def plot_bandstructure(fname,
rotate=True,
cmap='jet',
logscale=False,
ax=None,
E2=False):
"""
make a nice pcolormesh plot of the bandstructure
usage:
plot_bandstructure( fname )
where fname is a txt file exported manually using a lumerical script. See
'load_bandstructure' for proper formatting of this txt file.
"""
d1, d2, fields = load_bandstructure(fname)
D1 = kc.centers_to_corners(d1)
D2 = kc.centers_to_corners(d2)
if ax == None: ax = plt.gca()
if logscale: fields = np.log(fields)
if rotate == True:
""" Note: the /1e12 converts Hz to THz """
plot = ax.pcolormesh(D1, D2 / 1e12, np.transpose(fields), cmap=cmap)
ax.axis([D1.min(), D1.max(), D2.min() / 1e12, D2.max() / 1e12])
else:
plot = ax.pcolormesh(D2, D1, fields, cmap=cmap)
ax.axis([D2.min(), D2.max(), D1.min(), D1.max()])
#show()
return plot, D1, D2, fields
def plot_bandstructure( fname, rotate=True, cmap='jet', logscale=False, ax=None, E2=False ):
"""
make a nice pcolormesh plot of the bandstructure
usage:
plot_bandstructure( fname )
where fname is a txt file exported manually using a lumerical script. See
'load_bandstructure' for proper formatting of this txt file.
"""
d1, d2, fields = load_bandstructure( fname )
D1 = kc.centers_to_corners( d1 )
D2 = kc.centers_to_corners( d2 )
if ax==None: ax=plt.gca()
if logscale: fields = np.log(fields)
if rotate==True:
""" Note: the /1e12 converts Hz to THz """
plot = ax.pcolormesh( D1, D2/1e12, np.transpose( fields ), cmap=cmap )
ax.axis([ D1.min(), D1.max(), D2.min()/1e12, D2.max()/1e12 ])
else:
plot = ax.pcolormesh( D2, D1, fields, cmap=cmap )
ax.axis([ D2.min(), D2.max(), D1.min(), D1.max() ])
#show()
return plot, D1, D2, fields
def plotcolormap(self):
files = glob.glob( self.DataPath + "\\" + self.FnameBase + '_*.SPE' ) # get a list of all non-glued txt files
# assume filename is of the format: timeseriesvacuum_2640.SPE
# where 2640 is the time in seconds since the start of the series of scans
try:
files.sort( key=lambda x: int(os.path.split(x)[1].split('.SPE')[0].split('_')[1]) ) # sort by acquisition start time
except ValueError:
# there was a file in there with the same filename base but that wasn't part of the series
# (e.g. "timeseriesvacuum_after blocking laser 10mn.SPE")
for fname in files:
if not os.path.split(fname)[1].split('.SPE')[0].split('_')[1].isdigit():
files.remove( fname )
files.sort( key=lambda x: int(os.path.split(x)[1].split('.SPE')[0].split('_')[1]) ) # sort by acquisition start time
if len(files) == 0:
print "no SPE files found."
return False
if files == self.SPEFiles:
# print "same list as last time."
pass
else:
# presumably we could save some effort and not load the whole list every time,
# but this program is meant to be used while taking spectra every 30sec or so,
# which would give us plenty of time to refresh the plot each time.
# but the plotting itself is probably the most expensive part, so this is moot...
self.SPEFiles = files
self.spectra = []
self.time = []
for fname in files:
self.time.append( float( os.path.split(fname)[1].split('.SPE')[0].split('_')[-1] ) )
s = spe.Spectrum( fname )
s.remove_linear_background( npoints=10 )
s.normalize()
self.spectra.append( s.lum )
self.wavelen = s.wavelen
wavelen_image = kc.centers_to_corners( self.wavelen )
time_image = kc.centers_to_corners( self.time )/60.0
spectra_image = pylab.array( self.spectra )
self.axes.pcolormesh( time_image, wavelen_image, spectra_image.transpose(), cmap='copper' )
self.axes.set_ylim( wavelen_image[0], wavelen_image[-1] )
self.axes.set_xlim( time_image[0], time_image[-1] )
self.axes.set_ylabel( 'Wavelength (nm)' )
self.axes.set_xlabel( 'Time (min)' )
self.axes.set_title( self.FnameBase )
return True
def plot2Dmonitor( fname, rotate=False, offset=[0,0], cmap='Purples', ax=None, E2=False ):
"""
make a nice pcolormesh plot that has same units in both axes
usage: plot2Dmonitor( fname ) where fname is a txt file exported manually from CAD.
"""
d1, d2, fields = load2D( fname )
if E2: fields = np.sqrt(fields) # you exported E-squared (E intensity) but you want abs(E).
D1 = kc.centers_to_corners( d1 )
D2 = kc.centers_to_corners( d2 )
if ax==None: ax=plt.gca()
if rotate==True:
plot = ax.pcolormesh( D1+offset[0], D2+offset[1], transpose( fields ), cmap=cmap )
ax.axis([ D1.min()+offset[0], D1.max()+offset[0], D2.min()+offset[1], D2.max()+offset[1] ])
else:
plot = ax.pcolormesh( D2+offset[0], D1+offset[1], fields, cmap=cmap )
ax.axis([ D2.min()+offset[0], D2.max()+offset[0], D1.min()+offset[1], D1.max()+offset[1] ])
ax.set_aspect('equal')
#show()
return plot, D1, D2, fields
def plot2Dmonitor(fname, **kwargs):
"""
make a nice pcolormesh plot that has same units in both axes
usage: plot2Dmonitor( fname ) where fname is a txt file exported manually from CAD.
