diff --git a/test.py b/test.py
deleted file mode 100644
index 0b87ca0bfe99402dbef1d31ad8d2cc799d2d0ce3..0000000000000000000000000000000000000000
--- a/test.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import matplotlib.pyplot as plt
-import numpy as np
-
-np.random.seed(19680801)
-
-
-def gradient_image(ax, direction=1, cmap_range=(0, 1), **kwargs):
-    """
-    Draw a gradient image based on a colormap.
-
-    Parameters
-    ----------
-    ax : Axes
-        The Axes to draw on.
-    direction : float
-        The direction of the gradient. This is a number in
-        range 0 (=vertical) to 1 (=horizontal).
-    cmap_range : float, float
-        The fraction (cmin, cmax) of the colormap that should be
-        used for the gradient, where the complete colormap is (0, 1).
-    **kwargs
-        Other parameters are passed on to `.Axes.imshow()`.
-        In particular, *cmap*, *extent*, and *transform* may be useful.
-    """
-    phi = direction * np.pi / 2
-    v = np.array([np.cos(phi), np.sin(phi)])
-    X = np.array([[v @ [1, 0], v @ [1, 1]],
-                  [v @ [0, 0], v @ [0, 1]]])
-    a, b = cmap_range
-    X = a + (b - a) / X.max() * X
-    im = ax.imshow(X, interpolation='bicubic', clim=(0, 1),
-                   aspect='auto', **kwargs)
-    return im
-
-
-def gradient_bar(ax, x, y, width=0.5, bottom=0):
-    for left, top in zip(x, y):
-        right = left + width
-        gradient_image(ax, extent=(left, right, bottom, top),
-                       cmap=plt.cm.Blues_r, cmap_range=(0, 0.8))
-
-
-fig, ax = plt.subplots()
-ax.set(xlim=(0, 10), ylim=(0, 1))
-
-N = 10
-x = np.arange(N) + 0.15
-y = np.random.rand(N)
-gradient_bar(ax, x, y, width=0.7)
-plt.show()
\ No newline at end of file