def __init__(self, data, toplevel):
"""
*Initialize with:*
Args:
data (GlobalData Object): Source of Data
"""
super(PlotArea, self).__init__()
self.toplevel = toplevel
# GlobalData
self.data = data
# look_at_head: index-_bufsize:index -> the data you gonna display
self.look_at_head = 0
# look at present?
self.look_at_present = True
# number of points in buffer
self._bufsize = int(100)
# scrol Window Adjustments
self.adj_scroll_hist = None
self.axisequal = False
#
self.BufSizeSpinnBtn = None
# MPL:
# create figure
self.figure = Figure()
# create axes
self.axx = self.figure.add_subplot(111)
# set grid
self.axx.grid(True)
# set equal scale
self.axx.set_aspect('auto')
# set dynamic canvas to GTK3AGG backend
self.canvas = FigureCanvasGTK3Agg(self.figure)
# init plots
self.points = {}
self.nartist = 16
self.nMarkers = 7
# set the first 7 artists as Markers instead of lines
for artist in range(self.nMarkers):
self.points[artist] = self.axx.plot(nan, nan, 'ko')[0]
for artist in range(self.nMarkers, self.nartist):
self.points[artist] = self.axx.plot(nan, nan, '-')[0]
# GTK:
vbox = Gtk.VBox(False, 3)
self.add(vbox)
# Get PlotWindow and connect to figure
self.plot_win = Gtk.Viewport()
self.plot_win.add(self.canvas)
self.buffer_win = Gtk.Viewport()
vbox.pack_start(self.plot_win, True, True, 0)
vbox.pack_start(self.buffer_win, False, True, 1)
self._init_buffer_box()
# ######
# finally show
self.canvas.show()
self.show_all()
def __init__(self, data_file,
plot_groups = [1],
data_type = 2,
color_map = 'jet',
plot_contours = False,
face_colour = "white",
filled_contours = False,
plot_label = "",
plot_bands = None,
time_zone = 0,
plot_max_freq = 30.0,
run_quietly = False,
save_file = '',
dpi=150,
parent = None,
user_bands=None,
datadir=None):
"""
user_bands - a list of bands to be displayed.
"""
self.data_type = data_type
self.run_quietly = run_quietly
self.dpi=dpi
self.plot_filled_contours = filled_contours
self.df = VOAOutFile(data_file, time_zone=time_zone, data_type=self.data_type, quiet=run_quietly)
self.image_defs = self.IMG_TYPE_DICT[self.data_type]
self.user_bands = user_bands
portland = ListedColormap(["#0C3383", "#0b599b","#0a7fb4","#57a18f","#bec255","#f2c438","#f2a638","#ef8235","#e4502a","#d91e1e"])
matplotlib.cm.register_cmap(name='portland', cmap=portland)
if plot_groups[0]=='a':
num_grp = self.df.get_number_of_groups()
plot_groups = list(range(0,num_grp))
number_of_subplots = len(plot_groups)
#matplotlib.rcParams['mpl_toolkits.legacy_colorbar'] = False
matplotlib.rcParams['axes.edgecolor'] = 'gray'
matplotlib.rcParams['axes.facecolor'] = 'white'
matplotlib.rcParams['axes.grid'] = True
matplotlib.rcParams['grid.alpha'] = 0.4
matplotlib.rcParams['legend.fancybox'] = True
matplotlib.rcParams['legend.shadow'] = True
matplotlib.rcParams['figure.subplot.hspace'] = 0.45
matplotlib.rcParams['figure.subplot.wspace'] = 0.35
matplotlib.rcParams['figure.subplot.right'] = 0.85
colorbar_fontsize = 12
if number_of_subplots <= 1:
num_rows = 1
self.main_title_fontsize = 24
matplotlib.rcParams['legend.fontsize'] = 12
matplotlib.rcParams['axes.labelsize'] = 12
matplotlib.rcParams['axes.titlesize'] = 8
matplotlib.rcParams['xtick.labelsize'] = 10
matplotlib.rcParams['ytick.labelsize'] = 10
matplotlib.rcParams['figure.subplot.top'] = 0.79 # single figure plots have a larger title so require more space at the top.
