plot_coherence_matrix: add continuous time-axis view

src/mintpy/cli/plot_coherence_matrix.py

@@ -60,6 +60,8 @@ def create_parser(subparsers=None):
                         help='temporal coherence file.')
     parser.add_argument('-t','--template', dest='template_file',
                         help='temporal file.')
+    parser.add_argument('--time-axis', dest='time_axis', action='store_true',
+                        help='Use continuous time axis instead of date indices for coherence matrix')
 
     parser.add_argument('--save', dest='save_fig',
                         action='store_true', help='save the figure')

src/mintpy/plot_coherence_matrix.py

@@ -72,6 +72,8 @@ def __init__(self, inps):
         self.fig_mat = None
         self.ax_mat = None
 
+        self.time_axis = getattr(inps, 'time_axis', False)
+
         # copy inps to self object
         for key, value in inps.__dict__.items():
             setattr(self, key, value)
@@ -151,10 +153,78 @@ def plot_init_image(self):
         self.fig_img.tight_layout()
         return
 
+    def plot_coherence_matrix4pixel_time_axis(self, yx):
+        """Plot coherence matrix with continuous time axis for one pixel."""
+        self.ax_mat.cla()
+
+        box = (yx[1], yx[0], yx[1]+1, yx[0]+1)
+        coh = readfile.read(self.ifgram_file, datasetName='coherence', box=box)[0]
+
+        ex_date12_list = self.ex_date12_list[:]
+        if self.min_coh_used > 0.:
+            ex_date12_list += np.array(self.date12_list)[coh < self.min_coh_used].tolist()
+            ex_date12_list = sorted(list(set(ex_date12_list)))
+
+        plotDict = {}
+        plotDict['fig_title'] = f'Y = {yx[0]}, X = {yx[1]}'
+        if self.tcoh is not None:
+            tcoh = self.tcoh[yx[0], yx[1]]
+            plotDict['fig_title'] += f', tcoh = {tcoh:.2f}'
+        plotDict['colormap'] = self.colormap
+        if len(self.cmap_vlist) >= 2:
+            plotDict['vlim'] = [self.cmap_vlist[0], self.cmap_vlist[-1]]
+        else:
+            plotDict['vlim'] = [0.0, 1.0]
+        plotDict['cbar_label'] = 'Coherence'
+        plotDict['disp_legend'] = False
+
+        pp.plot_coherence_matrix_time_axis(
+            self.ax_mat,
+            date12List=self.date12_list,
+            cohList=coh.tolist(),
+            date12List_drop=ex_date12_list,
+            p_dict=plotDict,
+        )
+
+        self.ax_mat.annotate('ifgrams\navailable', xy=(0.05, 0.05), xycoords='axes fraction', fontsize=12)
+        self.ax_mat.annotate('ifgrams\nused', ha='right', xy=(0.95, 0.85), xycoords='axes fraction', fontsize=12)
+
+        msg = f'pixel in yx = {tuple(yx)}, '
+        msg += f'min/max spatial coherence: {np.nanmin(coh):.2f} / {np.nanmax(coh):.2f}, '
+        if self.tcoh is not None:
+            msg += f'temporal coherence: {tcoh:.2f}'
+        vprint(msg)
+
+        self.fig_mat.canvas.manager.set_window_title(self.figname_mat)
+        if not hasattr(self, "_mat_tight_layout_done"):
+            self.fig_mat.tight_layout()
+            self._mat_tight_layout_done = True
+
+        self.fig_mat.canvas.draw_idle()
+        self.fig_mat.canvas.flush_events()
+
+        # plot/update marker on the image window
+        if self.fig_coord == 'geo':
+            lat, lon = self.coord.yx2lalo(yx[0], yx[1])
+        mx = lon if self.fig_coord == 'geo' else yx[1]
+        my = lat if self.fig_coord == 'geo' else yx[0]
+        if self._marker_artist is None:
+            self._marker_artist = self.ax_img.plot(
+                mx, my, 'r^', markersize=6, markeredgecolor='black'
+            )[0]
+        else:
+            self._marker_artist.set_data([mx], [my])
+
+        self.fig_img.canvas.draw_idle()
+        return
+
     def plot_coherence_matrix4pixel(self, yx):
         """Plot coherence matrix for one pixel
         Parameters: yx : list of 2 int
         """
+        if self.time_axis:
+            return self.plot_coherence_matrix4pixel_time_axis(yx)
+
         self.ax_mat.cla()
 
