def dispim(imname='',subplot=111,chan=0, vmin=0.0, vmax=1.0):
print 'Opening', imname
ia.open(imname)
pix = ia.getchunk()
ia.close()
vmin=0.0
vmax=1.0
if imname.count('mosaic')==0:
arr = pix[:,:,0,chan]
else:
arr = pix[350:1150, 350:1150, 0, chan]
if imname.count('sdonly')>0:
vmax=5.0
if imname.count('alpha')==0:
pl.imshow(pl.rot90( np.sign(arr)*np.sqrt(np.fabs(arr)) ), interpolation=None,cmap='jet',vmin=vmin, vmax=vmax)
else:
pl.imshow(pl.rot90( arr ), interpolation=None,cmap='jet',vmin=-3.0, vmax=1.0)
# pl.imshow(pl.rot90(pix[:,:,chan,0]), interpolation=None,cmap='jet')
pl.colorbar()
def triangleImage(link, nom, s):
a = seuil(imageio.imread(link), s)
a = py.rot90(a, 3)
xBis, yBis = transforme(a.tolist())
xBis, yBis = np.array(xBis), np.array(yBis)
cens, edg, tri, neig = triang.delaunay(xBis, yBis)
taille = len(a.tolist())
l = taille / 15
b = 0
py.figure()
for t in tri:
# t[0], t[1], t[2] are the points indexes of the triangle
d1, d2, d3 = d(xBis[t[0]], yBis[t[0]], xBis[t[1]],
yBis[t[1]]), d(xBis[t[1]], yBis[t[1]], xBis[t[2]],
yBis[t[2]]), d(xBis[t[2]], yBis[t[2]],
xBis[t[0]], yBis[t[0]])
if (d1 < l and d2 < l and d3 < l):
#t_i = [t[0], t[1], t[2], t[0]]
t_i = [t[0], t[1], t[2], t[0]]
if (b):
py.fill(xBis[t_i], yBis[t_i], "black")
b = 0
else:
b = 1
py.savefig(nom)
def generate_masks(pattern,scattMaskRadius=50,scattMaskCenterX=523, scattMaskCenterY=523, background=30, slit=60):
[dimy,dimx] = pattern.shape
mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY, scattMaskRadius)
#mask[518:518+slit,:] = 0
#mask[370:480,520:650] = 0
#mask[:370,520:580] = 0
#mask[590:600,505:515] = 0
crosswidth = 10
shiftx = 10
shifty = 5
mask[512-crosswidth+shiftx:512+crosswidth+shiftx, :] = 0
mask[:, 512-crosswidth+shifty:512+crosswidth+shifty] = 0
mask[470:512, 400:512] = 0
mask = fliplr(rot90(mask,3))
H = numpy.array([map(float,line.strip('\n').split(',')) for line in filterwindow.split('\n')])
blurred = imfilter(mask,H)
newMask = 1-(blurred<0.99)
H2 = H
newMask = imfilter(newMask.astype('double'), H2)
#newMask = imfilter(newMask.astype('double'), H2)
mask *= newMask
gMask = gaussian_mask(dimx,dimx,400,700,300)
centerMask = euclid(dimx,dimx,numpy.round(dimx/2),numpy.round(dimx/2),90)
return mask, gMask, centerMask
def generate_masks(pattern,scattMaskRadius=50,scattMaskCenterX=523, scattMaskCenterY=523, background=30, slit=17):
print 'getting shape'
[dimy,dimx] = pattern.shape
print 'mask bad areas'
mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY, scattMaskRadius)
mask[518:518+slit,:] = 0
mask[370:480,520:650] = 0
mask[:370,520:580] = 0
mask[590:600,505:515] = 0
print 'doint some flipping...'
mask = fliplr(rot90(mask,3))
# H = numpy.array([map(float,line.strip('\n').split(',')) for line in open('/Users/Goldmund/Documents/MATLAB/H.txt').readlines()])
print 'generate smear object'
H = zeropad(strel(9, shape = 'disk'), mask.shape[0], mask.shape[1])
print 'broaden mask by blurring it'
blurred = numpy.abs(myconv2(mask,H))
newMask = 1-(blurred<0.99)
H2 = H
print 'blurring new mask'
newMask = numpy.abs(myconv2(newMask.astype('double'),H2))
mask *= newMask
print 'creating gaussian and center mask'
gMask = gaussian_mask(dimx,dimx,400,700,300)
centerMask = euclid(dimx,dimx,numpy.round(dimx/2),numpy.round(dimx/2),150)
return mask, gMask, centerMask
def display_APS_frames(frames, time_interval=1):
'''
display DAVIS240 frames with fixed time interval
inputs:
frames : obtained from net_raw_UDP_jAER.py
time_interval : optional parameter, time interval in between frames
'''
plt.ion()
my_obj = plt.imshow(plt.rot90(frames[1][3, :, :]))
plt.hold('on')
for i in range(len(frames)):
frames[i][3, :, :] = frames[i][2, :, :] - frames[i][1, :, :]
frames[i][6, :, :] = frames[i][5, :, :] - frames[i][4, :, :]
frames[i][3, :, :][frames[i][3, :, :] < 0] = 0
my_obj.set_data(plt.rot90(frames[i][3, :, :]))
plt.draw()
sleep(1)
def montage(I):
xdim, ydim, zdim = shape(I)
nimages_x = int(ceil(sqrt(xdim)))
nimages_y = int(ceil(sqrt(ydim)))
nimages_z = int(ceil(sqrt(zdim)))
Mx = zeros((nimages_x * zdim, nimages_x * ydim))
My = zeros((nimages_y * zdim, nimages_y * xdim))
Mz = zeros((nimages_z * ydim, nimages_z * xdim))
