1 files changed, 0 insertions, 51 deletions
diff --git a/test_diff.py b/test_diff.py
deleted file mode 100644
index 4429894..0000000
--- a/test_diff.py
+++ /dev/null
@@ -1,51 +0,0 @@
-import numpy as np
-from scipy.optimize import minimize
-from colour import *
-from colour.recovery import error_function_Jakob2019
-from matplotlib import pyplot as plt
-from gsoc_common import plot_comparison
-
-
-# This test checks if derivatives are calculated correctly by comparing them
-# to finite differences.
-if __name__ == "__main__":
-    shape = SpectralShape(360, 830, 1)
-    cmfs = STANDARD_OBSERVER_CMFS["CIE 1931 2 Degree Standard Observer"].align(shape)
-
-    illuminant = SpectralDistribution(ILLUMINANT_SDS["D65"]).align(shape)
-    illuminant_XYZ = sd_to_XYZ(illuminant) / 100
-
-    target = np.array([50, -20, 30]) # Some arbitrary Lab colour
-    xs = np.linspace(-10, 10, 500)
-    h = xs[1] - xs[0]
-
-    # Vary one coefficient at a time
-    for c_index in range(3):
-        errors = np.empty(len(xs))
-        derrors = np.empty(len(xs))
-
-        for i, x in enumerate(xs):
-            c = np.array([1.0, 1, 1])
-            c[c_index] = x
-
-            error, derror_dc = error_function_Jakob2019(
-                c, target, shape, cmfs, illuminant, illuminant_XYZ
-            )
-
-            errors[i] = error
-            derrors[i] = derror_dc[c_index]
-
-
-        plt.subplot(2, 3, 1 + c_index)
-        plt.xlabel("c%d" % c_index)
-        plt.ylabel("ΔE")
-        plt.plot(xs, errors)
-
-        plt.subplot(2, 3, 4 + c_index)
-        plt.xlabel("c%d" % c_index)
-        plt.ylabel("dΔE/dc%d" % c_index)
-
-        plt.plot(xs, derrors, "k-")
-        plt.plot(xs[:-1] + h / 2, np.diff(errors) / h, "r:")
-
-    plt.show()