         # read coherence

src/mintpy/plot_network.py

@@ -173,7 +173,7 @@ def plot_network(inps):
     # figure names
     ext = 'Ion.pdf' if os.path.basename(inps.file).startswith('ion') else '.pdf'
     fig_names = {
-        'coherence' : [i+ext for i in ['pbaseHistory',  'coherenceHistory', 'coherenceMatrix', 'network']],
+        'coherence' : [i+ext for i in ['pbaseHistory',  'coherenceHistory', 'coherenceMatrix', 'coherenceMatrixTimeAxis', 'network']],
         'offsetSNR' : [i+ext for i in ['pbaseHistory',        'SNRHistory',       'SNRMatrix', 'network']],
         'tbase'     : [i+ext for i in ['pbaseHistory',      'tbaseHistory',     'tbaseMatrix', 'network']],
         'pbase'     : [i+ext for i in ['pbaseHistory', 'pbaseRangeHistory',     'pbaseMatrix', 'network']],
@@ -204,7 +204,7 @@ def plot_network(inps):
         )
         if inps.save_fig:
             fig.savefig(fig_names[1], **kwargs)
-            print(f'save figure to {fig_names[2]}')
+            print(f'save figure to {fig_names[1]}')
 
         # Fig 3 - Coherence Matrix
         fig_size3 = np.mean(inps.fig_size)
@@ -218,9 +218,25 @@ def plot_network(inps):
         )[0]
         if inps.save_fig:
             fig.savefig(fig_names[2], **kwargs)
-            print(f'save figure to {fig_names[1]}')
+            print(f'save figure to {fig_names[2]}')
+
+        # Fig 4 - Coherence Matrix with Time Axis
+        fig_size4 = np.mean(inps.fig_size)
+        fig, ax = plt.subplots(figsize=[fig_size4, fig_size4])
+        ax = pp.plot_coherence_matrix_time_axis(
+            ax,
+            inps.date12List,
+            inps.cohList,
+            inps.date12List_drop,
+            p_dict=vars(inps),
+        )[0]
+        fig.tight_layout()
+        if inps.save_fig:
+            fig.savefig(fig_names[3], **kwargs)
+            print(f'save figure to {fig_names[3]}')
 
-    # Fig 4 - Interferogram Network
+    # Fig 5 - Interferogram Network (or Fig 4 if cohList is None)
+    fig_idx = 4 if inps.cohList is not None else 3
     fig, ax = plt.subplots(figsize=inps.fig_size)
     ax = pp.plot_network(
         ax,
@@ -231,8 +247,8 @@ def plot_network(inps):
         inps.date12List_drop,
     )
     if inps.save_fig:
-        fig.savefig(fig_names[3], **kwargs)
-        print(f'save figure to {fig_names[3]}')
+        fig.savefig(fig_names[fig_idx], **kwargs)
+        print(f'save figure to {fig_names[fig_idx]}')
 
     if inps.disp_fig:
         print('showing ...')

src/mintpy/utils/plot.py

@@ -959,6 +959,172 @@ def plot_coherence_matrix(ax, date12List, cohList, date12List_drop=[], p_dict={}
     return ax, coh_mat, im
 
