc.py
@@ -1,5 +1,8 @@
 import unicodedata
 import re
+import typing
+import pandas as pd
+import numpy as np
 
 
 def slugify(value, allow_unicode=False):
@@ -20,3 +23,45 @@ def slugify(value, allow_unicode=False):
             'ascii')
     value = re.sub(r'[^\w\s-]', '', value.lower())
     return re.sub(r'[-\s]+', '-', value).strip('-_')
+
+
+def pgf_reformat_data_3d(results: typing.Sequence, x_param_name: str,
+                         y_param_name: str,
+                         z_param_names: typing.Sequence[str]):
+    """Reformat the results obtained from the GenericMultithreadedSimulator
+    into a form usable by pgfplots.
+
+    :param results: Results from GenericMultiThreadedSimulator
+    (dict of the form {params1: results1, params2: results2, ...}),
+    where resultsN and paramsN are themselves dicts:
+        paramsN = {param_name_1: val, param_name_2: val, ...}
+        resultsN = {result_name_1: val, result_name_2: val, ...}
+    :param x_param_name:
+    :param y_param_name:
+    :param z_param_names:
+    :return: pandas DataFrame of the following form:
+        {x_param_name: [x1, x1, x1, ..., x2, x2, x2, ...],
+        y_param_name: [y1, y2, y3, ..., y1, y2, y3, ...],
+        z_param_name: [z11, z21, z31, ..., z12, z22, z32, ...]}
+    """
+    # Create result variables
+    x = np.zeros(len(results))
+    y = np.zeros(len(results))
+    zs = {name: np.zeros(len(results)) for name in z_param_names}
+
+    # Populate result variables
+    for i, (params, result) in enumerate(results.items()):
+        x_val = params[x_param_name]
+        y_val = params[y_param_name]
+        for z_param_name in z_param_names:
+            zs[z_param_name][i] = result[z_param_name]
+
+        x[i] = x_val
+        y[i] = y_val
+
+    # Create and return pandas DataFrame
+    df = pd.DataFrame({x_param_name: x, y_param_name: y})
+    for z_param_name in z_param_names:
+        df[z_param_name] = zs[z_param_name]
+
+    return df.sort_values(by=[x_param_name, y_param_name])