PyQt matplotlib在圖片頂部繪製輪廓數據 - 縮放問題

Question

我想把一張照片作爲背景放在matplotlib中。我設法添加照片，其大小爲273 x 272像素。然後我添加一個30×30大小的等值線圖。如果我註釋繪製照片的線條，等高線圖將覆蓋整個繪圖區域。

如果我包含照片，等高線圖出現在左下角。它看起來非常像是繪製在沿着每個軸的整個畫布的約30/272的分數上。我想要的是讓等高線圖覆蓋整張照片。

這些代碼（不是一個完整的工作示例）的相關部分：

# Matplotlib Figure object 
from matplotlib.figure import Figure 

# import the Qt4Agg FigureCanvas object, that binds Figure to 
# Qt4Agg backend. It also inherits from QWidget 
from matplotlib.backends.backend_qt4agg \ 
import FigureCanvasQTAgg as FigureCanvas 

from PIL import Image 

..... 

class Qt4ContourCanvas(FigureCanvas): 
    def __init__(self, Z_matrix, plot_freq, p2_freq, p2_power, ws_level, p2_patch_on, pmin, pmax, my_alpha, parent=None): 

     global p2_frequency 
     logger.debug("%s - created" % self.__class__.__name__) 
     self.fig = Figure(facecolor='Lavender') 
     self.axes = self.fig.add_subplot(111) 

     #Reduce the size of the borders 
     #http://stackoverflow.com/questions/1203639/how-do-i-limit-the-border-size-on-a-matplotlib-graph 
     self.fig.subplots_adjust(left=0.05, bottom=0.05, right=0.95, top=1-0.05, 
       wspace=0.01, hspace=0.01) 

     # We need to keep a class variable of Z to prevent it going out of scope 
     self.Z = Z_matrix 

............ 

    def drawContourPlot(self, Z_matrix, plot_freq, p2_freq, p2_power, ws_level, p2_patch_on, pmin, pmax, my_alpha): 
     "Method to plot contour plots" 
     global p2_frequency 
     p2_frequency = p2_freq 
     self.axes.cla() 

     self.Z = Z_matrix 


     map_dimensions = Z_matrix.shape 
     my_xdim = map_dimensions[0] 
     my_ydim = map_dimensions[1] 

     levels = np.arange(pmin, pmax, 2.5) 

     DIM = len(self.Z) 
     x = y = np.arange(0, DIM, 1) 
     X, Y = np.meshgrid(x, y) 

     my_cm = ListedColormap(faramir_cm) 

     # Background picture 
     picture = Image.open('gondor.png') 
     CSbkgr = self.axes.imshow(picture, origin='lower') 


     # Swap X and Y to transpose the data, otherwise the click event 
     # and the matrix coordinates do not agree 
     CS = self.axes.contourf(Y, X, self.Z, levels, cmap=my_cm, alpha=my_alpha) 

     CS2 = self.axes.contour(CS, levels=CS.levels, colors = 'r', hold='on') 
     self.axes.clabel(CS2, fontsize=10, inline=1, fmt='%1.1f') 

     CS3 = self.axes.contour(CS, levels=[ws_level], colors = 'black', hold='on', linestyles = 'solid', linewidths = 2) 

     self.axes.clabel(CS3, fontsize=12, inline=1, fmt='%1.1f') 

     self.axes.grid(True, color='white') 

     self.fig.canvas.draw() 

Answer 1

你可以重新調整你的等高線圖，以使其適應正確： 而不是（在左下角彩色圓點角落是未縮放的輪廓圖...）： 代碼：

import Image 
import numpy as np 
import matplotlib.mlab as mlab 
import matplotlib.pyplot as plt 

#contour plot test data: 
delta = 0.025 
x = np.arange(-3.0, 3.0, delta) 
y = np.arange(-2.0, 2.0, delta) 
X, Y = np.meshgrid(x, y) 
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0) 
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1) 
# difference of Gaussians 
Z = 10.0 * (Z2 - Z1) 

plt.figure() 
im = Image.open('tree_small.png') 
plt.imshow(im, origin='lower') 

#rescale contour plot: 
X = X - np.min(X) 
X = X * im.size[0]/np.max(X) 
Y = Y - np.min(Y) 
Y = Y * im.size[1]/np.max(Y) 
plt.contour(X, Y, Z, 20) 

plt.show() 

也許你可以疊加CON使用單獨的座標軸進行遊覽，但這似乎是最快捷的方式;）