def check_mem_masked_where(self,level=rlevel):
"""Ticket #62"""
from numpy.core.ma import masked_where, MaskType
a = N.zeros((1,1))
b = N.zeros(a.shape, MaskType)
c = masked_where(b,a)
a-c
def plot_data(xi,yi,zi):
zim = ma.masked_where(N.isnan(zi),zi)
pylab.figure(figsize=(8,8))
# pylab.pcolor(xi,yi,zim,shading='interp',cmap=pylab.cm.gray)
pylab.pcolor(xi,yi,zim,shading='interp',cmap=pylab.cm.jet)
# pylab.contour(xi,yi,zim,cmap=pylab.cm.jet)
pylab.show()
def check_mem_masked_where(self, level=rlevel):
"""Ticket #62"""
from numpy.core.ma import masked_where, MaskType
a = N.zeros((1, 1))
b = N.zeros(a.shape, MaskType)
c = masked_where(b, a)
a - c
def plot_data(xi,yi,zi,intx,inty):
"""provide...
xi=grid x data
yi=grided y data
zi=interpolated MEG data for contour
intx and inty= sensor coords for channel plotting"""
tstart = time.time()
zim = ma.masked_where(isnan(zi),zi)
#p.pcolor(xi,yi,zim,shading='interp',cmap=p.cm.jet)
p.contourf(xi,yi,zim,cmap=p.cm.jet)
def plot_data(xi,yi,zi,intx,inty):
"""provide...
xi=grid x data
yi=grided y data
zi=interpolated MEG data for contour
intx and inty= sensor coords for channel plotting"""
zim = ma.masked_where(isnan(zi),zi)
#pcolor(xi,yi,zim,shading='interp',cmap=cm.jet)
contourf(xi,yi,zim,cmap=cm.jet)
#scatter(intx,inty, alpha=.5,s=.5)
#contour(xi,yi,zim,cmap=cm.jet)
draw()
def display(data, chanlocs, labels="None", contourdata=None):
xi, yi = mgrid[-0.5:0.5:67j, -0.5:0.5:67j]
intx = chanlocs[1, :]
inty = chanlocs[0, :]
print "2d array of data"
# tri = Triangulation(intx,inty)
p.ion()
fig = p.figure()
print "suplotting quiver"
if len(data.shape) == 1:
data = array([data])
for i in range(0, size(data, 0)):
spnum = ceil(sqrt(shape(data)[0])) # get x and y dimension of subplots
fig.add_subplot(spnum, spnum, i + 1)
# axis('off')
if contourdata != None:
dataslice = contourdata[i, :]
z = dataslice
if delaunay == "yes":
print "delaunay is set"
tri = Triangulation(intx, inty)
interp = tri.nn_interpolator(z)
zi = interp(xi, yi)
else: # try griddata method
print "delaunay is off"
zi = griddata(intx, inty, z, xi, yi)
interp = tri.nn_interpolator(z)
zi = interp(xi, yi)
zim = ma.masked_where(isnan(zi), zi)
p.contourf(xi, yi, zim, cmap=p.cm.jet, alpha=0.8)
p.axis("off")
dataslice = data[i, :]
z = dataslice
sc = data.max() * 10
# return intx, inty, z#imag(z), real(z)
# print i
p.quiver(intx, inty, imag(z), real(z)) # , scale=sc)
if labels != "None":
p.title(str(labels[i]))
p.axis("off")
def display(data, chanlocs):
xi, yi = mgrid[-.5:.5:67j,-.5:.5:67j]
intx=chanlocs[1,:]
inty=chanlocs[0,:]
z = data
## tri = Triangulation(intx,inty)
## interp = tri.nn_interpolator(z)
## zi = interp(xi,yi)
if delaunay == 'yes':
tri = Triangulation(intx,inty)
interp = tri.nn_interpolator(z)
zi = interp(xi,yi)
else: #try griddata method
