本文整理汇总了Python中matplotlib.pyplot.barbs方法的典型用法代码示例。如果您正苦于以下问题：Python pyplot.barbs方法的具体用法？Python pyplot.barbs怎么用？Python pyplot.barbs使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类matplotlib.pyplot的用法示例。
在下文中一共展示了pyplot.barbs方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_streamplot_limits
# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import barbs [as 别名]
def test_streamplot_limits():
ax = plt.axes()
x = np.linspace(-5, 10, 20)
y = np.linspace(-2, 4, 10)
y, x = np.meshgrid(y, x)
trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
plt.barbs(x, y, np.sin(x), np.cos(y), transform=trans)
# The calculated bounds are approximately the bounds of the original data,
# this is because the entire path is taken into account when updating the
# datalim.
assert_array_almost_equal(ax.dataLim.bounds, (20, 30, 15, 6),
decimal=1) 示例2: test_barb_limits
# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import barbs [as 别名]
def test_barb_limits():
ax = plt.axes()
x = np.linspace(-5, 10, 20)
y = np.linspace(-2, 4, 10)
y, x = np.meshgrid(y, x)
trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
plt.barbs(x, y, np.sin(x), np.cos(y), transform=trans)
# The calculated bounds are approximately the bounds of the original data,
# this is because the entire path is taken into account when updating the
# datalim.
assert_array_almost_equal(ax.dataLim.bounds, (20, 30, 15, 6),
decimal=1) 示例3: plot_wind_axes
# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import barbs [as 别名]
def plot_wind_axes(axes):
# plot wind barbs
# TODO: also do storm-relative winds
draw_wind_line(axes)
axes.set_axis_off()
axes.axis([-1,1,pbot,ptop]) 示例4: plot_wind
# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import barbs [as 别名]
def plot_wind(axes, z, p, u, v, x=0):
for i in np.arange(0,len(z),1):
if (p[i] > pt_plot):
plt.barbs(x,p[i],u[i],v[i], length=5, linewidth=.5) 示例5: plot_wind_barbs
# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import barbs [as 别名]
def plot_wind_barbs(axes, z, p, u, v):
for i in np.arange(0,len(z)):
if (p[i] > pt_plot):
plt.barbs(0,p[i],u[i],v[i], length=5, linewidth=.5) 示例6: plot
# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import barbs [as 别名]
def plot(loc, z, th, p, qv, u, v, output, time = None, title = None):
"""Plots Skew-T/Log-P diagrapms with hodograph
The helper functions above facilitate loading data from
various formats and then call this function. If you have
data in another format or arrays of data in python already,
then this is the function you want to use.
:parameter loc: Location string
:parameter z: z grid mesh (1D)
:parameter time: Time string
:parameter th: Potential temperature at z points
:parameter p: Pressure at z points
:parameter qv: Water vapor mixing ratio at z points
:parameter u: u winds at z points
:parameter v: v winds at z points
:parameter title: Title for plot
:parameter output: Filename to save plot to
"""
fig = plt.figure(1, figsize=(10, 8), dpi=300, edgecolor='k')
# sounding
ax1 = plt.subplot(121)
plot_sounding_axes(ax1)
plot_sounding(ax1, z, th, p, qv, None, None)
# hodograph
ax2 = plt.subplot(222)
plot_hodo_axes(ax2)
plot_hodograph(ax2, z, u, v)
# datablock
ax3 = fig.add_subplot(224)
try:
plot_datablock(ax3, loc, z, time, th, p, qv, u, v, title)
except:
print("Error calcualting sounding stats, datablock omitted");
# wind barbs
ax4 = fig.add_subplot(132)
plot_wind_axes(ax4)
plot_wind_barbs(ax4,z,p,u,v)
# legend
ax5 = fig.add_subplot(4,4,15)
plot_legend(ax5)
# Adjust plot margins.
plt.subplots_adjust(left=0.03, bottom=0.03, right=0.97, top=0.97, wspace=0.12, hspace=0.12)
plt.savefig(output, dpi=300,bbox_inches=0)
plt.close()