-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathsequencer.py
371 lines (310 loc) · 11.2 KB
/
sequencer.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
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
# -*- coding: utf-8 -*-
"""
Created on ~
@author: VinLes
"""
from funs.read_lab import read_lab
from funs.breadth import labyrinth_breadth
from funs.astr import labyrinth_astr
import matplotlib.pyplot as plt
import time
import numpy as np
import os
from PIL import Image
# import scipy.misc #-not woking in python 3.6>
from toimage import *
import gc
gc.enable()
# bread stand for breadth
def seq_it(mode='RGB', name='20x15.txt', alg='breadth'):
'''
this function works as follows:
it creates cells with colors chosen then it concatenates cells into stripes,and finally in concatenates stripes into images
row by row. For rgb for every image in the sequence it goes 3 times for 3 channels. That is why, there are so many loops int there!
Do not use pyplot functionality in here to save the pictures, it slows down enormously.
Args:
mode (str): RGB or Simple. It's better to use RGB. And it works ok. 3 channels, deeper resolution for cells
name (str): name of file with a labyrinth
alg (str): options {breadth, astr}
'''
print('Calculating ...')
lab = read_lab(name)
lab1 = read_lab(name)
lab2 = read_lab(name)
lab3 = read_lab(name)
path = [0, 0]
X, Y = 8, 8
if alg == 'breadth':
lab, path = labyrinth_breadth(x=X+1, y=Y+1, lab=lab, labcopy=lab1)
elif alg == 'astr':
lab, WAVE = labyrinth_astr(
x=X+1, y=Y+1, lab=lab, labcopy=lab3, LAB=lab2)
print('Prepareing aninmation ...')
if mode == 'RGB':
NW = None
print('Animating in RGB mode, it may take time. For larger data please consider to use SIMPLE mode:).\n\n ***')
if alg == 'breadth':
# Names of waves up to exit
NW = list(range(2, len(path)+2))
elif alg == 'astr':
NW = list(range(2, WAVE))
t = [0.01 for _ in range(10)]
tz = [t for _ in range(10)]
WALL = np.array(tz)
# empty cell custom field
EC = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0, 0],
[0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0],
[0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0],
[0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0],
[0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0],
[0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0],
[0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0],
[0, 0, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
# dictionary of colors
DC, DC1, DC2 = {}, {}, {}
def seq(lab, tocolor):
IMG = []
wall = 1
for row in lab:
tmp = []
for item in row:
if item in tocolor:
tmp.append(DC[item])
elif (item == wall):
tmp.append(WALL)
else:
tmp.append(EC)
IMG.append(tmp)
IMG1 = []
wall = 1
for row in lab:
tmp = []
for item in row:
if item in tocolor:
tmp.append(DC1[item])
elif (item == wall):
tmp.append(WALL)
else:
tmp.append(EC)
IMG1.append(tmp)
IMG2 = []
wall = 1
for row in lab:
tmp = []
for item in row:
if item in tocolor:
tmp.append(DC2[item])
elif (item == wall):
tmp.append(WALL)
else:
tmp.append(EC)
IMG2.append(tmp)
return IMG, IMG1, IMG2
IMAGES, IMAGES1, IMAGES2 = [], [], []
tocolor = []
for color in NW:
if color != 1:
tocolor.append(color)
DC[color] = (np.where(EC == 0.98, np.random.random(), EC))
DC1[color] = (np.where(EC == 0.98, np.random.random(), EC))
DC2[color] = (np.where(EC == 0.98, np.random.random(), EC))
IMG, IMG1, IMG2 = seq(lab, tocolor)
IMAGES.append(IMG)
IMAGES1.append(IMG1)
IMAGES2.append(IMG2)
####part 2 #####
I2, I3, I4 = [], [], []
for IMG in IMAGES:
STRIPES = []
for row in IMG:
STRIPE = []
for item in row:
# print(item.shape)
try:
STRIPE[0] = np.hstack((STRIPE[0], item))
except:
STRIPE = [item]
STRIPES.append(STRIPE[0])
