[英]Combine multiple matplotlib figures into one
我有一個函數,它采用增強的 dicom 文件並執行以下操作:
當我調用該函數時,我可以創建多個顯示在不同圖形中的圖像。 那么,我怎樣才能將所有這些數字合二為一呢? 理想情況下,我想以 3x3 網格顯示它們。
這是我當前的代碼:
import matplotlib.pyplot as plt
import pydicom # Used for opening DICOM files
import numpy as np # General mathematical package
from pylab import text
# Import DICOM files
filename = "U:/File location"
ds = pydicom.dcmread(filename)
# Speck Locations
centerSpeck = (1690, 1477)
centerSpeck2 = (100, 100)
twelveOclockSpeck = (45, 84)
twoOkclockSpeck = (66, 148)
tenOclockSpeck = (136, 147)
fiveOclockSpeck = (157, 82)
sevenOclockSpeck = (102, 41)
backgroundSignalValue = (71, 63)
speckLocations = np.array([centerSpeck2, twelveOclockSpeck, twoOkclockSpeck, fiveOclockSpeck, sevenOclockSpeck, tenOclockSpeck, backgroundSignalValue])
# Function that draws a circle around a given pixel
def drawCircle(arrayToPLot, zeroIndex, oneIndex, specks, r = 10):
x = speckLocations[:,1] # get x axis variables from the speckLocations array
y = speckLocations[:,0] # get y axis variables from the speckLocations array
for i in range(zeroIndex,oneIndex,1): # For loop, note that the function range is: range(start, stop, step)
tempIm = arrayToPLot.pixel_array[i,:,:].astype(float) # Get one slice as float
slicedArray = tempIm[centerSpeck[0]-100:centerSpeck[0]+100, centerSpeck[1]-100:centerSpeck[1]+100].astype(float)
for x,y in (speckLocations):
plt.imshow(slicedArray, cmap='gray')
circle = plt.Circle((y, x),r, fc='none', ec="red")
plt.gca().add_patch(circle)
text(10, 180, i, fontsize=12, color='red') # Print the current slice on the image
plt.show() # Plot each slice with circles drawn around all the specks and the background signal value location
#Call the function
drawCircle(ds, 33, 34, speckLocations)
在下文中,我們將使用plt.subplots
方法生成圖形和axes
網格,即有人理解為子圖的 Matplotlib 對象......
二維網格上的迭代首先為您提供一行網格,該行上的第二次迭代為您提供單個子圖。 當我們挑選出一個軸時,是時候調用您的函數(您有責任區分要繪制的數據,因為從您的問題中不清楚您想要做什么),但是有一個額外的參數,即當前軸。
fig, ax_grid = plt.subplots(3,3)
for ax_row in ax_grid:
for ax in ax_row:
drawCircle(ax, ds, 33, 34, speckLocations)
plt.tight_layout()
plt.show()
最后我們展示圖,調用tight_layout
以獲得更好的子圖排列。
當然,我們必須修改圓繪圖函數……首先我們將ax
添加到參數列表中,接下來我們修改對plt
方法的調用以使用ax
對象的方法:
def drawCircle(ax, arrayToPLot, zeroIndex, oneIndex, specks, r = 10):
...
ax.imshow(...)
...
ax.add_patch(circle)
ax.text(10, 180, i, fontsize=12, color='red')
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