def greyscale(self, array2d, **kwargs):
"""
greyscale(array2d, **kwargs):
Plot a 2D array as a greyscale image using the same scalings
as in prepfold.
"""
# Use the same scaling as in prepfold_plot.c
global_max = Num.maximum.reduce(Num.maximum.reduce(array2d))
min_parts = Num.minimum.reduce(array2d, 1)
array2d = (array2d-min_parts[:,Num.newaxis])/Num.fabs(global_max)
Pgplot.plot2d(array2d, image='antigrey', **kwargs)
def greyscale(self, array2d, **kwargs):
"""
greyscale(array2d, **kwargs):
Plot a 2D array as a greyscale image using the same scalings
as in prepfold.
"""
# Use the same scaling as in prepfold_plot.c
global_max = Num.maximum.reduce(Num.maximum.reduce(array2d))
min_parts = Num.minimum.reduce(array2d, 1)
array2d = (array2d-min_parts[:,Num.newaxis])/global_max
Pgplot.plot2d(array2d, image='antigrey', **kwargs)
def show_ffdot_plane(data,
r,
z,
dr=0.125,
dz=0.5,
numr=300,
numz=300,
T=None,
contours=None,
title=None,
image="astro",
device="/XWIN",
norm=1.0):
"""
show_ffdot_plane(data, r, z):
Show a color plot of the F-Fdot plane centered on the point 'r', 'z'.
"""
ffdp = ffdot_plane(data, r, dr, numr, z, dz, numz)
ffdpow = spectralpower(ffdp.ravel())
ffdpow.shape = (numz, numr)
startbin = int(r - (numr * dr) / 2)
startz = int(z - (numz * dz) / 2)
x = Num.arange(numr, dtype="d") * dr + startbin
y = Num.arange(numz, dtype="d") * dz + startz
highpt = Num.argmax(ffdpow.ravel())
hir = highpt % numr
hiz = highpt / numr
print ""
print "Fourier Freqs from ", min(x), "to", max(x), "."
print "Fourier Fdots from ", min(y), "to", max(y), "."
print "Maximum normalized power is ", ffdpow[hiz][hir]
print "The max value is located at: r =", startbin + hir * dr, \
" z =", startz + hiz * dz
print ""
if not T:
Pgplot.plot2d(ffdpow, x, y, labx = "Fourier Frequency (bins)", \
laby = "Fourier Frequency Derivative", \
title = title, image = image, \
contours = contours, device = device)
else:
Pgplot.plot2d(ffdpow, x/T, y/(T**2.0), labx = "Frequency (hz)", \
laby = "Frequency Derivative (Hz/sec)", \
rangex2 = [x[0], x[-1]], rangey2 = [y[0], y[-1]], \
labx2 = "Fourier Frequency", \
laby2 = "Fourier Frequency Derivative", \
title = title, image = image, \
contours = contours, device = device)
def show_ffdot_plane(data, r, z, dr = 0.125, dz = 0.5,
numr = 300, numz = 300, T = None,
contours = None, title = None,
image = "astro", device = "/XWIN", norm = 1.0):
"""
show_ffdot_plane(data, r, z):
Show a color plot of the F-Fdot plane centered on the point 'r', 'z'.
"""
ffdp = ffdot_plane(data, r, dr, numr, z, dz, numz)
ffdpow = spectralpower(ffdp.ravel())
ffdpow.shape = (numz, numr)
startbin = int(r - (numr * dr) / 2)
startz = int(z - (numz * dz) / 2)
x = np.arange(numr, dtype="d") * dr + startbin
y = np.arange(numz, dtype="d") * dz + startz
highpt = np.argmax(ffdpow.ravel())
hir = highpt % numr
hiz = highpt / numr
print ""
print "Fourier Freqs from ", min(x), "to", max(x), "."
print "Fourier Fdots from ", min(y), "to", max(y), "."
print "Maximum normalized power is ", ffdpow[hiz][hir]
print "The max value is located at: r =", startbin + hir * dr, \
" z =", startz + hiz * dz
print ""
if not T:
Pgplot.plot2d(ffdpow, x, y, labx = "Fourier Frequency (bins)", \
laby = "Fourier Frequency Derivative", \
title = title, image = image, \
contours = contours, device = device)
else:
Pgplot.plot2d(ffdpow, x/T, y/(T**2.0), labx = "Frequency (hz)", \
laby = "Frequency Derivative (Hz/sec)", \
rangex2 = [x[0], x[-1]], rangey2 = [y[0], y[-1]], \
labx2 = "Fourier Frequency", \
laby2 = "Fourier Frequency Derivative", \
title = title, image = image, \
contours = contours, device = device)
maxarg = argmax(spectralpower(ffd.flat))
rind = maxarg % numr
zind = maxarg / numr
peakr = (rind * dr + int(tryr - (numr * dr) / 2.0))
peakz = (zind * dz + tryz - (numz * dz) / 2.0)
peakpow = ffd[zind][rind].real**2 + \
ffd[zind][rind].imag**2
if showplots:
xvals = arange(numr, typecode="d") * dr + \
int(tryr - (numr * dr) / 2.0)
yvals = arange(numz, typecode="d") * dz + \
tryz - (numz * dz) / 2.0
ffdpow = spectralpower(ffd.flat)
ffdpow.shape = (numz, numr)
Pgplot.plot2d(ffdpow, xvals, yvals, \
labx="Fourier Freq (bins)", \
laby="Fourier Freq Deriv", \
image="astro")
Pgplot.closeplot()
if debugout:
print 'peakr = %11.5f peakz = %11.5f' % \
(peakr, peakz)
if (peakpow < 0.2):
pows[ct] = peakpow
rmax = peakr
zmax = peakz
else:
[pows[ct], rmax, zmax, rd] = \
maximize_rz(data, peakr, peakz, \
norm=1.0)
if debugout:
print 'max_r = %11.5f max_z = %11.5f' % \
maxarg = argmax(spectralpower(ffd.flat))
rind = maxarg % numr
zind = maxarg / numr
peakr = (rind * dr + int(tryr - (numr * dr) / 2.0))
peakz = (zind * dz + tryz - (numz * dz) / 2.0)
peakpow = ffd[zind][rind].real**2 + \
ffd[zind][rind].imag**2
if showplots:
xvals = arange(numr, typecode="d") * dr + \
int(tryr - (numr * dr) / 2.0)
yvals = arange(numz, typecode="d") * dz + \
tryz - (numz * dz) / 2.0
ffdpow = spectralpower(ffd.flat)
ffdpow.shape = (numz, numr)
Pgplot.plot2d(ffdpow, xvals, yvals, \
labx="Fourier Freq (bins)", \
laby="Fourier Freq Deriv", \
image="astro")
Pgplot.closeplot()
if debugout:
print 'peakr = %11.5f peakz = %11.5f' % \
(peakr, peakz)
if (peakpow < 0.2):
pows[ct] = peakpow
rmax = peakr
zmax = peakz
else:
[pows[ct], rmax, zmax, rd] = \
maximize_rz(data, peakr, peakz, \
norm=1.0)
if debugout:
print 'max_r = %11.5f max_z = %11.5f' % \
