Add files from test project

scripts/plot_solution_curve.py

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+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+import argparse
+
+
+def plot_2d(df: pd.DataFrame):
+    df = pd.read_csv("temp.csv")
+
+    fig = plt.figure()
+    plt.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95)
+    ax = fig.add_subplot()
+
+    # Analytically computed solution
+    ts = df['tb']
+    x2s = -ts / 2
+    x1s = -ts * x2s
+
+    ax.scatter(x1s, x2s)
+
+    ax.set_xlabel("x1")
+    ax.set_ylabel("x2")
+    # ax.set_zlabel("t")
+
+    df = df.reset_index()
+
+    for _, row in df.iterrows():
+        x1b = row['x1b']
+        x2b = row['x2b']
+        # x1p = row['x1p']
+        # x2p = row['x2p']
+        x1e = row['x1e']
+        x2e = row['x2e']
+        x1n = row['x1n']
+        x2n = row['x2n']
+
+        ax.plot([x1b, x1e], [x2b, x2e], 'b')
+        ax.plot([x1e, x1n], [x2e, x2n], 'r')
+
+    plt.show()
+
+
+def plot_3d(df: pd.DataFrame):
+    df = pd.read_csv("temp.csv")
+
+    fig = plt.figure()
+    plt.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95)
+    ax = fig.add_subplot(projection='3d')
+
+    # Analytically computed solution
+    ts = df['tb']
+    x2s = -ts / 2
+    x1s = -ts * x2s
+
+    ax.scatter(x1s, x2s)
+    ax.scatter(x1s, x2s, ts)
+
+    ax.set_xlabel("x1")
+    ax.set_ylabel("x2")
+    ax.set_zlabel("t")
+
+    df = df.reset_index()
+
+    for _, row in df.iterrows():
+        x1b = row['x1b']
+        x2b = row['x2b']
+        tb = row['tb']
+        # x1p = row['x1p']
+        # x2p = row['x2p']
+        # tp  = row['tp']
+        x1e = row['x1e']
+        x2e = row['x2e']
+        te = row['te']
+        x1n = row['x1n']
+        x2n = row['x2n']
+        tn = row['tn']
+
+        ax.plot([x1b, x1e], [x2b, x2e], 'b', zs=[tb, te])
+        ax.plot([x1e, x1n], [x2e, x2n], 'r', zs=[te, tn])
+
+    plt.show()
+
+
+def main():
+    # Parse command line arguments
+
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--input", "-i", type=str, required=True,
+                        default="temp.csv", help="Filename of the csv file")
+    parser.add_argument("--projection", "-p", type=str, required=False,
+                        default="2d", help="2d or 3d plot")
+
+    args = parser.parse_args()
+
+    # Plot data
+    df = pd.read_csv(args.input)
+
+    if args.projection == "2d":
+        plot_2d(df)
+    elif args.projection == "3d":
+        plot_3d(df)
+
+
+if __name__ == "__main__":
+    main()