Question

有没有人知道使用Python从MATLAB图文件中提取数据的任何方法？我知道这些是二进制文件，但Python Cookbook for .mat文件http://www.scipy.org/Cookbook/Reading_mat_files中的方法似乎不适用于.fig文件......

提前感谢您的帮助，丹

Answer 1

.fig文件是.mat文件（包含结构），请参阅 http://undocumentedmatlab.com/blog/fig-files-format/

作为您给出的引用状态，结构仅支持v7.1： http://www.scipy.org/Cookbook/Reading_mat_files

所以，在MATLAB中我使用-v7保存：

plot([1 2],[3 4])
hgsave(gcf,'c','-v7');

然后在Python 2.6.4中我使用：

>>> from scipy.io import loadmat
>>> x = loadmat('c.fig')
>>> x
{'hgS_070000': array([[<scipy.io.matlab.mio5.mat_struct object at 0x1500e70>]], dtype=object), '__version__': '1.0', '__header__': 'MATLAB 5.0 MAT-file, Platform: MACI64, Created on: Fri Nov 18 12:02:31 2011', '__globals__': []}
>>> x['hgS_070000'][0,0].__dict__
{'handle': array([[1]], dtype=uint8), 'children': array([[<scipy.io.matlab.mio5.mat_struct object at 0x1516030>]], dtype=object), '_fieldnames': ['type', 'handle', 'properties', 'children', 'special'], 'type': array([u'figure'], dtype='<U6'), 'properties': array([[<scipy.io.matlab.mio5.mat_struct object at 0x1500fb0>]], dtype=object), 'special': array([], shape=(1, 0), dtype=float64)}

我使用.__dict__来查看如何遍历结构。例如。得到XData和YData我可以使用：

>>> x['hgS_070000'][0,0].children[0,0].children[0,0].properties[0,0].XData
array([[1, 2]], dtype=uint8)
>>> x['hgS_070000'][0,0].children[0,0].children[0,0].properties[0,0].YData
array([[3, 4]], dtype=uint8)

显示我在MATLAB中使用了plot([1 2],[3 4])（孩子是轴，孙子是lineseries）。

Answer 2

我发现Alex的答案非常吸引人，但我扩展了他的代码。首先，我在序言中加入了数字，ylabel等的来源。第二，我加入了传奇！我对Python很陌生，所以对任何改进建议都非常欢迎。

def plotFig(filename,fignr=1):
   from scipy.io import loadmat
   from numpy import size
   from matplotlib.pyplot import plot,figure,hold,xlabel,ylabel,show,clf,xlim,legend
   d = loadmat(filename,squeeze_me=True, struct_as_record=False)
   ax1 = d['hgS_070000'].children
   if size(ax1) > 1:
       legs= ax1[1]
       ax1 = ax1[0]
   else:
        legs=0
   figure(fignr)
   clf()
   hold(True)
   counter = 0    
   for line in ax1.children:
       if line.type == 'graph2d.lineseries':
           if hasattr(line.properties,'Marker'):
               mark = "%s" % line.properties.Marker
               mark = mark[0]
           else:
               mark = '.'
           if hasattr(line.properties,'LineStyle'):
               linestyle = "%s" % line.properties.LineStyle
           else:
               linestyle = '-'
           if hasattr(line.properties,'Color'):
               r,g,b =  line.properties.Color
           else:
               r = 0
               g = 0
               b = 1
           if hasattr(line.properties,'MarkerSize'):
               marker_size = line.properties.MarkerSize
           else:
               marker_size = 1                
           x = line.properties.XData
           y = line.properties.YData
           plot(x,y,marker=mark,linestyle=linestyle,\
           color(r,g,b),markersize=marker_size)
       elif line.type == 'text':
           if counter < 1:
               xlabel("%s" % line.properties.String,fontsize =16)
               counter += 1
           elif counter < 2:
               ylabel("%s" % line.properties.String,fontsize = 16)
               counter += 1        
   xlim(ax1.properties.XLim)
   if legs:        
       leg_entries = tuple(legs.properties.String)
       py_locs = ['upper center','lower center','right','left','upper right','upper left','lower right','lower left','best']
       MAT_locs=['North','South','East','West','NorthEast', 'NorthWest', 'SouthEast', 'SouthWest','Best']
       Mat2py = dict(zip(MAT_locs,py_locs))
       location = legs.properties.Location
       legend(leg_entries,loc=Mat2py[location])
    hold(False)
    show()

