-
Notifications
You must be signed in to change notification settings - Fork 1
/
ndsi_p02_modis_daily_map.py
250 lines (207 loc) · 8.3 KB
/
ndsi_p02_modis_daily_map.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
# -*- coding: utf-8 -*-
'''
Created on 2020年4月26日
@author: wape2
'''
import os
import sys
import warnings
import matplotlib.pyplot as plt
import numpy as np
import yaml
from pyhdf.SD import SD
from pylab import axis
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
import matplotlib.patches as mpatches
import matplotlib as mpl
import cartopy.crs as ccrs
mpl.use("Agg")
main_path, main_file = os.path.split(os.path.realpath(__file__))
color_lst_lab = ['Bad Value', 'Undeterminted', 'Night', 'Clear Land', 'Inland Water', 'Sea Water', 'Cloud Cover', 'Ice Cover', 'Snow Cover', 'Satturated', 'No Data']
color_lst_bar = ['w', 'black', 'black', 'w', 'w', 'w', 'black', 'w', 'w', 'w', 'w', 'w']
color_lst = {
'No Data': (0., 0., 0.), # 255-无数据-黑色
'Satturated': (139 / 255., 0., 0.), # 254-太阳天顶角饱和-红褐色
'Snow Cover': (0., 238 / 255., 238 / 255.), # 200-雪-蓝绿色
'Ice Cover': (0., 139 / 255., 139 / 255.), # 100-冰-青色
'Cloud Cover': (255 / 255., 255 / 255., 255 / 255.), # 50-云-白色
'Sea Water': (0., 0., 139 / 255.), # 39-海冰-深蓝色
'Inland Water': (0., 0., 255 / 255.), # 37-内陆水-蓝色
'Clear Land': (160 / 255., 82 / 255., 45 / 255.), # 25-陆地-褐色
'Night': (216 / 255., 191 / 255., 216 / 255.), # 11-暗像元-淡粉色
'Undeterminted':(255 / 255., 255 / 255., 0), # 1-不确定-黄色
'Bad Value': (100 / 255., 100 / 255., 100 / 255.) # 0-丢线-灰色
}
bounds = [0, 0.1, 100.1, 107.1, 111.1, 237.1, 239.1, 250.1, 253.1, 255.1]
color_dict = ['#A0522E', '#00EEEE', '#D8BFD8', '#8B0000', '#0000FF', '#00008B', '#FFFFFF', '#646464', '#000000']
# color_dict = ['#646464', '#FFFF00', '#D8BFD8', '#A0522E', '#0000FF', '#00008B', '#FFFFFF',
# '#008B8B', '#00EEEE', '#8B0000', '#000000']
class ReadInYaml():
def __init__(self, in_file):
"""
读取yaml格式配置文件
"""
if not os.path.isfile(in_file):
print ('Not Found %s' % in_file)
sys.exit(-1)
with open(in_file, 'r') as stream:
cfg = yaml.load(stream)
self.job_name = cfg['INFO']['job_name']
self.ymd = cfg['INFO']['ymd']
self.ipath = cfg['PATH']['ipath']
self.opath = cfg['PATH']['opath']
class ReadModeYaml():
def __init__(self, in_file):
"""
读取yaml格式配置文件
"""
if not os.path.isfile(in_file):
print ('Not Found %s' % in_file)
sys.exit(-1)
with open(in_file, 'r') as stream:
cfg = yaml.load(stream)
self.area = cfg['a02']['area']
self.res = cfg['a02']['res']
def main(yaml_file):
in_cfg = ReadInYaml(yaml_file)
job_name = in_cfg.job_name
ymd = in_cfg.ymd
in_path = in_cfg.ipath
out_path = in_cfg.opath
for eachfile in in_path:
h4r = SD(eachfile)
ndsi_data = h4r.select('Day_CMG_Snow_Cover')[:]
h4r.end()
file_name = os.path.basename(eachfile) + '.png'
out_fig = os.path.join(out_path, file_name)
if not os.path.isdir(out_path):
os.makedirs(out_path)
print (out_fig)
plot_map(job_name, ymd, ndsi_data, out_fig)
# cdict = ['#646464', '#FFFF00', '#D8BFD8', '#A0522E', '#0000FF', '#00018A', '#FFFFFF',
# '#008B8B', '#00EEEE', '#8B0000', '#000000']
def ndsi_colormap():
# 灰色 黄色 淡粉 褐色 蓝色 深蓝 白色 青色 蓝绿 红褐 黑色
# 按照上面定义的colordict，将数据分成对应的部分，indexed：代表顺序
return mpl.colors.ListedColormap(color_dict, 'indexed')
def plot_map(job_name, ymd, img, outfig):
fig = plt.figure(figsize = (20, 10))
ax = fig.add_subplot(111, projection = ccrs.PlateCarree())
pos1 = ax.get_position()
print (pos1)
# ax2 = fig.add_axes([0.91, 0.11, 0.02, 0.771]) # 距离左下的x,y,宽,高
# ax.set_global()
ax.coastlines(resolution = '50m', color = 'black', linewidth = 0.3, zorder = 100)