self.x_axes_ticks = np.arange(0,25,2)
elif ((number_of_subplots >= 2) and (number_of_subplots <= 6 )):
num_rows = 2
self.main_title_fontsize = 18
matplotlib.rcParams['legend.fontsize'] = 10
matplotlib.rcParams['axes.labelsize'] = 10
matplotlib.rcParams['axes.titlesize'] = 11
matplotlib.rcParams['xtick.labelsize'] = 8
matplotlib.rcParams['ytick.labelsize'] = 8
self.x_axes_ticks = np.arange(0,25,4)
else:
num_rows = 3
self.main_title_fontsize = 16
matplotlib.rcParams['legend.fontsize'] = 8
matplotlib.rcParams['axes.labelsize'] = 8
matplotlib.rcParams['axes.titlesize'] = 10
matplotlib.rcParams['xtick.labelsize'] = 6
matplotlib.rcParams['ytick.labelsize'] = 6
self.x_axes_ticks = np.arange(0,25,4)
num_cols = int(math.ceil(float(number_of_subplots)/float(num_rows)))
fig = plt.figure()
axgr = AxesGrid(fig, 111,
nrows_ncols=(num_rows, num_cols),
axes_pad=0.6,
cbar_location='right',
cbar_mode='single',
cbar_pad=0.2,
cbar_size='3%',
label_mode='')
self.main_title_label = fig.suptitle(plot_label+str(self.image_defs['title']), fontsize=self.main_title_fontsize)
for ax, chan_grp in zip(axgr, plot_groups):
(group_name, group_info, fot, muf, hpf, image_buffer) = self.df.get_group_data(chan_grp)
if number_of_subplots > 4:
#save a little space by only labelling the outer edges of the plot
ax.label_outer()
_sign = '+' if (time_zone >= 0) else ''
self.x_label = ax.set_xlabel(_('Time (UTC%(sig)s%(tz)s)') % {'sig':_sign, 'tz':time_zone})
self.y_label = ax.set_ylabel(_('Frequency (MHz)'))
## Autoscale y (frequency axis)
if (plot_max_freq==self.AUTOSCALE) :
y_max = math.ceil(max(muf) / 5.0) * 5.0
y_max = min(plot_max_freq, 30.0)
y_max = max(plot_max_freq, 5.0)
else :
y_max = math.ceil(plot_max_freq / 5.0) * 5.0
image_buffer = image_buffer[0:int(y_max-1),:]
y_ticks = [2, 5]
for y_tick_value in np.arange(10, y_max+1, 5):
y_ticks.append(y_tick_value)
ax.plot(list(range(0, 25)), muf,'r-', list(range(0, 25)), fot, 'g-')
ax.set_ylim([2, y_max])
ax.set_xticks(self.x_axes_ticks)
ax.set_yticks(y_ticks)
self.add_legend(ax)
title_str = group_info.strip()
if number_of_subplots > 1:
title_str = self.get_small_title(title_str)
self.subplot_title_label = ax.set_title(title_str, multialignment='left', **self.mono_font)
if (self.data_type > 0):
if (self.plot_filled_contours):
im = ax.contourf(image_buffer,
self.image_defs['y_labels'],
extent=(0, 24, 2, y_max),
cmap=color_map)
plot_contours =True
else:
im = ax.imshow(image_buffer, interpolation='bicubic',
extent=(0, 24, 2, y_max),
origin = 'lower',
cmap=color_map,
alpha = 0.95,
norm = matplotlib.colors.Normalize(clip = False,
vmin=self.image_defs['min'],
vmax=self.image_defs['max']))
if plot_contours:
ax.contour(image_buffer, self.image_defs['y_labels'][1:], extent=(0, 24, 2, y_max), linewidths=1.0, colors='k', alpha=0.6)
if plot_bands:
for a,b in plot_bands:
ax.axhspan(a, b, alpha=0.5, ec='k', fc='k')
if self.user_bands:
for ch in self.user_bands:
ax.axhspan(ch-0.04, ch+0.04, alpha=0.5, ec='0.5', fc='0.5')
# Hide any unused subplots
for ax in axgr[number_of_subplots:]:
ax.set_visible(False)
if (self.data_type > 0):
axgr.cbar_axes[0].colorbar(im,
format = FuncFormatter(eval('self.'+self.image_defs['formatter'])))
