指定Matplotlib网格上轴的最大范围。

问题描述 投票:0回答:1

我正在处理一些波形,需要一个网格。 对于X范围为 [0,20.500] 和y-范围为 [0,1800] 我尝试了以下代码。

%pylab
def grid(imgIn,bounds, axlabels):
  import numpy as np
  import matplotlib.pyplot as plt
  import matplotlib.ticker
  dpi=100
  size = (imgIn.size[0]/dpi,imgIn.size[1]/dpi)
  print(f'size={size}')
  plt.figure(figsize=size)
  plt.imshow(imgIn,'gray') # ,vmin=-1,vmax=1)

  plt.minorticks_on()
  from matplotlib.ticker import StrMethodFormatter
  plt.gca().xaxis.set_major_formatter(StrMethodFormatter('{x:,.0f}'))
  plt.gca().yaxis.set_major_formatter(StrMethodFormatter('{x:,.2f}'))
  import matplotlib.ticker as plticker
  plt.gca().xaxis.set_minor_locator\
     (matplotlib.ticker.MultipleLocator(bounds[0][1]))
  plt.gca().yaxis.set_minor_locator\
    (matplotlib.ticker.MultipleLocator(bounds[1][1]))
  plt.grid(which="both", linewidth=0.72,color="k")
  plt.tick_params(which="minor", length=0)
  plt.xlabel(axlabels[0])
  plt.ylabel(axlabels[1])
  import io
  buf = io.BytesIO()
  plt.savefig(buf, format='png', dpi=dpi,bbox_inches='tight')
  buf.seek(0)
  plt.close()
  bytes = buf.getvalue()
  return bytes

from PIL import Image as PImage
import requests
from io import BytesIO
response = requests.get('https://i.pinimg.com/564x/d2/cf/81/d2cf8152167a978747d15f3ce3bd6835.jpg')
imgaa = PImage.open(BytesIO(response.content))
T = 20.5
yMax = 1800
imgBytes = grid(imgaa,[(0,T),(0,yMax)],('Elapsed Time','Frequency'))
import io
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
ax.axis('off')
im = PImage.open(io.BytesIO(imgBytes))
ax.imshow(im,aspect='auto')    

enter image description here

所以从积极的一面来看 -- 这确实创建了一个网格。 但缺点是

  1. 网格的范围没有被尊重
  2. y轴从上往下数,从下往上数,从上往下数。

我不确定如何解决这两个问题。感谢指点!

python matplotlib grid
1个回答
1
投票

我已经清理了很多代码,在一个更简单的基础上工作。我现在剩下的是以下代码。

from io import BytesIO
import matplotlib.pyplot as plt
from PIL import Image as PImage
import requests

response = requests.get(
    'https://i.pinimg.com/564x/d2/cf/81/d2cf8152167a978747d15f3ce3bd6835.jpg')
image = PImage.open(BytesIO(response.content))
dpi = 100
size = (image.size[0] / dpi, image.size[1] / dpi)
fig, ax = plt.subplots(figsize=size)
ax.imshow(image, extent=[0, 20.5, 0, 1800], aspect='auto')
ax.grid(which='both', color='black', linewidth=2)
ax.minorticks_on()
ax.tick_params(which='minor', length=0)
ax.set_xlabel('Elapsed Time')
ax.set_ylabel('Frequency')
plt.show()

显示

enter image description here

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