我无法在没有白色边框的情况下保存图像,并且在初始分辨率下(1037x627
)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import pyplot, lines
import matplotlib.image as mpimg
from matplotlib.patches import Ellipse
x=[0,0,0,0,0]
y=[0,0,0,0,0]
a=10**1.3*15
inc=25
b=np.cos(np.radians(inc))*a
x[0],y[0]=516.667,313.021
x[1],y[1]=x[0]-a,y[0]
x[2],y[2]=x[0]+a,y[0]
x[3],y[3]=x[0],y[0]+b
x[4],y[4]=x[0],y[0]-b
for pa in range(0,10,5):
fig, ax = plt.subplots()
img=mpimg.imread('IC342.png')
imgplot = plt.imshow(img)
x[1],y[1]=x[0]-a/2*np.cos(np.radians(pa)),y[0]-a/2*np.sin(np.radians(pa))
x[2],y[2]=x[0]+a/2*np.cos(np.radians(pa)),y[0]+a/2*np.sin(np.radians(pa))
x[3],y[3]=x[0]+b/2*np.cos(np.radians(pa+90)),y[0]+b/2*np.sin(np.radians(pa+90))
x[4],y[4]=x[0]-b/2*np.cos(np.radians(pa+90)),y[0]-b/2*np.sin(np.radians(pa+90))
ell = Ellipse(xy=[516.667,313.021], width=a, height=b, angle=pa, edgecolor='b',lw=4, alpha=0.5, facecolor='none')
name='plt'+str(pa)+'.png'
leg='PA='+str(pa)
#ax.text(10, 10, leg, fontsize=15,color='white')
ax.add_artist(ell)
xn=[x[1],x[2],x[0]]
yn=[y[1],y[2],y[0]]
xnw=[x[3],x[4],x[0]]
ynw=[y[3],y[4],y[0]]
line = lines.Line2D(xn, yn, linestyle='-.',lw=5., color='r', alpha=0.4)
line1 = lines.Line2D(xnw, ynw, linestyle='-.',lw=5., color='g', alpha=0.4)
ax.add_line(line)
ax.add_line(line1)
plt.axis('off')
fig.savefig(name, transparent=True, bbox_inches='tight', pad_inches=0,dpi=150 )
初始形象
结果
我还需要白色的文字 PA=something
而不改变分辨率。根据我的理解,添加另一个数字,如文字,可能会自动改变分辨率。
谢谢你的时间
这里有两个因素在起作用。
Axes
不占 Figure
默认matplotlib
జజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజ Figure
的大小是固定的,内容被拉伸挤压插值,以适应这个数字。 你想要的是 Figure
的大小由其内容来定义。要做你想做的事,有三个步骤。
让我们用美国国家航空航天局的哈勃图像来说明一下 http:/www.nasa.govsitesdefaultfilesthumbnailsimagehubble_friday_12102015.jpg. 这是一张1280x1216像素的图片。
这里有一个大量评论的例子来引导你。
import matplotlib.pyplot as plt
# On-screen, things will be displayed at 80dpi regardless of what we set here
# This is effectively the dpi for the saved figure. We need to specify it,
# otherwise `savefig` will pick a default dpi based on your local configuration
dpi = 80
im_data = plt.imread('hubble_friday_12102015.jpg')
height, width, nbands = im_data.shape
# What size does the figure need to be in inches to fit the image?
figsize = width / float(dpi), height / float(dpi)
# Create a figure of the right size with one axes that takes up the full figure
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0, 0, 1, 1])
# Hide spines, ticks, etc.
ax.axis('off')
# Display the image.
ax.imshow(im_data, interpolation='nearest')
# Add something...
ax.annotate('Look at This!', xy=(590, 650), xytext=(500, 500),
color='cyan', size=24, ha='right',
arrowprops=dict(arrowstyle='fancy', fc='cyan', ec='none'))
# Ensure we're displaying with square pixels and the right extent.
# This is optional if you haven't called `plot` or anything else that might
# change the limits/aspect. We don't need this step in this case.
ax.set(xlim=[-0.5, width - 0.5], ylim=[height - 0.5, -0.5], aspect=1)
fig.savefig('test.jpg', dpi=dpi, transparent=True)
plt.show()
保存的 test.jpg
将是精确的1280x1216像素。 当然,因为我们的输入和输出都使用了有损压缩格式,所以由于压缩伪影的影响,你不会得到完美的像素匹配。 不过如果你使用的是无损输入和输出格式,你应该。