#for t in self.cb_ax.get_yticklabels():
### t.set_fontsize(colorbar_fontsize)
if save_file :
fig.savefig(save_file, dpi=self.dpi, facecolor=fig.get_facecolor(), edgecolor='none')
if not self.run_quietly:
canvas = FigureCanvasGTK3Agg(fig)
canvas.show()
dia = VOAPlotWindow('pythonProp - ' + self.image_defs['title'],
canvas,
parent=parent,
dpi=self.dpi,
datadir=datadir)
return
def __init__(self, main_window=None, nbp=0):
Gtk.VBox.__init__(self)
self._main_window = main_window
self.figure = Figure(facecolor='#474747', edgecolor='#474747')
self.canvas = FigureCanvasGTK3Agg(self.figure) # a Gtk.DrawingArea
# --- Flag for primary axis time format
self.xtime = False
# --- The primary axis
self.axis = self.figure.add_subplot(111)
# --- The secondary y-axis (hidden by default)
self.secondary_axis = self.axis.twinx()
self.secondary_axis.set_frame_on(False)
self.show_secondary_axis = True
self.hide_secondary_axis()
# --- A dummy secondary x axis for mousover events
self.dummy_axis = self.axis.twiny()
self.dummy_axis.set_frame_on(False)
self.dummy_axis.set_xticks([])
self.set_dummy_xlim()
self.cb = None
self.nbp = nbp
# Init some globals for getting the mouse position in the client
# application
self.inaxes = False
self.mouse_x = 0
self.mouse_y = 0
hbox = Gtk.HBox(spacing=4)
self.r_label = Gtk.Label("0.0 | ")
self.z_label = Gtk.Label("| 0.0")
self.spacer = Gtk.Label("|")
self.reset_b = Gtk.Button("Reset Zoom")
self.settings_b = Gtk.Button("Settings")
self.pack_start(self.canvas, True, True, 0.0)
self.pack_start(hbox, False, False, 0.0)
hbox.pack_end(self.r_label, False, False, 0.0)
hbox.pack_end(self.spacer, False, False, 0.0)
hbox.pack_end(self.z_label, False, False, 0.0)
hbox.pack_end(self.reset_b, False, False, 0.0)
hbox.pack_start(self.settings_b, False, False, 0.0)
# --- Variables for zooming --- #
self.holddown = False
self.zoom_flag = False
self.box_start = None
self.box_start_px = None
self.box_end = None
self.zoom_box = None
self.zoomlimits = [0., 1., 0., 1.]
self.maxlimits = []
self.autoscale_old = [True, True]
# --- Container for flags to show certain legend entries -- #
self.show_legend_entries = np.array([], 'bool')
# --- Connections --- #
self.canvas.mpl_connect("motion_notify_event", self.mouse_move)
self.canvas.mpl_connect("scroll_event", self.mouse_scroll)
self.canvas.mpl_connect("button_press_event", self.button_pressed)
self.canvas.mpl_connect("button_release_event", self.button_released)
self.reset_b.connect("clicked", self.zoom_out)
self.settings_b.connect("clicked", self.change_settings)
self.canvas.mpl_connect("axes_enter_event", self.axes_enter_callback)
self.canvas.mpl_connect("axes_leave_event", self.axes_leave_callback)
self.canvas.mpl_connect("draw_event", self.draw_event)
self.set_settings(generate_default_settings())
# Create a plotsettings dictionary as a copy of the current plot settings
# Redundand, but a quick workaround for keeping the marker size and linewidth
# even if settings were loaded without any plots
self.main_plot_settings = self.get_settings()
def __init__(self, data_file,
data_type = 2,
color_map = 'jet',
plot_label = "",
time_zone = 0,
plot_max_freq = 30.0,
run_quietly = False,
save_file = '',
