def SavePlot(y, filename, xtitle='', ytitle='', title=''):
plot = Figure(figsize=(12, 3))
ax = plot.add_subplot(111)
# plot.grid(True)
ax.set_title(title)
ax.set_xlabel(xtitle)
ax.set_ylabel(ytitle)
# ax.axis(ymax=1, ymin =-3)
plot.subplots_adjust(left=0.1, bottom=0.2)
x = range(len(y))
# ax.plot(x, nu.log2(Y))
ax.plot(x, y)
FigureCanvasAgg(ax.get_figure()).print_figure(filename, dpi=120)
return
def timeseries_station_page(ms, station_name, time_slots, data, fn=abs, output_name=None):
dpi=50
if output_name is None:
fig = figure(figsize=(32,24), dpi=dpi)
else:
fig = Figure(figsize=(32,24), dpi=dpi)
station_name_list = list(ms.tables['antennae']['NAME'])
station_id = station_name_list.index(station_name)
num_ant = len(ms.tables['antennae'])
tsn = time_slots-time_slots[0]
pol_names = corr_type(ms.tables['polarization']['CORR_TYPE'][0])
ref_freq_mhz = ms.tables['spectral_windows'][0]['REF_FREQUENCY']/1.e6
fig.suptitle(ms.msname+': '+fn.__name__+'(vis) with '+station_name+' at %3.2f MHz' % (ref_freq_mhz,), fontsize='large')
median_amp = ma.median(ma.mean(ma.median(fn(data[station_id,:,0::3,:]), axis=-1), axis=-1), axis=-1)
for id2,name in enumerate(station_name_list):
ax = fig.add_subplot(ceil(num_ant/4.0),4, id2+1)
ax.plot(tsn, fn(data[station_id,id2,0,:]), c='blue' , label=pol_names[0])
ax.plot(tsn, fn(data[station_id,id2,1,:]), c='green' , label=pol_names[1])
ax.plot(tsn, fn(data[station_id,id2,2,:]), c='purple', label=pol_names[2])
ax.plot(tsn, fn(data[station_id,id2,3,:]), c='red' , label=pol_names[3])
ax.grid()
ax.set_ylabel(station_name_list[id2], rotation='horizontal')
ax.set_ylim(0.0, 3*median_amp)
ax.set_yticklabels([])
if id2 < len(station_name_list)-4:
ax.set_xticklabels([])
else:
ax.set_xlabel('Time [s]')
pass
fig.subplots_adjust(hspace=0.0, top=0.95, bottom=0.04)
if output_name is not None:
canvas = FigureCanvasAgg(fig)
if output_name[-4:] in ['.jpg', '.JPG']:
canvas.print_jpg(output_name, dpi=dpi, quality=55)
else:
canvas.print_figure(output_name, dpi=dpi)
pass
pass
T = np.sqrt(1.0 - R ** 2)
D = T ** 4 + 4 * R ** 2 * np.sin(2 * np.pi * (w + w_hene) / c * L) ** 2
I = T ** 4 / D
# Saturation radiation density
Ws = hbar * (w_hene) ** 3 / np.pi ** 2 / c ** 2
# Create the figure instance
if use_mpl:
fig = Figure()
else:
fig = pl.figure(prog_title)
# Create the axes for the main plot and plot the initial data
axes = fig.add_subplot(111)
fig.subplots_adjust(bottom=0.25)
plt, = axes.plot(c / (w + w_hene) * 1e9, F * I * 1e6, "r")
# Declare the areas dedicated for the slider controls
axes_length = fig.add_axes([0.17, 0.12, 0.73, 0.03])
axes_reflect = fig.add_axes([0.17, 0.06, 0.73, 0.03])
# If using matplotlib, we must create the canvas area of the Window before
# creating the actual Sliders.
if use_mpl:
# Create root Tk widget and set the title
root = tk.Tk()
root.title(prog_title)
# Create and pack the renderable area of the widget, using the figure class
plot_widget = FigureCanvasTkAgg(fig, master=root)