# Sagittal (x)
# switch i2 and i1 for loops to have the slice sequence
# progress vertically rather than horizontally.
xcount = 0
for i1 in range(nimages_x):
for i2 in range(nimages_x):
xcount += 1
if xcount < xdim:
Mx[ i1*zdim : (i1+1)*zdim, i2*ydim : (i2+1)*ydim ] = rot90(I[xdim-xcount,::-1,:],1)
else:
break
# Coronal (y)
ycount = 0
for i1 in range(nimages_y):
for i2 in range(nimages_y):
ycount += 1
if ycount < ydim:
My[ i1*zdim : (i1+1)*zdim, i2*xdim : (i2+1)*xdim ] = flipud(I[::-1,ydim-ycount,:].transpose())
else:
break
# Horizontal (z)
zcount = 0
for i1 in range(nimages_z):
for i2 in range(nimages_z):
zcount += 1
if zcount < zdim:
Mz[ i1*ydim : (i1+1)*ydim, i2*xdim : (i2+1)*xdim ] = flipud(I[:,:,zdim-zcount].transpose())
else:
break
return Mx, My, Mz, xdim, ydim, zdim, nimages_x, nimages_y, nimages_z
def generate_masks(pattern,
scattMaskRadius=50,
scattMaskCenterX=523,
scattMaskCenterY=523,
background=30,
slit=60):
[dimy, dimx] = pattern.shape
mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY,
scattMaskRadius)
#mask[518:518+slit,:] = 0
#mask[370:480,520:650] = 0
#mask[:370,520:580] = 0
#mask[590:600,505:515] = 0
crosswidth = 10
shiftx = 10
shifty = 5
mask[512 - crosswidth + shiftx:512 + crosswidth + shiftx, :] = 0
mask[:, 512 - crosswidth + shifty:512 + crosswidth + shifty] = 0
mask[470:512, 400:512] = 0
mask = fliplr(rot90(mask, 3))
H = numpy.array([
map(float,
line.strip('\n').split(',')) for line in filterwindow.split('\n')
])
blurred = imfilter(mask, H)
newMask = 1 - (blurred < 0.99)
H2 = H
newMask = imfilter(newMask.astype('double'), H2)
#newMask = imfilter(newMask.astype('double'), H2)
mask *= newMask
gMask = gaussian_mask(dimx, dimx, 400, 700, 300)
centerMask = euclid(dimx, dimx, numpy.round(dimx / 2),
numpy.round(dimx / 2), 90)
return mask, gMask, centerMask
Mz3 = zeros((shape(Mz)[0], shape(Mz)[1], 3))
Mxyz = [Mx,My,Mz]
Mxyz3 = [Mx3,My3,Mz3]
dims1 = [shape(Mx)[0],shape(My)[0],shape(Mz)[0]]
dims2 = [shape(Mx)[1],shape(My)[1],shape(Mz)[1]]
for iaxis in range(3):
M = Mxyz[iaxis]
M3 = Mxyz3[iaxis]
for i1 in range(dims1[iaxis]):
for i2 in range(dims2[iaxis]):
if str(int(M[i1,i2])) in labelnumbers:
ilabel = labelnumbers.index(str(int(M[i1,i2])))
if labelnames[ilabel] not in exclude_list:
labelcolor = labelcolors[ilabel].split(" ")
rgb = (int(labelcolor[0]),int(labelcolor[1]),int(labelcolor[2]))
M3[i1,i2,:] = rgb
if iaxis == 0: Mx = M3
elif iaxis == 1: My = M3
elif iaxis == 2: Mz = M3
"""
Save images
(Alternatives:)
pylab.imsave with: cmap=cm.gist_gray for grayscale or vmax=255 for color
scipy.misc.toimage (http://www.scipy.org/Cookbook/Matplotlib/LoadImage)
"""
#plt.gray()
imsave(out_path + '_x' + '.png', Mx)
imsave(out_path + '_y' + '.png', My)
imsave(out_path + '_z' + '.png', rot90(Mz,2))
def win(board, letter):
wins = logical_or(board == letter, board == 'T')
return any(all(wins, 0)) or any(all(wins, 1)) or all(diag(wins)) or \
all(diag(rot90(wins)))
estart = 0.0
deltae = 4.0
sqe = numpy.zeros((10,10), dtype='float')
for iq in range(10):
for ie in range(10):
qtransfer = qstart + iq * deltaq
etransfer = estart + ie * deltae
sqe[iq,ie] = sqecalc.calcSqeCohCreateAllmodes(qtransfer, etransfer)
print iq, ie, sqe[iq,ie]
pickle.dump(sqe, open('sqe.pkl', 'w'))
pylab.imshow(pylab.rot90(sqe))
pylab.show()
end = raw_input()
#########
#mp40 grid
mp40=uc.getMonkhorstPackGrid((40,40,40))
sqecalc._kpts= mp40
sqecalc._numkpts = 64000
sqecalc.readIDFeigenvectors(filename='pols_FeAl222_mp40.idf')
sqecalc.readEigenvaluesFromIDFomega2(filename='omega2_FeAl222_mp40.idf')