Various keyword arguments are supported (in addition to any :
rotate: True/False for whether colormap should be rotated 90deg
offset: [x,y] tuple specifying lateral shift of origin for plotting
ax: axes instance for plotting. If not specified, gca() is used.
take_sqrt: True/False. If True, take np.sqrt() before plotting (formerly E2)
logscale: True/False. If True, take np.log10() before plotting
flipvert: True/False. If True, multiply the locations of the vertical axis by -1 to flip it.
"""
d1, d2, fields = load2D(fname)
D1 = kc.centers_to_corners(d1)
D2 = kc.centers_to_corners(d2)
if 'E2' in kwargs.keys():
raise ValueError, "E2 is deprecated and was replaced with take_sqrt (which acts equivalently)."
if 'rotate' in kwargs.keys():
rotate = kwargs['rotate']
del kwargs['rotate']
else:
rotate = False
if 'offset' in kwargs.keys():
offset = kwargs['offset']
del kwargs['offset']
else:
offset = [0, 0]
if 'ax' in kwargs.keys():
ax = kwargs['ax']
del kwargs['ax']
else:
ax = plt.gca()
if 'flipvert' in kwargs.keys():
flipvert = kwargs['flipvert']
del kwargs['flipvert']
else:
flipvert = False
if 'take_sqrt' in kwargs.keys():
if kwargs['take_sqrt']:
fields = np.sqrt(
fields
) # you exported E-squared (E intensity) but you want abs(E).
del kwargs['take_sqrt']
if 'logscale' in kwargs.keys():
if kwargs['logscale']:
fields = np.log10(fields)
del kwargs['logscale']
if rotate == True:
if flipvert: D2 *= -1
plot = ax.pcolormesh(D1 + offset[0], D2 + offset[1],
np.transpose(fields), **kwargs)
ax.axis([
D1.min() + offset[0],
D1.max() + offset[0],
D2.min() + offset[1],
D2.max() + offset[1]
])
else:
if flipvert: D1 *= -1
plot = ax.pcolormesh(D2 + offset[0], D1 + offset[1], fields, **kwargs)
ax.axis([
D2.min() + offset[0],
D2.max() + offset[0],
D1.min() + offset[1],
D1.max() + offset[1]
])
ax.set_aspect('equal')
#show()
return plot, D1, D2, fields
def colormap(self):
""" plot a colormap of the full raster scan
"""
x = kc.centers_to_corners(self.xpoints)
y = kc.centers_to_corners(self.ypoints)
def plot2Dmonitor( fname, **kwargs ):
"""
make a nice pcolormesh plot that has same units in both axes
usage: plot2Dmonitor( fname ) where fname is a txt file exported manually from CAD.
Various keyword arguments are supported (in addition to any :
rotate: True/False for whether colormap should be rotated 90deg
offset: [x,y] tuple specifying lateral shift of origin for plotting
ax: axes instance for plotting. If not specified, gca() is used.
take_sqrt: True/False. If True, take np.sqrt() before plotting (formerly E2)
logscale: True/False. If True, take np.log10() before plotting
flipvert: True/False. If True, multiply the locations of the vertical axis by -1 to flip it.
"""
d1, d2, fields = load2D( fname )
D1 = kc.centers_to_corners( d1 )
D2 = kc.centers_to_corners( d2 )
if 'E2' in kwargs.keys():
raise ValueError, "E2 is deprecated and was replaced with take_sqrt (which acts equivalently)."
if 'rotate' in kwargs.keys():
rotate = kwargs['rotate']
del kwargs['rotate']
else:
rotate = False
if 'offset' in kwargs.keys():
offset = kwargs['offset']
del kwargs['offset']
else:
offset = [0,0]
if 'ax' in kwargs.keys():
ax = kwargs['ax']
del kwargs['ax']
else:
ax=plt.gca()
if 'flipvert' in kwargs.keys():
flipvert = kwargs['flipvert']
del kwargs['flipvert']
else:
flipvert=False
if 'take_sqrt' in kwargs.keys():
if kwargs['take_sqrt']:
fields = np.sqrt(fields) # you exported E-squared (E intensity) but you want abs(E).
del kwargs['take_sqrt']
if 'logscale' in kwargs.keys():
if kwargs['logscale']:
fields = np.log10(fields)
del kwargs['logscale']
if rotate==True:
if flipvert: D2 *= -1
plot = ax.pcolormesh( D1+offset[0], D2+offset[1], np.transpose( fields ), **kwargs )
ax.axis([ D1.min()+offset[0], D1.max()+offset[0], D2.min()+offset[1], D2.max()+offset[1] ])
else:
if flipvert: D1 *= -1
plot = ax.pcolormesh( D2+offset[0], D1+offset[1], fields, **kwargs )
ax.axis([ D2.min()+offset[0], D2.max()+offset[0], D1.min()+offset[1], D1.max()+offset[1] ])
ax.set_aspect('equal')
#show()
return plot, D1, D2, fields
def colormap( self ):
""" plot a colormap of the full raster scan
"""
x = kc.centers_to_corners( self.xpoints )
y = kc.centers_to_corners( self.ypoints )
