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 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)