# ax.stock_img()
print('start')
# w e n s
img_extent = (-180, 180, -90, 90)
# 设置色标的最大最小值
# norm = mpl.colors.Normalize(vmin = 0, vmax = 255)
mycolormap = ndsi_colormap()
# 11个颜色值，对应的11个区间，数据是12个
# bounds = [0, 0.1, 1.1, 11.1, 25.1, 37.1, 39.1, 50.1, 100.1, 200.1, 254.1, 255.1]
# bounds = [0, 100.1, 107.1, 111.1, 237.1, 239.1, 250.1, 253.1, 255.1]
norm = mpl.colors.BoundaryNorm(bounds, mycolormap.N)
print (mycolormap.N)
img = np.ma.masked_where(img < 0 , img)
# cb = ax.scatter(lon, lat, marker = '.', c = value, s = 0.4, cmap = 'jet', lw = 0, norm = norm)
im = ax.imshow(img, origin = 'upper', cmap = mycolormap, norm = norm, extent = img_extent, transform = ccrs.PlateCarree())
# 标注坐标轴
ax.set_xticks([-180, -120, -60, 0, 60, 120, 180], crs = ccrs.PlateCarree())
ax.set_yticks([-90, -60, -30, 0, 30, 60, 90], crs = ccrs.PlateCarree())
# zero_direction_label用来设置经度的0度加不加E和W
lon_formatter = LongitudeFormatter(zero_direction_label = False)
lat_formatter = LatitudeFormatter()
ax.xaxis.set_major_formatter(lon_formatter)
ax.yaxis.set_major_formatter(lat_formatter)
ax.grid(linestyle = '--')
ax.tick_params(labelsize = 12)
pos1 = ax.get_position()
print (pos1)
ax2 = fig.add_axes([0.1275, 0.01, 0.77, 0.04]) # 距离左下的x,y,宽,高
# ax2 = fig.add_subplot(212)
ax2.set_xticks([])
ax2.set_yticks([])
ax.set_title('%s Daily Snow Extent %s' % (job_name, ymd), fontsize = 20)
# 取消colorbar上的刻度
# cb.set_ticks([])
# xpos = 0
# for i in range(0, 11):
# # text的xy是针对fig的xy
# xpos_step = 1 / 11
# xpos = i * xpos_step + 0.005
# ax2.text(xpos, 0.45, label_lst[i], color = color_lst[i], ha = 'left', va = 'center', fontsize = 6)
drawRects(ax2)
# 更改刻度位置 写入自定义内容，删除数值标记
# color_lst = ['灰色-丢线', '黄色-不确定', '淡粉-暗像元', '褐色-陆地', '蓝色-内陆水', '深蓝-海水', '白色-云', '青色-冰', '蓝绿-雪', '红褐-饱和', '黑色-无效']
# labels = np.arange(0, 12, 1)
# loc = labels + .5
# cb.set_ticks(loc)
# ax2.yaxis.set_tick_params(labelsize = 7)
# cb.set_ticklabels(color_lst)
# out_fig = r'D:\data\ndsi\global_map_10km.png'
# plt.savefig(out_fig, dpi = 300)
plt.savefig(outfig, dpi = 360)
# plt.show()
print('end')
def drawRects(ax):
'''
色标
'''
# divider = make_axes_locatable(ax)
# fig = ax.get_figure()
# ax2 = divider.append_axes("bottom", "2%", pad = "0.1%")
# fig.add_axes(ax2)
patches = []
# add a rectangle
x0 = 0.
y0 = 0.01
rectl = 0.0909 # 1/11
recth = 0.99
step = 0.
for i, eachkey in enumerate(color_lst_lab):
color_bar = color_lst_bar[i]
color_str = color_lst_lab[i]
rect = mpatches.Rectangle((x0, y0), rectl, recth, ec = 'k', fc = color_lst[eachkey], fill = True, lw = 0.3)
patches.append(rect)
ax.add_patch(rect)
strt = color_str
if eachkey in ['Night', 'No Data']:
x1 = x0 + (13 - len(eachkey)) / 250.
else:
x1 = x0 + (14 - len(eachkey)) / 250.
y1 = y0 + 0.4
# print(eachkey, len(eachkey))
# if eachkey.count(' ') == 2: # 3个单词加回车
# i = eachkey.rfind(' ')
# l = list(eachkey)
# l[i] = '\n'
# strt = ''.join(l)
# y1 = y1 - 0.5
# x1 = x0 + 13 - len(eachkey)
# plt.text(x1, y1, strt, color = color_bar, ha = 'left', va = 'center', fontsize = 6.5, FontWeight = 'bold')
plt.text(x1, y1, strt, color = color_bar, ha = 'left', va = 'center', fontsize = 11, weight = 'bold')
x0 = x0 + rectl + step
axis('off')
if __name__ == '__main__':
warnings.filterwarnings("ignore")
# 获取程序参数接口
ARGS = sys.argv[1:]
HELP_INFO = \
u"""
[arg1]：yaml_path
[example]： python app.py arg1
"""
if "-h" in ARGS:
print(HELP_INFO)
sys.exit(-1)
if len(ARGS) != 1:
print(HELP_INFO)
sys.exit(-1)
else:
ARG1 = ARGS[0]
# with time_block("ALL", switch=TIME_TEST):
main(ARG1)
if __name__ == '__main__':
pass