def plot(self):
# Figure 1
self.fig = plt.figure(self.figname, figsize=self.fig_size)
# Axes 1 - Image
self.ax_img = self.fig.add_axes([0.05, 0.1, 0.4, 0.8])
view_cmd = self.view_cmd.format(self.img_file)
d_img, atr, inps_img = view.prep_slice(view_cmd)
if all(i is not None for i in self.yx):
inps_img.pts_marker = 'r^'
inps_img.pts_yx = np.array(self.yx).reshape(-1, 2)
# point yx --> lalo for geocoded product
if 'Y_FIRST' in atr.keys():
coord = ut.coordinate(atr)
inps_img.pts_lalo = np.array(coord.radar2geo(self.yx[0], self.yx[1])[0:2]).reshape(-1,2)
inps_img.print_msg = self.print_msg
self.ax_img = view.plot_slice(self.ax_img, d_img, atr, inps_img)[0]
# coordinate info
self.coord = ut.coordinate(atr)
self.fig_coord = inps_img.fig_coord
# Axes 2 - coherence matrix
self.ax_mat = self.fig.add_axes([0.55, 0.125, 0.40, 0.75])
self.colormap = pp.ColormapExt(self.cmap_name, vlist=self.cmap_vlist).colormap
if all(i is not None for i in self.yx):
self.plot_coherence_matrix4pixel(self.yx)
# Link the canvas to the plots.
self.cid = self.fig.canvas.mpl_connect('button_press_event', self.update_coherence_matrix)
if self.disp_fig:
plt.show()
return
def plot_init_image(self, img_data):
"""Plot the initial 2D image."""
# prepare data
if self.wrap:
if self.disp_unit_img == 'radian':
img_data *= self.range2phase
img_data = ut.wrap(img_data, wrap_range=self.wrap_range)
# Title and Axis Label
self.disp_date_format = ptime.get_compact_isoformat(self.date_list[0])
disp_date = self.dates[self.idx].strftime(self.disp_date_format)
self.fig_title = 'N = {}, Time = {}'.format(self.idx, disp_date)
# Initial Pixel of interest
self.pts_yx = None
self.pts_lalo = None
if self.yx and self.yx != self.ref_yx:
self.pts_yx = np.array(self.yx).reshape(-1, 2)
if self.lalo:
self.pts_lalo = np.array(self.lalo).reshape(-1, 2)
# call view.py to plot
self.img, self.cbar_img = view.plot_slice(self.ax_img, img_data,
self.atr, self)[2:4]
self.fig_img.canvas.set_window_title(self.figname_img)
self.fig_img.tight_layout(rect=(0, 0, 1, 0.97))
return self.img, self.cbar_img
def plot(self):
# Figure 1
self.fig = plt.figure(self.figname, figsize=self.fig_size)
# Axes 1 - Image
self.ax_img = self.fig.add_axes([0.05, 0.1, 0.4, 0.8])
view_cmd = self.view_cmd.format(self.img_file)
d_img, atr, inps_img = view.prep_slice(view_cmd)
if self.yx:
inps_img.pts_yx = np.array(self.yx).reshape(-1, 2)
inps_img.pts_marker = 'r^'
inps_img.print_msg = self.print_msg
self.ax_img = view.plot_slice(self.ax_img, d_img, atr, inps_img)[0]
# coordinate info
self.coord = ut.coordinate(atr)
self.fig_coord = inps_img.fig_coord
# Axes 2 - coherence matrix
self.ax_mat = self.fig.add_axes([0.55, 0.125, 0.40, 0.75])
self.colormap = pp.ColormapExt(self.cmap_name,
vlist=self.cmap_vlist).colormap
if self.yx:
self.plot_coherence_matrix4pixel(self.yx)
# Link the canvas to the plots.
self.cid = self.fig.canvas.mpl_connect('button_press_event',
self.update_coherence_matrix)
if self.disp_fig:
plt.show()
return
def plot(self):
# Figure 1
self.fig = plt.figure(self.figname, figsize=self.fig_size)
# Axes 1 - Image
self.ax_img = self.fig.add_axes([0.05, 0.1, 0.4, 0.8])
view_cmd = self.view_cmd.format(self.img_file)
d_img, atr, inps_img = view.prep_slice(view_cmd)
if self.yx:
inps_img.pts_yx = np.array(self.yx).reshape(-1, 2)
inps_img.pts_marker = 'r^'
inps_img.print_msg = self.print_msg
self.ax_img = view.plot_slice(self.ax_img, d_img, atr, inps_img)[0]
# coordinate info
self.coord = ut.coordinate(atr)
self.fig_coord = inps_img.fig_coord
# Axes 2 - coherence matrix
self.ax_mat = self.fig.add_axes([0.55, 0.125, 0.40, 0.75])
if self.yx:
self.plot_coherence_matrix4pixel(self.yx)
