def plot(self,
num_pointsx=100,
num_pointsy=100,
num_contours=75,
logz=False,
show=True):
"""Plot the spline.
Args
----
num_pointsx : int
The number of x sampling points to be used to draw the spline.
num_pointsy : int
The number of y sampling points to be used to draw the spline.
num_contours : int
The number of contours for the color plot.
show : bool, optional
If True, `plt.show()` is called at the end, interrupting the flow.
"""
from ximpol.utils.matplotlib_ import pyplot as plt
_x = numpy.linspace(self.xmin(), self.xmax(), num_pointsx)
_y = numpy.linspace(self.ymin(), self.ymax(), num_pointsy)
_x, _y = numpy.meshgrid(_x, _y)
_z = self(_x, _y, grid=False)
if logz:
from matplotlib.colors import LogNorm
_levels = numpy.logspace(-4, numpy.log10(_z.max()), num_contours)
contour = plt.contourf(_x, _y, _z, levels=_levels, norm=LogNorm())
else:
contour = plt.contourf(_x, _y, _z, num_contours)
bar = plt.colorbar()
if self.xname is not None:
plt.xlabel(self.xlabel())
if self.yname is not None:
plt.ylabel(self.ylabel())
if self.zname is not None:
bar.set_label(self.zlabel())
if show:
plt.show()
def plot_pol_map_from_ascii():
output_file = get_output_file()
logger.info('Opening file %s for plotting...' % output_file)
emin,emax, degree, degree_error, angle, angle_error, counts = numpy.loadtxt(output_file, delimiter=',', unpack=True)
_ra = numpy.linspace(ra_min, ra_max, num_points)
_dec = numpy.linspace(dec_min, dec_max, num_points)
_ra, _dec = numpy.meshgrid(_ra, _dec)
fig = plt.figure()
for i in range(len(E_BINNING) - 1):
sigma_array = degree[emin==E_BINNING[i]]/degree_error[emin==E_BINNING[i]]
pol_array = degree[emin==E_BINNING[i]].reshape((num_points,num_points))
sigma_array = sigma_array.reshape((num_points,num_points))
ax1 = fig.add_subplot()
label = 'XIPE %.1d ks'%(DURATION/1000.)
plt.contourf(_ra,_dec,pol_array)
cbar = plt.colorbar()
cbar.ax.set_ylabel('Polarization degree')
plt.text(0.02, 0.92, label, transform=plt.gca().transAxes,
fontsize=20,color='w')
plt.xlabel('RA')
plt.ylabel('DEC')
# fig.gca().add_artist(psf)
plt.show()
ax2 = fig.add_subplot()
plt.contourf(_ra,_dec,sigma_array)
cbar2 = plt.colorbar()
cbar2.ax.set_ylabel('Sigma')
plt.text(0.02, 0.92, label, transform=plt.gca().transAxes,
fontsize=20,color='w')
plt.xlabel('RA')
plt.ylabel('DEC')
plt.show()
def plot(self, num_pointsx=100, num_pointsy=100, num_contours=75,
logz=False, show=True):
"""Plot the spline.
Args
----
num_pointsx : int
The number of x sampling points to be used to draw the spline.
num_pointsy : int
The number of y sampling points to be used to draw the spline.
num_contours : int
The number of contours for the color plot.
show : bool, optional
If True, `plt.show()` is called at the end, interrupting the flow.
"""
from ximpol.utils.matplotlib_ import pyplot as plt
_x = numpy.linspace(self.xmin(), self.xmax(), num_pointsx)
_y = numpy.linspace(self.ymin(), self.ymax(), num_pointsy)
_x, _y = numpy.meshgrid(_x, _y)
_z = self(_x, _y, grid=False)
if logz:
from matplotlib.colors import LogNorm
_levels = numpy.logspace(-4, numpy.log10(_z.max()), num_contours)
contour = plt.contourf(_x, _y, _z, levels=_levels, norm = LogNorm())
else:
contour = plt.contourf(_x, _y, _z, num_contours)
bar = plt.colorbar()
if self.xname is not None:
plt.xlabel(self.xlabel())
if self.yname is not None:
plt.ylabel(self.ylabel())
if self.zname is not None:
bar.set_label(self.zlabel())
if show:
plt.show()
