-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathinspect_variables_cut.py
executable file
·151 lines (115 loc) · 5.26 KB
/
inspect_variables_cut.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
########################################################################################
"""
File allowing the inspection of variables from pickles
"""
########################################################################################
import pickle
import numpy as np
from plot import create_animated_output
# save_directory = 'results/100cells/'
# save_directory = 'results/**_asymmetric_cut/remove_35L_24R/'
# save_directory = 'results/**_intact_embryo/'
# save_directory = 'results/study_calcium/D_50/'
# save_directory = 'results/vary_params_2023/beta_V_2_19/'
save_directory = 'results/vary_params_2023/standard_cut/'
number_of_cells = 100
########################################################################################
""" Pickle variables """
pickle_directory = save_directory + 'vars/'
t = pickle.load( open(pickle_directory + 't.p','rb') )
a = pickle.load( open(pickle_directory + 'a.p','rb') )
b = pickle.load( open(pickle_directory + 'b.p','rb') )
c = pickle.load( open(pickle_directory + 'c.p','rb') )
v = pickle.load( open(pickle_directory + 'v.p','rb') )
########################################################################################
print("")
print("Basic time data")
print(t.shape)
print(t[0],t[-1])
timepoint_N = t.shape[0]
########################################################################################
print("")
print("Check time scaling")
time_scaling = int((t.shape[0]-1) / (c.shape[1]-1))
print(time_scaling)
########################################################################################
print("")
print("Find time of cut")
cut_time_idx = 0
while all(i >= 0 for i in c[:,cut_time_idx]):
cut_time_idx += 1
# print(cut_time_idx - 1, t[cut_time_idx - 1])
# print(t[cut_time_idx - 1], c[:,cut_time_idx - 1])
# print(t[cut_time_idx], c[:,cut_time_idx])
########################################################################################
print("")
print("Find shape after cut")
bool_cells_after_cut = c[:,cut_time_idx]>=0
idx_cells_after_cut = [i for i, x in enumerate(bool_cells_after_cut) if x]
cells_after_cut_N = sum(bool_cells_after_cut)
print(cells_after_cut_N)
print(min(bool_cells_after_cut * c[:,cut_time_idx]))
########################################################################################
print("")
print("Calcium data")
print("Min max just precut", min(c[:,cut_time_idx-1]), max(c[:,cut_time_idx-1]))
c_at_end = [c[idx, -1] for idx in idx_cells_after_cut]
print("Min max end,", min(c_at_end), max(c_at_end))
print('calcium cell 34 35 36 74 75 76', c[34, -1], c[35, -1], c[36, -1], c[74, -1], c[75, -1], c[76, -1])
########################################################################################
print("")
print("When does calcium come on precut?")
temp_c = 0
t_idx_counter = 0
while temp_c == 0:
temp_c = np.max(c[:,t_idx_counter])
t_idx_counter += 1
print(t_idx_counter, t[t_idx_counter]*time_scaling)
ca_on_idx = t_idx_counter
ca_zero_idx = ca_on_idx - 1
########################################################################################
print("")
print("Does calcium reach equilibrium precut?")
print("Min max just precut minus 1", min(c[:,cut_time_idx-2]), max(c[:,cut_time_idx-2]))
print("Min max just precut", min(c[:,cut_time_idx-1]), max(c[:,cut_time_idx-1]))
print("Precut bool, ", min(c[:,cut_time_idx-2]) == min(c[:,cut_time_idx-1]), max(c[:,cut_time_idx-2]) == max(c[:,cut_time_idx-1]))
########################################################################################
print("")
print("Does calcium reach equilibrium postcut?")
c_at_end_minus_1 = [c[idx, -2] for idx in idx_cells_after_cut]
print("Min max end minus 1", min(c_at_end_minus_1), max(c_at_end_minus_1))
print("Min max end", min(c_at_end), max(c_at_end))
print("End bool, ", min(c_at_end_minus_1) == min(c_at_end), max(c_at_end_minus_1) == max(c_at_end))
########################################################################################
print("")
print("When does calcium reach equilibrium postcut?")
max_c = max(c_at_end)
temp_max_c = 0
t_idx_counter_max = 0
while temp_max_c < max_c:
temp_max_c = np.max(c[:,t_idx_counter_max])
t_idx_counter_max += 1
print(t_idx_counter_max, t[t_idx_counter_max]*time_scaling)
########################################################################################
print("")
print("Verify calcium reached equilibrium postcut")
t_idx = t_idx_counter_max - 2
print('Time')
print(t_idx, t[t_idx])
print(t_idx+1, t[t_idx+1])
print(t_idx+2, t[t_idx+2])
print('\nCalcium')
left_cell_post_cut = min(idx_cells_after_cut)
right_cell_post_cut = max(idx_cells_after_cut)
print(c[left_cell_post_cut, t_idx], c[right_cell_post_cut, t_idx])
print(c[left_cell_post_cut, t_idx+1], c[right_cell_post_cut, t_idx+1])
print(c[left_cell_post_cut, t_idx+2], c[right_cell_post_cut, t_idx+2])
########################################################################################
print("\nTotal calcium in the system at pre cut")
print(np.sum(c[:,cut_time_idx-1]))
print("\nTotal calcium in the system at equilibrium post cut")
print(np.sum(c_at_end))
########################################################################################
print("\nBMP and Vg1 min and max at end")
print("BMP ", b[left_cell_post_cut, -1], b[right_cell_post_cut, -1])
print("Vg1 ", v[left_cell_post_cut, -1], v[right_cell_post_cut, -1])