# Link the canvas to the plots.
self.cid = self.fig.canvas.mpl_connect('button_press_event', self.update_coherence_matrix)
if self.disp_fig:
plt.show()
return
def plot(self):
# Read data for transection
self.data_list = []
self.atr_list = []
for fname in self.file:
data, atr = readfile.read(fname, datasetName=self.dset)
data = pp.scale_data2disp_unit(data,
metadata=atr,
disp_unit=self.disp_unit)[0]
self.data_list.append(data)
self.atr_list.append(atr)
# Figure
self.fig, (self.ax_img,
self.ax_txn) = plt.subplots(1,
2,
num=self.figname,
figsize=self.fig_size)
# Axes 1 - map with view.prep/plot_slice()
self.ax_img = view.plot_slice(self.ax_img, self.data_img, self.atr,
self)[0]
# Axes 2 - transection
self.ax_txn.yaxis.tick_right()
self.ax_txn.yaxis.set_label_position("right")
# plot initial input transect
if self.start_yx and self.end_yx:
self.draw_line(self.start_yx, self.end_yx)
self.draw_transection(self.start_yx, self.end_yx, self.start_lalo,
self.end_lalo)
self.fig.subplots_adjust(left=0.05, wspace=0.25)
# save
if self.save_fig:
outfile = '{}.pdf'.format(self.outfile_base)
self.fig.savefig(outfile,
bbox_inches='tight',
transparent=True,
dpi=self.fig_dpi)
vprint('saved transect to', outfile)
self.cid = self.fig.canvas.mpl_connect('button_release_event',
self.select_point)
if self.disp_fig:
vprint('showing ...')
plt.show()
return
def get_poly_mask(fname, datasetName, print_msg=True):
"""Get mask of pixels within polygon from interactive selection
Parameters: data : 2D np.array in size of (length, width)
Returns: mask : 2D np.arrat in size of (length, width) in np.bool_ format
"""
# option 1 - Advanced plot using view.prep/plot_slice()
cmd = 'view.py {} '.format(fname)
if datasetName:
cmd += ' {} '.format(datasetName)
## Customized setting for plotting (temporarily for advanced users)
#cmd += ' --dem ./inputs/geometryGeo.h5 --contour-step 100 --contour-smooth 0.0 '
#cmd += ' -u cm -v -6 6 '
d_v, atr, inps = view.prep_slice(cmd)
ax = plt.subplots(figsize=inps.fig_size)[1]
inps.fig_coord = 'radar' #selector works for radar coord plot only
ax, inps, im = view.plot_slice(ax, d_v, atr, inps)[0:3]
## Option 2 - Simple plot with matplotlib
#from mintpy.utils import readfile
#data = readfile.read(fname, datasetName)[0]
#vlim = np.nanmax(np.abs(data))
#vmin, vmax = -vlim, vlim
## for dataset with non-negative values such as elevation
#if np.nanmin(data) > 0:
# vmin = np.nanmin(data)
## plot
#fig, ax = plt.subplots()
#im = ax.imshow(data, cmap='jet', vmin=vmin, vmax=vmax)
#fig.colorbar(im)
selector = SelectFromCollection(ax, im)
plt.show()
selector.disconnect()
if hasattr(selector, 'mask'):
mask = selector.mask
if print_msg:
print('selected polygon: {}'.format(selector.poly_path))
else:
mask = None
if print_msg:
print('no polygon selected.\n')
return mask
def plot_init_image(self, img_data):
# prepare data
if self.wrap:
if self.disp_unit_img == 'radian':
img_data *= self.range2phase
img_data = ut.wrap(img_data, wrap_range=self.wrap_range)
# Title and Axis Label
disp_date = self.dates[self.idx].strftime('%Y-%m-%d')
self.fig_title = 'N = {}, Time = {}'.format(self.idx, disp_date)
# Initial Pixel of interest
self.pts_yx = None
self.pts_lalo = None
if self.yx and self.yx != self.ref_yx:
self.pts_yx = np.array(self.yx).reshape(-1, 2)
if self.lalo:
self.pts_lalo = np.array(self.lalo).reshape(-1, 2)
# call view.py to plot
self.img, self.cbar_img = view.plot_slice(self.ax_img, img_data, self.atr, self)[2:4]
return self.img, self.cbar_img
if save_fig:
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=[8, 3])
# read vel data
cmd = 'view.py {} velocity --mask {} '.format(vel_file, mask_file)
cmd += ' --sub-lon {w} {e} --sub-lat {s} {n} '.format(w=geo_box[0],
n=geo_box[1],
e=geo_box[2],
s=geo_box[3])
cmd += ' -c bwr_r -v -1.0 1.0 --cbar-loc bottom --cbar-nbins 5 --cbar-ext both --cbar-size 5% '
cmd += ' --dem {} --dem-nocontour '.format(dem_file)
cmd += ' --lalo-step 0.2 --lalo-loc 1 0 1 0 --scalebar 0.3 0.80 0.05 --notitle --fontsize 12 '
cmd += ' --noverbose'
d_v, atr, inps = view.prep_slice(cmd)
ax[0], inps, im, cbar = view.plot_slice(ax[0], d_v, atr, inps)
ax[0].plot(lon, lat, "k^", mfc='none', mew=1.,
ms=6) # point of interest
cbar.set_label("LOS Velocity [cm/yr]", fontsize=font_size)
ax[1].scatter(dates, d_ts, marker='o', s=4**2) # , color='k')
pp.auto_adjust_xaxis_date(ax[1], obj.yearList, fontsize=font_size)
ax[1].set_xlabel('Time [years]', fontsize=font_size)
ax[1].set_ylabel('LOS Displacement [cm]', fontsize=font_size)
ax[1].yaxis.set_minor_locator(ticker.AutoMinorLocator())
ax[1].tick_params(which='both',
direction='in',
labelsize=font_size,
bottom=True,
top=True,
