Fits图片互相关交互
作者：互联网
import tkinter
from astropy.io import fits
import numpy as np
import pickle
from astropy.io import fits
import matplotlib.pyplot as plt
import os
from matplotlib import widgets
def fitsData(fitsName):
with fits.open(fitsName) as hdul:
hdul.info()
data = hdul[0].data
shape = data.shape
data = data.reshape((shape[-1], shape[-2]))
return data
def plotContour(data, ax,base):
"""将一个矩阵的等高线画在对应的ax上,用base来衡量等高线的level"""
shape = data.shape
y, x = np.mgrid[0:shape[0],
0:shape[1]]
ax.contour(x, y, data, [-base, base, base * 1.41, base * 2, base * 2.83, base * 4,
base * 5.65, base * 7.99, base * 11.3, base * 16, base * 22.6, base * 32, base * 45.2,
base * 64], colors='black')
def plotBox(x,y,width,height,ax):
"""定义画方框的函数,依次对应方框左下角横纵坐标，宽度，高度以及对应的ax"""
ax.hlines(y=[y, y+height]
, xmin=x
, xmax=x+width
)
ax.vlines(x=[x,x+width]
, ymin=y
, ymax=y+height
)
def crossCorrelation(data1,data2,outFileName):
"""
:param data1: 第一个二维矩阵数据
:param data2: 第二个二维矩阵数据
:param outFileName: 输出pkl文件的名字，要写后缀
:param data1On: 默认为数据1在上，设置为False的话数据2在上
:return: 两个数据的cross-correlation，并将每个点的相关数据存储在一个pkl文件里
"""
shape1=data1.shape
shape2=data2.shape
"""取数据1的0行0列为初始点，让这个点在数据2的0行0列开始逐行逐列平移
现在初始点移动到了数据2的第x行第y列
"""
rho=[]
for i in range(shape2[0]):
for j in range(shape2[1]):
"""
包含的数据1的数据为数据1的第0行到shape1[0]-x行，第0列到shape1[1]-y列
包含数据2的数据为数据2的第x行到最后一行，第y列到最后一列.
"""
subData1=data1[0:shape1[0]-i,0:shape1[1]-j]
subData2=data2[i:,j:]
subShape1=subData1.shape
subShape2=subData2.shape
subMean1=subData1.mean()
subMean2=subData2.mean()
sum1=0
sum2=0
sum3=0
for x in range(subShape1[0]):
for y in range(subShape1[1]):
sum1=sum1+(subData1[x,y]-subMean1)*(subData2[-x,-y]-subMean2)
sum2=sum2+(subData1[x,y]-subMean1)**2*(subData2[-x,-y]-subMean2)**2
rho.append((i,j,sum1/(sum2**0.5)))
print(i,j)
with open(outFileName,'wb') as file:
pickle.dump(rho,file)
print("Cross_Correlation++++++++++++++++done")
class FitsGUI():
def __init__(self):
"""导入两个fits图片的数据"""
fitsName1='8GHz.fits'
fitsName2='22GHz.fits'
self.data1=fitsData(fitsName1)
self.data2 = fitsData(fitsName2)
self.shape1=self.data1.shape
self.shape2 = self.data1.shape
###############################################################################
"""
figure大小设置为10*10，分为四块，下面两块用来显示数据1与数据2，对应的ax为4*4，左侧与下侧空隙均为0.5.