 
+def plot_coherence_matrix_time_axis(ax, date12List, cohList, date12List_drop=[], p_dict={}):
+    """Plot Coherence Matrix with continuous time axis
+    Parameters: ax : matplotlib.pyplot.Axes,
+                date12List : list of date12 in YYYYMMDD_YYYYMMDD format
+                cohList    : list of float, coherence value
+                date12List_drop : list of date12 for date12 marked as dropped
+                p_dict  : dict of plot setting
+    Returns:    ax : matplotlib.pyplot.Axes
+                coh_mat : 2D np.array in size of [num_date, num_date]
+                mesh : matplotlib.collections.QuadMesh object
+    """
+    # Figure Setting
+    if 'ds_name'     not in p_dict.keys():   p_dict['ds_name']     = 'Coherence'
+    if 'fontsize'    not in p_dict.keys():   p_dict['fontsize']    = 12
+    if 'disp_title'  not in p_dict.keys():   p_dict['disp_title']  = True
+    if 'fig_title'   not in p_dict.keys():   p_dict['fig_title']   = '{} Matrix'.format(p_dict['ds_name'])
+    if 'colormap'    not in p_dict.keys():   p_dict['colormap']    = 'RdBu_truncate'
+    if 'cbar_label'  not in p_dict.keys():   p_dict['cbar_label']  = p_dict['ds_name']
+    if 'vlim'        not in p_dict.keys():   p_dict['vlim']        = (0.2, 1.0)
+    if 'disp_cbar'   not in p_dict.keys():   p_dict['disp_cbar']   = True
+    if 'legend_loc'  not in p_dict.keys():   p_dict['legend_loc']  = 'best'
+    if 'disp_legend' not in p_dict.keys():   p_dict['disp_legend'] = True
+
+    # support input colormap: string for colormap name, or colormap object directly
+    if isinstance(p_dict['colormap'], str):
+        cmap = ColormapExt(p_dict['colormap']).colormap
+    elif isinstance(p_dict['colormap'], mpl.colors.LinearSegmentedColormap):
+        cmap = p_dict['colormap']
+    else:
+        raise ValueError('unrecognized colormap input: {}'.format(p_dict['colormap']))
+
+    date12List = ptime.yyyymmdd_date12(date12List)
+    coh_mat = pnet.coherence_matrix(date12List, cohList)
+
+    m_dates = [i.split('_')[0] for i in date12List]
+    s_dates = [i.split('_')[1] for i in date12List]
+    dateList = ptime.yyyymmdd(sorted(list(set(m_dates + s_dates))))
+    dateList_dt = [dt.datetime.strptime(i, '%Y%m%d') for i in dateList]
+
+    if date12List_drop:
+        date12List_drop = ptime.yyyymmdd_date12(date12List_drop)
+        for date12 in date12List_drop:
+            idx1, idx2 = (dateList.index(i) for i in date12.split('_'))
+            coh_mat[idx1, idx2] = np.nan
+
+    if len(dateList_dt) == 1:
+        half_width = dt.timedelta(days=15)
+        grid_points = [dateList_dt[0] - half_width, dateList_dt[0] + half_width]
+    else:
+        grid_points = [dateList_dt[0] - (dateList_dt[1] - dateList_dt[0])]
+        for date1, date2 in zip(dateList_dt[:-1], dateList_dt[1:]):
+            grid_points.append(date1 + (date2 - date1) / 2)
+        grid_points.append(dateList_dt[-1] + (dateList_dt[-1] - dateList_dt[-2]))
+
+    grid_nums = mdates.date2num(grid_points)
+    X, Y = np.meshgrid(grid_nums, grid_nums)
+
+    # Show diagonal value as black, to be distinguished from un-selected interferograms
+    diag_mat = np.diag(np.ones(coh_mat.shape[0]))
+    diag_mat[diag_mat == 0.] = np.nan
+    ax.pcolormesh(X, Y, diag_mat, cmap='gray_r', vmin=0.0, vmax=1.0, shading='auto', zorder=1)
+
+    cmap_plot = cmap.copy()
+    cmap_plot.set_bad('white')
+    mesh = ax.pcolormesh(
+        X, Y, coh_mat,
+        cmap=cmap_plot,
+        vmin=p_dict['vlim'][0],
+        vmax=p_dict['vlim'][1],
+        shading='auto',
+        zorder=0,
+    )
+
+    # numeric month/year axis labels
+    fs = p_dict['fontsize']
+    min_date, max_date = min(dateList_dt), max(dateList_dt)
+    if min_date.day > 1:
+        if min_date.month == 12:
+            tick_start = min_date.replace(year=min_date.year + 1, month=1, day=1)
+        else:
+            tick_start = min_date.replace(month=min_date.month + 1, day=1)