zi = griddata(intx,inty,z,xi,yi)
zim = ma.masked_where(isnan(zi),zi)
plot_data(xi,yi,zi,intx,inty)
def display(data, chanlocs, data2=None, subplot='on', animate='off', quiver='off', title=None, labels=None, colorbar='off'):
if len(shape(chanlocs)) != 2:
print 'Chanlocs shape error. Should be 2D array "(2,N)"'
print 'transposing'
chanlocs = chanlocs.T
#xi, yi = mgrid[-.5:.5:67j,-.5:.5:67j]
xi, yi = mgrid[chanlocs[1,:].min():chanlocs[1,:].max():57j,chanlocs[0,:].min():chanlocs[0,:].max():57j]
intx=chanlocs[1,:]
inty=chanlocs[0,:]
if shape(shape(data))[0]==2: #more than a single vector, need to animate or subplot
print '2d array of data'
z = data[0,:]
if delaunay == 'yes':
print 'delaunay is set'
tri = Triangulation(intx,inty)
interp = tri.nn_interpolator(z)
zi = interp(xi,yi)
else: #try griddata method
print 'delaunay is off'
zi = griddata(intx,inty,z,xi,yi)
#p.ion()
fig = p.figure()
if animate == 'on': #single plot with a loop to animate
p.scatter(intx,inty, alpha=.5,s=.5)
print 'animating'
for i in range(0, shape(data)[0]):
dataslice=data[i,:];
z = dataslice
if delaunay == 'yes':
interp = tri.nn_interpolator(z)
zi = interp(xi,yi)
else:
zi = griddata(intx,inty,z,xi,yi)
zim = ma.masked_where(isnan(zi),zi)
p.contourf(xi,yi,zim,cmap=p.cm.jet, alpha=.8)
if labels != None:
printlabels(chanlocs, labels)
p.draw()
#del(z,interp,zi,zim)
if subplot == 'on':
print 'suplotting'
for i in range(0, shape(data)[0]):
spnum = ceil(sqrt(shape(data)[0])) #get x and y dimension of subplots
fig.add_subplot(spnum,spnum,i+1);#axis('off')
dataslice=data[i,:];
p.scatter(intx,inty, alpha=.75,s=3)
z = dataslice
if delaunay == 'yes':
interp = tri.nn_interpolator(z)
zi = interp(xi,yi)
else:
zi = griddata(intx,inty,z,xi,yi)
zim = ma.masked_where(isnan(zi),zi)
p.contourf(xi,yi,zim,cmap=p.cm.jet, alpha=.8)
p.axis('off')
if labels != None:
printlabels(chanlocs, labels)
if title != None:
p.title(str(title[i]))
else:
p.title(str(i))
if quiver == 'on':
print 'suplotting quiver'
for i in range(0, shape(data)[0]):
spnum = ceil(sqrt(shape(data)[0])) #get x and y dimension of subplots
fig.add_subplot(spnum,spnum,i+1);#axis('off')
dataslice=data[i,:];
p.scatter(intx,inty, alpha=.75,s=3)
z = dataslice
print 'size or z', size(z)
for xx in range(0,size(z)):
quiver(intx[xx],inty[xx], z[xx], data2[xx])
p.axis('off')
if labels != None:
printlabels(chanlocs, labels)
if colorbar == 'on':
p.colorbar()
#p.ioff()
#p.colorbar()
p.show()
else:
z = data
if delaunay == 'yes':
print 'delaunay is set'
tri = Triangulation(intx,inty)
interp = tri.nn_interpolator(z)
zi = interp(xi,yi)
else:
print 'delaunay is off'
zi = griddata(intx,inty,z,xi,yi)
zim = ma.masked_where(isnan(zi),zi)
plot_data(xi,yi,zi,intx,inty)
if labels != None:
printlabels(chanlocs, labels)
if colorbar == 'on':
p.colorbar(cmap=p.cm.jet)