############################################################ # Program is part of MintPy # # Copyright (c) 2013, Zhang Yunjun, Heresh Fattahi # # Author: Zhang Yunjun, Joshua Zahner, Jun 2022 # ############################################################ # Recommend import: # from mintpy.utils.map import draw_lalo_label, draw_scalebar # OR from mintpy.utils import plot as pp import pyproj import numpy as np from matplotlib import pyplot as plt from cartopy import crs as ccrs from cartopy.mpl import ticker as cticker ########################################## Lat/Lon Labels ########################################## def draw_lalo_label(ax, geo_box, lalo_step=None, lalo_loc=[1, 0, 0, 1], lalo_max_num=4, lalo_offset=None, projection=ccrs.PlateCarree(), font_size=None, print_msg=True): """Auto draw lat/lon label/tick based on coverage from geo_box Parameters: ax : cartopy axes. geo_box : 4-tuple of float, (W, N, E, S) in degree lalo_step : float, major tick interval for X/Y axes lalo_loc : list of 4 bool, positions where the labels are drawn as in [left, right, top, bottom] default: [1,0,0,1] lalo_max_num : int, maximum number of major ticks for X/Y axes lalo_offset : float, distance in points between tick and label. Set to negative value to move the ticklabel inside the plot. projection : cartopy.crs object ... Example: geo_box = (128.0, 37.0, 138.0, 30.0) m.draw_lalo_label(geo_box) """ # default lat/lon sequences lats, lons, lalo_step, digit = auto_lalo_sequence(geo_box, lalo_step=lalo_step, lalo_max_num=lalo_max_num) if print_msg: print(f'plot lat/lon label in step of {lalo_step} and location of {lalo_loc}') # ticklabel/tick style ax.tick_params(which='both', direction='in', labelsize=font_size, left=True, right=True, top=True, bottom=True, labelleft=lalo_loc[0], labelright=lalo_loc[1], labeltop=lalo_loc[2], labelbottom=lalo_loc[3]) # custom padding to move the tick labels inside axis if lalo_offset: ax.tick_params(axis='x', which='major', pad=lalo_offset[1]) ax.tick_params(axis='y', which='major', pad=lalo_offset[0]) # ticklabel symbol style dec_digit = max(0, 0-digit) lon_formatter = cticker.LongitudeFormatter(number_format=f'.{dec_digit}f') lat_formatter = cticker.LatitudeFormatter(number_format=f'.{dec_digit}f') ax.xaxis.set_major_formatter(lon_formatter) ax.yaxis.set_major_formatter(lat_formatter) # plot ticks & tick labels ax.set_xticks(lons, crs=projection) ax.set_yticks(lats, crs=projection) return ax def auto_lalo_sequence(geo_box, lalo_step=None, lalo_max_num=4, step_candidate=[1, 2, 3, 4, 5]): """Auto calculate lat/lon label sequence based on input geo_box Parameters: geo_box : 4-tuple of float, defining UL_lon, UL_lat, LR_lon, LR_lat coordinate lalo_step : float lalo_max_num : int, rough major tick number along the longer axis step_candidate : list of int, candidate list for the significant number of step Returns: lats/lons : np.array of float, sequence of lat/lon auto calculated from input geo_box lalo_step : float, lat/lon label step Example: geo_box = (128.0, 37.0, 138.0, 30.0) lats, lons, step = m.auto_lalo_sequence(geo_box) """ max_lalo_dist = max([geo_box[1] - geo_box[3], geo_box[2] - geo_box[0]]) if not lalo_step: # Initial tick step lalo_step = round_to_1(max_lalo_dist / lalo_max_num) # reduce decimal if it ends with 8/9 digit = np.int(np.floor(np.log10(lalo_step))) if str(lalo_step)[-1] in ['8','9']: digit += 1 lalo_step = round(lalo_step, digit) # Final tick step - choose from candidate list lalo_step_candidate = [i*10**digit for i in step_candidate] distance = [(i - max_lalo_dist / lalo_max_num) ** 2 for i in lalo_step_candidate] lalo_step = lalo_step_candidate[distance.index(min(distance))] digit = np.int(np.floor(np.log10(lalo_step))) # Auto tick sequence lat_major = np.ceil( geo_box[3] / 10**(digit+1) ) * 10**(digit+1) lon_major = np.ceil( geo_box[0] / 10**(digit+1) ) * 10**(digit+1) lats = np.hstack((np.arange(lat_major, lat_major - 10.