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)