一开始图1与2显示自己对应的fits,ax3用来显示最终相关的结果
"""
self.fig=plt.figure(figsize=(10,10))
self.ax1 = self.fig.add_axes([0.5 / 10, 0.5 / 10, 4/10, 4/10])
self.ax2 = self.fig.add_axes([5.5 / 10, 0.5 / 10, 4 / 10, 4 / 10])
self.ax3 = self.fig.add_axes([5.5 / 10, 5.5 / 10, 4 / 10, 4 / 10])
plotContour(self.data1,self.ax1,base=0.0015)
plotContour(self.data2, self.ax2,base=0.001)
###############################################################################
""""
滑块长度均为4，宽度为0.15，用来移动方框的滑块的长度设置为图片的长度
"""
##############################################
"""图1滑块设置，用来控制图1中方框左下角点的坐标"""
self.ax1XSliderAxes = self.fig.add_axes([0.5/10, 4.75/10, 4/10, 0.15/10])
self.ax1XSlider = widgets.Slider(ax=self.ax1XSliderAxes, valmin=0, valmax=self.shape1[1], valstep=1, label='X')
self.ax1YSliderAxes = self.fig.add_axes([4.75 / 10, 0.5 / 10, 0.15 / 10, 4 / 10])
self.ax1YSlider = widgets.Slider(ax=self.ax1YSliderAxes, valmin=0, valmax=self.shape1[0], valstep=1, label='Y'
,orientation='vertical')
##############################################
"""图2滑块设置，用来控制图2中方框左下角点的坐标"""
self.ax2XSliderAxes = self.fig.add_axes([5.5 / 10, 4.75 / 10, 4 / 10, 0.15 / 10])
self.ax2XSlider = widgets.Slider(ax=self.ax2XSliderAxes, valmin=0, valmax=self.shape2[1], valstep=1, label='X')
self.ax2YSliderAxes = self.fig.add_axes([9.75 / 10, 0.5 / 10, 0.15 / 10, 4 / 10])
self.ax2YSlider = widgets.Slider(ax=self.ax2YSliderAxes, valmin=0, valmax=self.shape2[0], valstep=1, label='Y'
, orientation='vertical')
#############################################
"""设置用来控制方框大小的滑块，这两个滑块放在图片左上方，分别代表方框的宽和高,上面控制方框高度，下面控制宽度，宽与高的最大值与图片长度相同"""
self.BoxWidthAxes=self.fig.add_axes([0.5/10, 9.2 / 10, 4 / 10, 0.15 / 10])
self.BoxWidthSlider=widgets.Slider(ax=self.BoxWidthAxes, valmin=0, valmax=self.shape2[1], valstep=1
, label='Width')
self.BoxHeightAxes = self.fig.add_axes([0.5 / 10, 9.65 / 10, 4 / 10, 0.15 / 10])
self.BoxHeightSlider = widgets.Slider(ax=self.BoxHeightAxes, valmin=0, valmax=self.shape2[0], valstep=1
,label='Height')
#############################################
"""所有滑块的变化都对应函数sliderChange"""
self.ax1XSlider.on_changed(self.sliderChange)
self.ax1YSlider.on_changed(self.sliderChange)
self.ax2XSlider.on_changed(self.sliderChange)
self.ax2YSlider.on_changed(self.sliderChange)
self.BoxHeightSlider.on_changed(self.sliderChange)
self.BoxWidthSlider.on_changed(self.sliderChange)
###############################################################################
"""选定好区域后，点击开始互相关按钮，开始计算最终成图"""
self.startbuttonAxes=self.fig.add_axes([2/10, 8 / 10, 1 / 10, 0.5 / 10])
self.startButton=widgets.Button(ax=self.startbuttonAxes,label='START')
self.startButton.on_clicked(self.buttonClick)
###############################################################################
plt.show()
def sliderChange(self,val):
"""开始画方框以及显示fits图片,也就是设置各个滑块的交互函数"""
self.ax1.cla()
self.ax2.cla()
plotContour(self.data1,self.ax1,base=0.0015)
plotContour(self.data2, self.ax2,base=0.001)
plotBox(ax=self.ax1,x=self.ax1XSlider.val,y=self.ax1YSlider.val,height=self.BoxHeightSlider.val
,width=self.BoxWidthSlider.val)
plotBox(ax=self.ax2, x=self.ax2XSlider.val, y=self.ax2YSlider.val, height=self.BoxHeightSlider.val
,width=self.BoxWidthSlider.val)
# print('数据1从第{}到第{}行，第{}列到第{}列'.format(self.ax1YSlider.val
# ,self.ax1YSlider.val+self.BoxHeightSlider.val
# ,self.ax1XSlider.val
# ,self.ax1XSlider.val+self.BoxWidthSlider.val))
#
# print('数据2从第{}到第{}行，第{}列到第{}列'.format(self.ax2YSlider.val
# , self.ax2YSlider.val + self.BoxHeightSlider.val
# , self.ax2XSlider.val
# , self.ax2XSlider.val + self.BoxWidthSlider.val))
self.subData1=self.data1[self.ax1YSlider.val:self.ax1YSlider.val+self.BoxHeightSlider.val
,self.ax1XSlider.val:self.ax1XSlider.val+self.BoxWidthSlider.val]
self.subData2=self.data2[self.ax2YSlider.val:self.ax2YSlider.val + self.BoxHeightSlider.val
,self.ax2XSlider.val:self.ax2XSlider.val + self.BoxWidthSlider.val]
def buttonClick(self,click):
crossCorrelation(self.subData1,self.subData2,outFileName="corss.pkl")
with open('corss.pkl', 'rb') as file1:
data1 = pickle.load(file1)
data1 = sorted(data1, key=lambda x: x[-1], reverse=True)
print(data1[0])
if __name__=='__main__':
FitsGUI()
标签：10,val,self,shape,base,Fits,ax,交互,图片 来源： https://blog.csdn.net/weixin_51772689/article/details/121444487