python-Matplotlib散点图-删除白色填充

我正在使用matplotlib在纬度经度坐标中绘制变量.问题在于该图像不能包含轴或边界.我已经能够移除轴,但是必须完全移除图像周围的白色填充(请参见下面的代码示例图像：http://imgur.com/a/W0vy9).

我已经尝试了Google搜索提供的几种方法,包括以下StackOverflow方法：

Remove padding from matplotlib plotting

How to remove padding/border in a matplotlib subplot (SOLVED)

Matplotlib plots: removing axis, legends and white spaces

但是移除空白没有任何作用.如果您有任何建议(即使是放弃matplotlib并尝试使用另一个绘图库),我也将不胜感激！

这是我正在使用的代码的基本形式,它显示了这种行为：

import numpy as np
import matplotlib
from mpl_toolkits.basemap import Basemap
from scipy import stats

lat = np.random.randint(-60.5, high=60.5, size=257087)
lon = np.random.randint(-179.95, high=180, size=257087)
maxnsz =  np.random.randint(12, 60, size=257087)

percRange = np.arange(100,40,-1)
percStr=percRange.astype(str)
val_percentile=np.percentile(maxnsz, percRange, interpolation='nearest')  

#Rank all values
all_percentiles=stats.rankdata(maxnsz)/len(maxnsz)
#Figure setup
fig = matplotlib.pyplot.figure(frameon=False, dpi=600)
#Basemap code can go here

x=lon
y=lat

cmap = matplotlib.cm.get_cmap('cool')


h=np.where(all_percentiles >= 0.999)
hl=np.where((all_percentiles < 0.999) & (all_percentiles > 0.90))
mh=np.where((all_percentiles > 0.75) & (all_percentiles < 0.90))
ml=np.where((all_percentiles >= 0.4) & (all_percentiles < 0.75))
l=np.where(all_percentiles < 0.4)

all_percentiles[h]=0
all_percentiles[hl]=0.25
all_percentiles[mh]=0.5
all_percentiles[ml]=0.75
all_percentiles[l]=1

rgba_low=cmap(1)
rgba_ml=cmap(0.75)
rgba_mh=cmap(0.51)
rgba_hl=cmap(0.25)
rgba_high=cmap(0)

matplotlib.pyplot.axis('off')

matplotlib.pyplot.scatter(x[ml],y[ml], c=rgba_ml, s=3, marker=',',edgecolor='none', alpha=0.4)
matplotlib.pyplot.scatter(x[mh],y[mh], c=rgba_mh, s=3,     marker='o', edgecolor='none', alpha=0.5)
matplotlib.pyplot.scatter(x[hl],y[hl], c=rgba_hl, s=4, marker='*',edgecolor='none', alpha=0.6)
matplotlib.pyplot.scatter(x[h],y[h], c=rgba_high, s=5, marker='^', edgecolor='none',alpha=0.75)

fig.savefig('/home/usr/code/python/testfig.jpg', bbox_inches=0, nbins=0, transparent="True", pad_inches=0.0)
fig.canvas.draw()

解决方法:

问题在于,在Matplotlib plots: removing axis, legends and white spaces处给出的所有解决方案实际上都旨在与imshow一起使用.

因此,以下显然有效

import matplotlib.pyplot as plt

fig = plt.figure()
ax=fig.add_axes([0,0,1,1])
ax.set_axis_off()

im = ax.imshow([[2,3,4,1], [2,4,4,2]], origin="lower", extent=[1,4,2,8])
ax.plot([1,2,3,4], [2,3,4,8], lw=5)

ax.set_aspect('auto')
plt.show()

并产生

但是在这里,您正在使用分散.添加散点图

import matplotlib.pyplot as plt

fig = plt.figure()
ax=fig.add_axes([0,0,1,1])
ax.set_axis_off()


im = ax.imshow([[2,3,4,1], [2,4,4,2]], origin="lower", extent=[1,4,2,8])
ax.plot([1,2,3,4], [2,3,4,8], lw=5)

ax.scatter([2,3,4,1], [2,3,4,8], c="r", s=2500)

ax.set_aspect('auto')
plt.show()

产生

散点的特殊之处在于,默认情况下matplotlib会尝试使所有点可见,这意味着已设置轴限制,以使所有散点都整体可见.

为了克服这个问题,我们需要专门设置轴限制：

import matplotlib.pyplot as plt

fig = plt.figure()
ax=fig.add_axes([0,0,1,1])
ax.set_axis_off()

im = ax.imshow([[2,3,4,1], [2,4,4,2]], origin="lower", extent=[1,4,2,8])
ax.plot([1,2,3,4], [2,3,4,8], lw=5)

ax.scatter([2,3,4,1], [2,3,4,8], c="r", s=2500)

ax.set_xlim([1,4])
ax.set_ylim([2,8])

ax.set_aspect('auto')
plt.show()

这样我们将获得所需的行为.

标签：scatter-plot,matplotlib,data-visualization,python
来源： https://codeday.me/bug/20191112/2024108.html