+    else:
+        tick_start = min_date.replace(day=1)
+
+    tick_dates = []
+    current_date = tick_start
+    while current_date <= max_date:
+        tick_dates.append(current_date)
+        if current_date.month == 12:
+            current_date = current_date.replace(year=current_date.year + 1, month=1)
+        else:
+            current_date = current_date.replace(month=current_date.month + 1)
+
+    tick_positions = mdates.date2num(tick_dates)
+    major_ticks = [p for p, d in zip(tick_positions, tick_dates) if d.month == 1]
+    minor_ticks = [p for p, d in zip(tick_positions, tick_dates) if d.month != 1]
+    ax.set_xticks(major_ticks)
+    ax.set_xticks(minor_ticks, minor=True)
+    ax.set_yticks(major_ticks)
+    ax.set_yticks(minor_ticks, minor=True)
+    ax.set_xticklabels([''] * len(major_ticks))
+    ax.set_xticklabels([''] * len(minor_ticks), minor=True)
+    ax.set_yticklabels([''] * len(major_ticks))
+    ax.set_yticklabels([''] * len(minor_ticks), minor=True)
+    ax.tick_params(which='major', direction='out', length=6, width=1.1,
+                   bottom=True, top=True, left=True, right=True)
+    ax.tick_params(which='minor', direction='out', length=3, width=1,
+                   bottom=True, top=True, left=True, right=True)
+
+    offset = (ax.get_ylim()[1] - ax.get_ylim()[0]) * 0.03
+    year_offset = offset * 2.2
+    for i in range(len(tick_dates) - 1):
+        if tick_dates[i].month % 2 == 1:
+            pos = (tick_positions[i] + tick_positions[i + 1]) / 2
+            label = str(tick_dates[i].month)
+            ax.text(pos, ax.get_ylim()[1] + offset, label, ha='center', va='top', fontsize=fs)
+            ax.text(ax.get_xlim()[0] - offset, pos, label, ha='right', va='center', fontsize=fs)
+
+    year_groups = {}
+    for i, date in enumerate(tick_dates):
+        year_groups.setdefault(date.year, []).append(tick_positions[i])
+    for year, positions in sorted(year_groups.items()):
+        pos = (positions[0] + positions[-1]) / 2
+        ax.text(pos, ax.get_ylim()[1] + year_offset, str(year), ha='center', va='top', fontsize=fs)
+        ax.text(ax.get_xlim()[0] - year_offset, pos, str(year),
+                ha='right', va='center', fontsize=fs, rotation=90)
+
+    ax.set_xlabel('Time', fontsize=fs, labelpad=18)
+    ax.set_ylabel('Time', fontsize=fs, labelpad=18)
+    ax.set_aspect('equal', adjustable='box')
+    ax.invert_yaxis()
+
+    if p_dict['disp_title']:
+        ax.set_title(p_dict['fig_title'], fontsize=p_dict['fontsize'])
+
+    # Colorbar
+    if p_dict['disp_cbar']:
+        divider = make_axes_locatable(ax)
+        cax = divider.append_axes("right", "3%", pad="3%")
+        cbar = ax.figure.colorbar(mesh, cax=cax)
+        cbar.set_label(p_dict['cbar_label'], fontsize=p_dict['fontsize'])
+
+    # Legend
+    if date12List_drop and p_dict['disp_legend']:
+        ax.plot([], [], label='Upper: Ifgrams used')
+        ax.plot([], [], label='Lower: Ifgrams all')
+        ax.legend(loc=p_dict['legend_loc'], handlelength=0)
+
+    # Status bar
+    def format_coord(x, y):
+        col = np.searchsorted(grid_nums, x, side='right') - 1
+        row = np.searchsorted(grid_nums, y, side='right') - 1
+        if 0 <= row < len(dateList_dt) and 0 <= col < len(dateList_dt):
+            date1 = dateList_dt[col].strftime('%Y-%m-%d')
+            date2 = dateList_dt[row].strftime('%Y-%m-%d')
+            coh_val = coh_mat[row, col]
+            if not np.isnan(coh_val):
+                return f'x={date1}, y={date2}, v={coh_val:.3f}'
+            return f'x={date1}, y={date2}, v=NaN'
+        return ''
+
+    ax.format_coord = format_coord
+
+    return ax, coh_mat, mesh
+
+
 def plot_num_triplet_with_nonzero_integer_ambiguity(fname, disp_fig=False, font_size=12, fig_size=[9,3]):
     """Plot the histogram for the number of triplets with non-zero integer ambiguity.