IMG2 = []
for S in STRIPES:
try:
IMG2[0] = np.vstack((IMG2[0], S))
except Exception as e:
IMG2 = [S]
I2.append(IMG2)
for IMG in IMAGES1:
STRIPES = []
for row in IMG:
STRIPE = []
for item in row:
try:
STRIPE[0] = np.hstack((STRIPE[0], item))
except:
STRIPE = [item]
STRIPES.append(STRIPE[0])
IMG3 = []
for S in STRIPES:
try:
IMG3[0] = np.vstack((IMG3[0], S))
except Exception as e:
IMG3 = [S]
I3.append(IMG3)
for IMG in IMAGES2:
STRIPES = []
for row in IMG:
STRIPE = []
for item in row:
try:
STRIPE[0] = np.hstack((STRIPE[0], item))
except:
STRIPE = [item]
STRIPES.append(STRIPE[0])
IMG4 = []
for S in STRIPES:
try:
IMG4[0] = np.vstack((IMG4[0], S))
except Exception as e:
IMG4 = [S]
I4.append(IMG4)
#### part 3 ####
try:
os.makedirs('ANIM')
except:
pass
K = list(range(len(I2)))
for IMG2, IMG3, IMG4, k in zip(I2, I3, I4, K):
print('done ', k, 'of ', len(path), flush=True, end='\r')
IMG2[0] = np.stack((IMG2[0], IMG3[0], IMG4[0]), axis=2)
toimage(IMG2[0], cmin=0.0, cmax=1.0).save('ANIM/{}.png'.format(k))
elif mode == 'SIMPLE':
print('Animating in SIMPLE mode, it may also take time. For larger data please consider to use ANOTHER APP:)).\n\n ***')
NW = None
if alg == 'breadth':
# Names of waves up to exit
NW = list(range(2, len(path)+2))
elif alg == 'astr':
NW = list(range(2, np.max((np.unique(lab)))))
t = [0.01 for _ in range(2)]
tz = [t for _ in range(2)]
WALL = np.array(tz)
WALL = np.array([[0.01]])
# empty cell
EC = np.array([[0.98]])
# dictionary of colors
DC, DC1, DC2 = {}, {}, {}
def seq(lab, tocolor):
IMG = []
wall = 1
for row in lab:
tmp = []
for item in row:
if item in tocolor:
tmp.append(DC[item])
elif (item == wall):
tmp.append(WALL)
else:
tmp.append(EC)
IMG.append(tmp)
IMG1 = []
wall = 1
for row in lab:
tmp = []
for item in row:
if item in tocolor:
tmp.append(DC1[item])
elif (item == wall):
tmp.append(WALL)
else:
tmp.append(EC)
IMG1.append(tmp)
IMG2 = []
wall = 1
for row in lab:
tmp = []
for item in row:
if item in tocolor:
tmp.append(DC2[item])
elif (item == wall):
tmp.append(WALL)
else:
tmp.append(EC)
IMG2.append(tmp)
return IMG, IMG1, IMG2
IMAGES, IMAGES1, IMAGES2 = [], [], []
tocolor = []
for color in NW:
if color != 1:
tocolor.append(color)
DC[color] = (np.where(EC == 0.98, np.random.random(), EC))
DC1[color] = (np.where(EC == 0.98, np.random.random(), EC))
DC2[color] = (np.where(EC == 0.98, np.random.random(), EC))
IMG, IMG1, IMG2 = seq(lab, tocolor)
IMAGES.append(IMG)
IMAGES1.append(IMG1)
IMAGES2.append(IMG2)
####part 2 #####
I2, I3, I4 = [], [], []
for IMG in IMAGES:
STRIPES = []
for row in IMG:
STRIPE = []
for item in row:
# print(item.shape)
try:
STRIPE[0] = np.hstack((STRIPE[0], item))
except:
STRIPE = [item]
STRIPES.append(STRIPE[0])
IMG2 = []
for S in STRIPES:
try:
IMG2[0] = np.vstack((IMG2[0], S))
except Exception as e:
IMG2 = [S]
I2.append(IMG2)
for IMG in IMAGES1:
STRIPES = []
for row in IMG:
STRIPE = []
for item in row:
try:
STRIPE[0] = np.hstack((STRIPE[0], item))
except:
STRIPE = [item]
STRIPES.append(STRIPE[0])
IMG3 = []
for S in STRIPES:
try:
IMG3[0] = np.vstack((IMG3[0], S))
except Exception as e:
IMG3 = [S]
I3.append(IMG3)
for IMG in IMAGES2:
STRIPES = []
for row in IMG:
STRIPE = []
for item in row:
try:
STRIPE[0] = np.hstack((STRIPE[0], item))
except:
STRIPE = [item]
STRIPES.append(STRIPE[0])
IMG4 = []
for S in STRIPES:
try:
IMG4[0] = np.vstack((IMG4[0], S))
except Exception as e:
IMG4 = [S]
I4.append(IMG4)
#### part 3 ####
try:
os.makedirs('ANIM')
except:
pass
K = list(range(len(I2)))
for IMG2, IMG3, IMG4, k in zip(I2, I3, I4, K):
print('done ', k, 'of ', len(path), flush=True, end='\r')
IMG2[0] = np.stack((IMG2[0], IMG3[0], IMG4[0]), axis=2)
toimage(IMG2[0], cmin=0.0, cmax=1.0).save('ANIM/{}.png'.format(k))