parent = None):
self.data_type = data_type
self.data_file = VOAOutFile(data_file, \
time_zone=time_zone, \
data_type=self.data_type)
self.image_defs = self.IMG_TYPE_DICT[self.data_type]
#color_map = eval('P.cm.' + color_map)
num_grp = self.data_file.get_number_of_groups()
if num_grp < 2:
md = Gtk.MessageDialog(parent, \
Gtk.DialogFlags.MODAL,\
Gtk.MessageType.ERROR, \
Gtk.ButtonsType.CANCEL, \
"There must be 2 groups or more")
md.run()
md.destroy()
return
plot_groups = list(range(0, num_grp))
self.subplots = []
number_of_subplots = len(plot_groups)
matplotlib.rcParams['axes.edgecolor'] = 'gray'
matplotlib.rcParams['axes.facecolor'] = 'white'
matplotlib.rcParams['axes.grid'] = True
matplotlib.rcParams['figure.facecolor'] = 'white'
matplotlib.rcParams['legend.fancybox'] = True
matplotlib.rcParams['legend.shadow'] = True
matplotlib.rcParams['figure.subplot.hspace'] = 0.45
matplotlib.rcParams['figure.subplot.wspace'] = 0.35
matplotlib.rcParams['figure.subplot.right'] = 0.85
colorbar_fontsize = 12
self.main_title_fontsize = 24
matplotlib.rcParams['legend.fontsize'] = 12
matplotlib.rcParams['axes.labelsize'] = 12
matplotlib.rcParams['axes.titlesize'] = 10
matplotlib.rcParams['xtick.labelsize'] = 10
matplotlib.rcParams['ytick.labelsize'] = 10
self.x_axes_ticks = np.arange(0, 25, 2)
self.fig = Figure()
ax = Axes3D(self.fig)
X = np.arange(0, 25)
Y = np.arange(0, len(plot_groups))
X, Y = np.meshgrid(X, Y)
data_buffer = [] # hold the Z data sets
for chan_grp in plot_groups:
(group_name, group_info, fot, muf, hpf, image_buffer) = \
self.data_file.get_group_data(chan_grp)
# Copy the element at [0] to the tail of the array
#to 'wrap-around' the values at 24hrs.
np.resize(muf, len(muf)+1)
muf[-1] = muf[0]
data_buffer.append(muf)
Z = np.vstack((tuple(data_buffer)))
# set up the titles and labels
ax.set_xticks(np.arange(0, 25, 2))
if (plot_max_freq==self.AUTOSCALE) :
z_max = math.ceil(max(muf) / 5.0) * 5.0
z_max = min(plot_max_freq, 30.0)
z_max = max(plot_max_freq, 5.0)
else :
z_max = math.ceil(plot_max_freq / 5.0) * 5.0
z_ticks = [2, 5]
for z_tick_value in np.arange(10, z_max+1, 5):
z_ticks.append(z_tick_value)
#ax.set_yticks(z_ticks)
#label axes
tz_sign = '+' if (time_zone >= 0) else ''
self.x_label = ax.set_xlabel('Time (UTC%s%s)' % (tz_sign, time_zone))
self.y_label = ax.set_ylabel('Group')
self.z_label = ax.set_zlabel('Frequency (MHz)')
#do the plot
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=color_map)
canvas = FigureCanvasGTK3Agg(self.fig)
canvas.show()
Axes3D.mouse_init(ax)
VOAPlotWindow('pythonProp - ' + self.image_defs['title'], \
canvas, \
parent)
return
return r
phi = numpy.linspace(0, 2 * numpy.pi, 1024)
m_init = 3
n1_init = 2
n2_init = 18
n3_init = 18
fig = Figure((6, 6), dpi = 80)
ax = fig.add_subplot(111, polar = True)
r = supershape_radius(phi, 1, 1, m_init, n1_init, n2_init, n3_init)
lines, = ax.plot(phi, r, lw = 3.)
win = Gtk.Window()
win.connect('delete-event', Gtk.main_quit)
win.set_title('SuperShape')
canvas = FigureCanvasGTK3Agg(fig)
w, h = fig.get_size_inches()
dpi_res = fig.get_dpi()
w, h = int(numpy.ceil(w * dpi_res)), int(numpy.ceil(h * dpi_res))
canvas.set_size_request(w, h)
win.add(canvas)
win.show_all()
Gtk.main()
