# We want an image which has a background color of bluish green, with an

# alpha of 0.25.

fig = Figure([1, 0.4])

canvas = FigureCanvas(fig)

fig.set_facecolor((0, 1, 0.4))

fig.patch.set_alpha(0.25)

# The target color is fig.patch.get_facecolor()

buf = io.BytesIO()

fig.savefig(buf,

facecolor=fig.get_facecolor(),

edgecolor='none')

# Save the figure again to check that the

# colors don't bleed from the previous renderer.

buf.seek(0)

fig.savefig(buf,

facecolor=fig.get_facecolor(),

edgecolor='none')

# Check the first pixel has the desired color & alpha

# (approx: 0, 1.0, 0.4, 0.25)

buf.seek(0)

assert_array_almost_equal(tuple(imread(buf)[0, 0]),

(0.0, 1.0, 0.4, 0.250),

buff = io.BytesIO()

# Generates a too-large single path in a path collection that

# would cause a segfault if the draw_markers optimization is

# applied.

f, ax = plt.subplots()

collection = collections.PathCollection(

[path.Path([[-10, 5], [10, 5], [10, -5], [-10, -5], [-10, 5]])])

ax.add_artist(collection)

ax.set_xlim(10**-3, 1)

# This creates a marker with nans in it, which was segfaulting the

# Agg backend (see #3722)

fig, ax = plt.subplots(1)

steps = 1000

data = np.arange(steps)

ax.semilogx(data)

ax.fill_between(data, data*0.8, data*1.2)

buf = io.BytesIO()

buff = io.BytesIO()

fig, ax = plt.subplots()

np.random.seed(0)

points = np.random.rand(70000)

ax.plot(points)

def smooth1d(x, window_len):

s = np.r_[2*x[0] - x[window_len:1:-1],

x,

2*x[-1] - x[-1:-window_len:-1]]

w = np.hanning(window_len)

y = np.convolve(w/w.sum(), s, mode='same')

return y[window_len-1:-window_len+1]

def smooth2d(A, sigma=3):

window_len = max(int(sigma), 3)*2 + 1

A1 = np.array([smooth1d(x, window_len) for x in np.asarray(A)])

A2 = np.transpose(A1)

A3 = np.array([smooth1d(x, window_len) for x in A2])

A4 = np.transpose(A3)

return A4

class BaseFilter(object):

def prepare_image(self, src_image, dpi, pad):

ny, nx, depth = src_image.shape

padded_src = np.zeros([pad*2 + ny, pad*2 + nx, depth], dtype="d")

padded_src[pad:-pad, pad:-pad, :] = src_image[:, :, :]

return padded_src # , tgt_image

def get_pad(self, dpi):

return 0

def __call__(self, im, dpi):

pad = self.get_pad(dpi)

padded_src = self.prepare_image(im, dpi, pad)

tgt_image = self.process_image(padded_src, dpi)

return tgt_image, -pad, -pad

class OffsetFilter(BaseFilter):

def __init__(self, offsets=None):

if offsets is None:

self.offsets = (0, 0)

else:

self.offsets = offsets

def get_pad(self, dpi):

return int(max(*self.offsets)/72.*dpi)

def process_image(self, padded_src, dpi):

ox, oy = self.offsets

a1 = np.roll(padded_src, int(ox/72.*dpi), axis=1)

a2 = np.roll(a1, -int(oy/72.*dpi), axis=0)

return a2

class GaussianFilter(BaseFilter):

"simple gauss filter"

def __init__(self, sigma, alpha=0.5, color=None):

self.sigma = sigma

self.alpha = alpha

if color is None:

self.color = (0, 0, 0)

else:

self.color = color

def get_pad(self, dpi):

return int(self.sigma*3/72.*dpi)

def process_image(self, padded_src, dpi):

tgt_image = np.zeros_like(padded_src)

aa = smooth2d(padded_src[:, :, -1]*self.alpha,

self.sigma/72.*dpi)

tgt_image[:, :, -1] = aa

tgt_image[:, :, :-1] = self.color

return tgt_image

class DropShadowFilter(BaseFilter):

def __init__(self, sigma, alpha=0.3, color=None, offsets=None):

self.gauss_filter = GaussianFilter(sigma, alpha, color)

self.offset_filter = OffsetFilter(offsets)

def get_pad(self, dpi):

return max(self.gauss_filter.get_pad(dpi),

self.offset_filter.get_pad(dpi))

def process_image(self, padded_src, dpi):

t1 = self.gauss_filter.process_image(padded_src, dpi)

t2 = self.offset_filter.process_image(t1, dpi)

return t2

fig = plt.figure()

ax = fig.add_subplot(111)

# draw lines

l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-",

mec="b", mfc="w", lw=5, mew=3, ms=10, label="Line 1")

l2, = ax.plot([0.1, 0.5, 0.9], [0.5, 0.2, 0.7], "ro-",

mec="r", mfc="w", lw=5, mew=3, ms=10, label="Line 1")

gauss = DropShadowFilter(4)

for l in [l1, l2]:

# draw shadows with same lines with slight offset.

xx = l.get_xdata()

yy = l.get_ydata()

shadow, = ax.plot(xx, yy)

shadow.update_from(l)

# offset transform

ot = mtransforms.offset_copy(l.get_transform(), ax.figure,

x=4.0, y=-6.0, units='points')

shadow.set_transform(ot)

# adjust zorder of the shadow lines so that it is drawn below the

# original lines

shadow.set_zorder(l.get_zorder() - 0.5)

shadow.set_agg_filter(gauss)

shadow.set_rasterized(True) # to support mixed-mode renderers

ax.set_xlim(0., 1.)

ax.set_ylim(0., 1.)

ax.xaxis.set_visible(False)

fig = plt.figure(figsize=(300, 1000))

buff = io.BytesIO()

with pytest.raises(ValueError):

x = range(200)

# Test without chunksize

fig, ax = plt.subplots()

ax.plot(x, np.sin(x))

fig.canvas.draw()

# Test with chunksize

fig, ax = plt.subplots()

rcParams['agg.path.chunksize'] = 105

ax.plot(x, np.sin(x))