*max_lalo_dist, -lalo_step), np.arange(lat_major, lat_major + 10.*max_lalo_dist, lalo_step))) lons = np.hstack((np.arange(lon_major, lon_major - 10.*max_lalo_dist, -lalo_step), np.arange(lon_major, lon_major + 10.*max_lalo_dist, lalo_step))) lats = np.sort(np.unique(lats)) lons = np.sort(np.unique(lons)) lats = lats[np.where(np.logical_and(lats >= geo_box[3], lats <= geo_box[1]))] lons = lons[np.where(np.logical_and(lons >= geo_box[0], lons <= geo_box[2]))] return lats, lons, lalo_step, digit ############################################ Scale Bar ############################################# def draw_scalebar(ax, geo_box, unit='degrees', loc=[0.2, 0.2, 0.1], labelpad=0.05, font_size=12, color='k'): """draw a simple map scale from x1,y to x2,y in map projection coordinates, label it with actual distance ref_link: http://matplotlib.1069221.n5.nabble.com/basemap-scalebar-td14133.html Parameters: ax : matplotlib.pyplot.axes object geo_box : tuple of 4 float in (x0, y0, x1, y1) for (W, N, E, S) in degrees / meters unit : str, coordinate unit - degrees or meters loc : list of 3 float in (length, y, x) of scale bar location: length = ratio of the total width y / x = axes fraction of the scale bar center labelpad : float Returns: ax : matplotlib.pyplot.axes object Example: from mintpy.utils import plot as pp pp.draw_scale_bar(ax, geo_box) """ geod = pyproj.Geod(ellps='WGS84') ax = ax if ax else plt.gca() ## location - center lon_c = geo_box[0] + loc[1] * (geo_box[2] - geo_box[0]) lat_c = geo_box[3] + loc[2] * (geo_box[1] - geo_box[3]) ## length # 1. calc scene width in meters if unit.startswith('meter'): scene_width = geo_box[2] - geo_box[0] elif unit.startswith('deg'): scene_width = geod.inv(geo_box[0], geo_box[3], geo_box[2], geo_box[3])[2] # do not plot scalebar if the longitude span > 30 deg if (geo_box[2] - geo_box[0]) > 30: return ax # 2. convert length ratio to length in meters length_meter = round_to_1(scene_width * loc[0]) # round to the nearest km if length_meter > 1000.0: length_meter = np.rint(length_meter/1000.0)*1000.0 # 3. convert length in meters to length in display coord unit if unit.startswith('deg'): lon_c2 = geod.fwd(lon_c, lat_c, 90, length_meter)[0] length_disp = np.abs(lon_c - lon_c2) elif unit.startswith('meter'): length_disp = length_meter ## starting/ending longitude lon0 = lon_c - length_disp / 2.0 lon1 = lon_c + length_disp / 2.0 ## plot scale bar ax.plot([lon0, lon1], [lat_c, lat_c], color=color) ax.plot([lon0, lon0], [lat_c, lat_c + 0.1*length_disp], color=color) ax.plot([lon1, lon1], [lat_c, lat_c + 0.1*length_disp], color=color) ## plot scale bar label unit = 'm' if length_meter >= 1000.0: unit = 'km' length_meter *= 0.001 txt_offset = (geo_box[1] - geo_box[3]) * labelpad ax.text(x=lon0+length_disp/2.0, y=lat_c+txt_offset, s=f'{length_meter:.0f} {unit}', va='center', ha='center', fontsize=font_size, color=color) return ax ############################################## Utils ############################################### # copied from utils.util0.py to simplify the module dependency def round_to_1(x): """Return the most significant digit of input number""" digit = int(np.floor(np.log10(abs(x)))) return round(x, -digit)