Answer 3

这是我在Sascha的帖子中的更新。现在它可以：

显示旋转，tex标签
显示xticks和yticks
更好地处理标记
网格开/关
更好的轴和图例枚举处理
维持数字大小

代码如下：

from scipy.io import loadmat
import numpy as np
import matplotlib.pyplot as plt

def plotFig(filename,fignr=1):
   d = loadmat(filename,squeeze_me=True, struct_as_record=False)
   matfig = d['hgS_070000']
   childs = matfig.children
   ax1 = [c for c in childs if c.type == 'axes']
   if(len(ax1) > 0):
       ax1 = ax1[0]
   legs = [c for c in childs if c.type == 'scribe.legend']
   if(len(legs) > 0):
       legs = legs[0]
   else:
       legs=0
   pos = matfig.properties.Position
   size = np.array([pos[2]-pos[0],pos[3]-pos[1]])/96
   plt.figure(fignr,figsize=size)
   plt.clf()
   plt.hold(True)
   counter = 0    
   for line in ax1.children:
       if line.type == 'graph2d.lineseries':
           if hasattr(line.properties,'Marker'):
               mark = "%s" % line.properties.Marker
               if(mark != "none"):
                   mark = mark[0]
           else:
               mark = '.'
           if hasattr(line.properties,'LineStyle'):
               linestyle = "%s" % line.properties.LineStyle
           else:
               linestyle = '-'
           if hasattr(line.properties,'Color'):
               r,g,b =  line.properties.Color
           else:
               r = 0
               g = 0
               b = 1
           if hasattr(line.properties,'MarkerSize'):
               marker_size = line.properties.MarkerSize
           else:
               marker_size = -1                
           x = line.properties.XData
           y = line.properties.YData
           if(mark == "none"):
               plt.plot(x,y,linestyle=linestyle,color=[r,g,b])
           elif(marker_size==-1):
               plt.plot(x,y,marker=mark,linestyle=linestyle,color=[r,g,b])
           else:
               plt.plot(x,y,marker=mark,linestyle=linestyle,color=[r,g,b],ms=marker_size)
       elif line.type == 'text':
           if counter == 0:
               plt.xlabel("$%s$" % line.properties.String,fontsize =16)
           elif counter == 1:
               plt.ylabel("$%s$" % line.properties.String,fontsize = 16)
           elif counter == 3:
               plt.title("$%s$" % line.properties.String,fontsize = 16)
           counter += 1        
   plt.grid(ax1.properties.XGrid)

   if(hasattr(ax1.properties,'XTick')):
       if(hasattr(ax1.properties,'XTickLabelRotation')):
           plt.xticks(ax1.properties.XTick,ax1.properties.XTickLabel,rotation=ax1.properties.XTickLabelRotation)
       else:
           plt.xticks(ax1.properties.XTick,ax1.properties.XTickLabel)
   if(hasattr(ax1.properties,'YTick')):
       if(hasattr(ax1.properties,'YTickLabelRotation')):
           plt.yticks(ax1.properties.YTick,ax1.properties.YTickLabel,rotation=ax1.properties.YTickLabelRotation)
       else:
           plt.yticks(ax1.properties.YTick,ax1.properties.YTickLabel)
   plt.xlim(ax1.properties.XLim)
   plt.ylim(ax1.properties.YLim)
   if legs:        
       leg_entries = tuple(['$' + l + '$' for l in legs.properties.String])
       py_locs = ['upper center','lower center','right','left','upper right','upper left','lower right','lower left','best','best']
       MAT_locs=['North','South','East','West','NorthEast', 'NorthWest', 'SouthEast', 'SouthWest','Best','none']
       Mat2py = dict(zip(MAT_locs,py_locs))
       location = legs.properties.Location
       plt.legend(leg_entries,loc=Mat2py[location])
   plt.hold(False)
   plt.show()

Answer 4

保存MATLAB图形时，它会将Handle Graphics层次结构转储到结构中，将其保存到.mat文件，并将扩展名更改为.fig。所以.fig文件只是.mat文件，如果你要查找的数据存储在原始图中的某个位置，它就会在那里。如果您手动将扩展名更改回.mat，您可以将其加载到MATLAB中并查看。

我担心我不太了解从Python读取.mat文件，但是如果你有办法一般这样做，你也应该能够读取.fig文件。

Answer 5

这是更简单的方法。它基于较新的Scipy和loadmat：

http://answerpot.com/showthread.php?3707193-loadmat+and+figure

我对简单2D线的小扩展是：

from scipy.io import loadmat



d = loadmat('../impulse_all.fig',squeeze_me=True, struct_as_record=False)
# d = loadmat('R11_resuspension.fig',squeeze_me=True, struct_as_record=False)
ax1 = d['hgS_070000'].children
if size(ax1) > 1:
    ax1 = ax1[0]

figure
hold(True)
counter = 0
for line in ax1.children:
    if line.type == 'graph2d.lineseries':
        marker = "%s" % line.properties.Marker
        linestyle = "%s" % line.properties.LineStyle
        r,g,b =  line.properties.Color
        marker_size = line.properties.MarkerSize
        x = line.properties.XData
        y = line.properties.YData
        plot(x,y,marker,linestyle=linestyle,color = (r,g,b),markersize=marker_size)
    elif line.type == 'text':
        if counter < 1:
            xlabel("%s" % line.properties.String,fontsize =16)
            counter += 1
        elif counter < 2:
            ylabel("%s" % line.properties.String,fontsize = 16)
            counter += 1



hold(False)

Answer 6

使用Sascha的帖子，我只想提取存储在.fig文件中的x数据和y数据。

下面是我的python函数，它是Sascha函数的简化，旨在仅提取数据。输出是字典。其键是图中数据的相应标签。

我把它放在那里。很高兴，如果这可以节省几分钟给别人！

card.Item1

使用Python从MATLAB .fig文件中获取数据？

6 个答案: