pre class="prettyprint lang-*" linenums wrap="wrap" ggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggg
source: http://www.stylifyyourblog.com/2012/07/syntax-highlighting-in-blogger-using.html
The lang-* class specifies the language file extensions.
File extensions supported by default include
"bsh", "c", "cc", "cpp", "cs", "csh", "cyc", "cv", "htm", "html",
"java", "js", "m", "mxml", "perl", "pl", "pm", "py", "rb", "sh",
"xhtml", "xml", "xsl".
python 테스트import matplotlib.pyplot as plt
def get_demo_image():
import numpy as np
from matplotlib.cbook import get_sample_data
f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
z = np.load(f)
# z is a numpy array of 15x15
return z, (-3,4,-4,3)
def demo_simple_image(ax):
Z, extent = get_demo_image()
im = ax.imshow(Z, extent=extent, interpolation="nearest")
cb = plt.colorbar(im)
plt.setp(cb.ax.get_yticklabels(), visible=False)
def demo_locatable_axes_hard(fig1):
from mpl_toolkits.axes_grid1 \
import SubplotDivider, LocatableAxes, Size
divider = SubplotDivider(fig1, 2, 2, 2, aspect=True)
# axes for image
ax = LocatableAxes(fig1, divider.get_position())
# axes for coloarbar
ax_cb = LocatableAxes(fig1, divider.get_position())
h = [Size.AxesX(ax), # main axes
Size.Fixed(0.05), # padding, 0.1 inch
Size.Fixed(0.2), # colorbar, 0.3 inch
]
v = [Size.AxesY(ax)]
divider.set_horizontal(h)
divider.set_vertical(v)
ax.set_axes_locator(divider.new_locator(nx=0, ny=0))
ax_cb.set_axes_locator(divider.new_locator(nx=2, ny=0))
fig1.add_axes(ax)
fig1.add_axes(ax_cb)
ax_cb.axis["left"].toggle(all=False)
ax_cb.axis["right"].toggle(ticks=True)
Z, extent = get_demo_image()
im = ax.imshow(Z, extent=extent, interpolation="nearest")
plt.colorbar(im, cax=ax_cb)
plt.setp(ax_cb.get_yticklabels(), visible=False)
def demo_locatable_axes_easy(ax):
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(ax)
ax_cb = divider.new_horizontal(size="5%", pad=0.05)
fig1 = ax.get_figure()
fig1.add_axes(ax_cb)
Z, extent = get_demo_image()
im = ax.imshow(Z, extent=extent, interpolation="nearest")
plt.colorbar(im, cax=ax_cb)
ax_cb.yaxis.tick_right()
for tl in ax_cb.get_yticklabels():
tl.set_visible(False)
ax_cb.yaxis.tick_right()
def demo_images_side_by_sied(ax):
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(ax)
Z, extent = get_demo_image()
ax2 = divider.new_horizontal(size="100%", pad=0.05)
fig1 = ax.get_figure()
fig1.add_axes(ax2)
ax.imshow(Z, extent=extent, interpolation="nearest")
ax2.imshow(Z, extent=extent, interpolation="nearest")
for tl in ax2.get_yticklabels():
tl.set_visible(False)
def demo():
fig1 = plt.figure(1, (6, 6))
fig1.clf()
## PLOT 1
# simple image & colorbar
ax = fig1.add_subplot(2, 2, 1)
demo_simple_image(ax)
## PLOT 2
# image and colorbar whose location is adjusted in the drawing time.
# a hard way
demo_locatable_axes_hard(fig1)
## PLOT 3
# image and colorbar whose location is adjusted in the drawing time.
# a easy way
ax = fig1.add_subplot(2, 2, 3)
demo_locatable_axes_easy(ax)
## PLOT 4
# two images side by sied with fixed padding.
ax = fig1.add_subplot(2, 2, 4)
demo_images_side_by_sied(ax)
plt.draw()
plt.show()
demo()
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