Does anyone know of any methods of extracting the data from a MATLAB fig file using Python? I know these are binary files but the methods in the Python Cookbook for .mat files http://www.scipy.org/Cookbook/Reading_mat_files don't seem to work for .fig files...
Thanks in advance for any help, Dan
.fig files are .mat files (containing a struct), see http://undocumentedmatlab.com/blog/fig-files-format/
As the reference you give states, structs are only supported up to v7.1: http://www.scipy.org/Cookbook/Reading_mat_files
So, in MATLAB I save using -v7:
plot([1 2],[3 4])
hgsave(gcf,'c','-v7');
Then in Python 2.6.4 I use:
>>> 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)}
Where I used .__dict__ to see how to traverse the structure. E.g. to get XData and YData I can use:
>>> 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)
Showing that I'd used plot([1 2],[3 4]) in MATLAB (the child is the axis and the grandchild is the lineseries).
Here is my update from Sascha's post. Now it can:
The code is below:
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()
updated for python >3.x, (see comments from @robert-pollak):
from scipy.io import loadmat
import numpy as np
import matplotlib.pyplot as plt
def plotFig(filename,fignr=1, subfig=1):
d = loadmat(filename,squeeze_me=True, struct_as_record=False)
matfig = d['hgS_070000']
childs = matfig.children
sfig = max(0, subfig - 1)
ax1 = [c for c in childs if c.type == 'axes']
if(len(ax1) > 0):
sfig = min(sfig, len(ax1) - 1)
ax1 = ax1[sfig]
legs = [c for c in childs if c.type == 'scribe.legend']
if(len(legs) > 0):
legs = legs[sfig]
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.lower()
plt.legend(leg_entries,loc=Mat2py[ location ])
#plt.hold(False)
plt.show()
I found Alex's answer very appealing, but I extended his code a bit. First of all, I included the preamble to show where the figure, ylabel, etc. comes from. Second of all, I included the legend! I'm rather new to Python, so any suggestions for improvements are highly welcomed.
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=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()
This is much easier way available. It's based on the newer Scipy and loadmat:
http://answerpot.com/showthread.php?3707193-loadmat+and+figure
And my small extension to it for the simple 2D lines is:
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)
When you save a MATLAB figure, it dumps the Handle Graphics hierarchy into a structure, saves it to a .mat file, and changes the extension to .fig. So .fig files are just .mat files, and if the data you're looking for was stored somewhere in the original figure it will be in there. If you manually change the extension back to .mat you can load it into MATLAB and take a look.
I'm afraid I don't know much about reading .mat files from Python, but if you have a way of doing that in general, you should also be able to read in a .fig file.
Using the posts of Sascha, I just wanted to extract the x-data and y-data stored in a .fig file.
Below is my python function, which is a simplification of the Sascha's function aiming at only extracting the data. Output is a dictionary. Its keys are the corresponding labels of the data in the figure.
I put it there. Glad if this could save a few minutes to someone else !
import numpy
from scipy.io import loadmat
def read_fig(filename):
output = {}
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'][0]
for line in ax1.children:
try:
if line.type == 'graph2d.lineseries':
x = line.properties.XData
y = line.properties.YData
leg = line.properties.DisplayName
print leg
output[leg] = numpy.column_stack((x, y))
except:
print 'One children is ignored...'
return output
