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map.py
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map.py
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"""Utilities wrapped around cartopy/matplotlib for maps."""
############################################################
# 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
# from mintpy.utils import plot as pp
import numpy as np
import pyproj
from cartopy import crs as ccrs
from cartopy.mpl import ticker as cticker
from matplotlib import pyplot as plt
########################################## 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 = 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 = 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', linewidth=2):
"""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
kwargs = dict(color=color, linewidth=linewidth)
ax.plot([lon0, lon1], [lat_c, lat_c], **kwargs)
ax.plot([lon0, lon0], [lat_c, lat_c + 0.1*length_disp], **kwargs)
ax.plot([lon1, lon1], [lat_c, lat_c + 0.1*length_disp], **kwargs)
## 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)