def click(event):
"""
Handle mouse click in the main matplotlib overview window, opens single monitor window
called from: display
input: event structure
output: None
"""
from pylab import get_current_fig_manager,get,gcf,figure,clf,connect,show
tb = get_current_fig_manager().toolbar
if event.button==1 and event.inaxes and tb.mode == '':
g = event.inaxes
# Determine number of clicked axis
ax = get(gcf(),'axes')
jused = 0
for j in range(0, len(FSlist)):
FS = FSlist[j]
if g==FS['axes']:
h=figure()
clf()
FS=display_single(FS)
connect('key_press_event', keypress)
jused = j
FSlist[jused]['axes']=g
show()
def click(event):
"""
Handle mouse click in the main matplotlib overview window, opens single monitor window
called from: display
input: event structure
output: None
"""
from pylab import get_current_fig_manager,get,gcf,figure,clf,connect,show
tb = get_current_fig_manager().toolbar
if event.button==1 and event.inaxes and tb.mode == '':
g = event.inaxes
# Determine number of clicked axis
ax = get(gcf(),'axes')
jused = 0
for j in range(0, len(FSlist)):
FS = FSlist[j]
if g==FS['axes']:
h=figure()
clf()
FS=display_single(FS)
connect('key_press_event', keypress)
jused = j
FSlist[jused]['axes']=g
show()
def main():
'''Plot a surfaces defined in a JSON file
Typical use:
tfitsurf -n 1 X_IMAGE Y_IMAGE FWHM_IMAGE < sub.cat > sub.json
jsurfplot sub.json
'''
parser = argparse.ArgumentParser()
parser.add_argument("input_file",
help="Input JSON file containing the surface")
parser.add_argument("-o", "--output_file", help="Output file name")
parser.add_argument("-n",
"--number_format",
help="Number format for contours",
default='%1.1f')
parser.add_argument("-p",
"--points",
help="Plot data points",
action="store_true")
parser.add_argument("-T",
"--type",
type=int,
default=1,
help="Type of plot (1=image, 2=surface)")
parser.add_argument("-t", "--title", help="Title of the plot")
parser.add_argument("-l",
"--lower",
type=float,
help="Lower limit to plot range")
parser.add_argument("-u",
"--upper",
type=float,
help="Upper limit to plot range")
parser.add_argument("-X",
type=int,
default=3352,
help="Number of X pixels")
parser.add_argument("-Y",
type=int,
default=2532,
help="Number of Y pixels")
parser.add_argument("-v",
"--verbose",
help="Increase output verbosity",
action="store_true")
parser.add_argument("-m",
"--mean",
help="Display mean in the title",
action="store_true")
parser.add_argument("-C",
"--contour",
help="Draw labeled contours",
action="store_true")
args = parser.parse_args()
nx = args.X
ny = args.Y
points = args.points
number_format = args.number_format
verbose = args.verbose
plottype = args.type
thetitle = args.title
drawcontours = args.contour
input_file = args.input_file
output_file = args.output_file
lower = args.lower
upper = args.upper
showmean = args.mean
'Get data from JSON file'
json_data = open(input_file)
data = json.load(json_data)
equation = data['equation']
labels = data['axes']
json_data.close()
def fun(x, y):
return eval(equation)
'Define the color map'
cmap = cm.Spectral
'Image plot'
if (plottype == 1):
x = np.arange(1, nx, 20)
y = np.arange(1, ny, 20)
X, Y = np.meshgrid(x, y)
zs = np.array([fun(x, y) for x, y in zip(np.ravel(X), np.ravel(Y))])
Z = zs.reshape(X.shape)
fig = plt.figure(figsize=(7, 4.5))
fig.subplots_adjust(hspace=0.15,
wspace=0,
top=0.95,
bottom=0.07,
left=0.14,
right=0.98)
ax = fig.add_subplot(111)
extent = (1, nx, 1, ny)
if (not lower):
lower = Z.min()
if (not upper):
upper = Z.max()
norm = cm.colors.Normalize(vmax=upper, vmin=lower)
im = imshow(Z,
interpolation='nearest',
extent=extent,
cmap=cmap,
norm=norm)
ax.set_xlabel(labels[0])
ax.set_ylabel(labels[1])
if (thetitle):
if (showmean):
thetitle = "%s (Mean: %.2f)" % (thetitle, np.mean(Z))
title(thetitle)
'Plot the data points'
if (points):
xs = data['xdata']
ys = data['ydata']
scatter(xs, ys, s=5, marker='.', color='b')
'Plot the contours'
if (drawcontours):
dz = (Z.max() - Z.min()) / 6
levels = arange(Z.min(), Z.max(), dz)
cplot = contour(Z,
levels,
hold='on',
colors='k',
extent=extent,
linewidth=0.1,
origin='image')
plt.clabel(cplot,
inline=2,
fmt=number_format,
use_clabeltext=True,
fontsize=10,
origin='image')
'Plot the color bar'
ylim = get(gca(), 'ylim')
setp(gca(), ylim=ylim[::-1])
cbar = colorbar(im, shrink=0.7, aspect=15)
cbar.ax.set_ylabel(labels[2], rotation=90)
'Surface plot'
if (plottype == 2):
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = np.arange(1, nx, 20)
y = np.arange(1, ny, 20)
X, Y = np.meshgrid(x, y)
zs = np.array([fun(x, y) for x, y in zip(np.ravel(X), np.ravel(Y))])
Z = zs.reshape(X.shape)
surf = ax.plot_surface(X, Y, Z, cmap=cmap, linewidth=0.2)
ax.set_xlabel(labels[0])
ax.set_ylabel(labels[1])
ax.set_zlabel(labels[2])
if (thetitle):
title(thetitle)
'Plot the data points'
if (points):
xs = data['xdata']
ys = data['ydata']
ax.scatter(xs, ys, 0, c='r', marker='.')
'Plot the color bar'
cbar = fig.colorbar(surf, shrink=0.5, aspect=15)
cbar.ax.set_ylabel(labels[2], rotation=90)
if (output_file):
plt.savefig(output_file)
else:
plt.show()