MultiCompartmentModel/dataCol.py at master · annikc/MultiCompartmentModel · GitHub

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
'''
Some .dat files missing; resync with SciNet and/or rerun files (move data fom scratch folder permanently)
soma[where syn were present] contains timesteps {-50, -25 ... }
	timesteps[delta t values] contains section lists {soma / prox / mid / dist}
		section lists[soma/prox/midd/dist] contains individual sections i.e. in prox{dend[0], dend[1] ...}
			sections[dend[i], etc] contains vectors of data
'''
from readNRNdata import *

##############################################
# Read in Data
##############################################
# Set up vector of STDP spike timing interval values used during data collection
timesteps = np.array([-50, -25, -15, -10, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 10, 15, 25, 50])

# set up vector of dendrites in sectionlists Proximal, middle, and distal
prox_seclist = np.array([0, 1, 2, 3, 5, 6, 7, 8, 9, 29, 42, 43, 44, 45, 46, 47, 54, 56])
midd_seclist = np.array([4, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 48, 49, 50, 51, 52, 53, 55, 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, 139, 140, 141, 142, 147, 150, 151, 154, 155, 156, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 174, 175, 176, 177, 178, 179])
dist_seclist = np.array([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, 143, 144, 145, 146, 148, 149, 152, 153, 157, 158, 173])

# set up lists for storing read data
soma_syn = []
prox_syn = []
midd_syn = []
dist_syn = []

for i in range(len(timesteps)):
	soma_syn.append(nrnReader("./data/coarseExpts/soma_{0}.dat".format(timesteps[i])))
	prox_syn.append(nrnReader("./data/coarseExpts/proximal_{0}.dat".format(timesteps[i])))
	midd_syn.append(nrnReader("./data/coarseExpts/middle_{0}.dat".format(timesteps[i])))
	dist_syn.append(nrnReader("./data/coarseExpts/distal_{0}.dat".format(timesteps[i])))

num_var = soma_syn[0].num_variables


# Set up dictionaries for organizing imported data, based on where synaptic connections were present during data collection
somatic_list = dict()
proximal_list = dict()
middle_list = dict()
distal_list = dict()

for i in range(len(timesteps)):
	## SYNAPSES INSERTED IN SOMA
	somatic_list["delta_{0}".format(timesteps[i])] = dict()
	# Dictionaries of data recorded from each area of the cell
	somatic_list["delta_{0}".format(timesteps[i])]["soma"] = dict()
	somatic_list["delta_{0}".format(timesteps[i])]["prox"] = dict()
	somatic_list["delta_{0}".format(timesteps[i])]["midd"] = dict()
	somatic_list["delta_{0}".format(timesteps[i])]["dist"] = dict()

	# add data to dictionaries
	somatic_list["delta_{0}".format(timesteps[i])]["soma"]["soma"] = []
	for k in range(num_var):
		somatic_list["delta_{0}".format(timesteps[i])]["soma"]["soma"].append(soma_syn[i].var_list.varList[k].secList[0][0]) ### what is the seclist[1]?????/not working with index 0 which should be soma

	for j in range(len(prox_seclist)):
		somatic_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])] = []
		for k in range(num_var):
			somatic_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])].append(soma_syn[i].var_list.varList[k].secList[1][j])

	for j in range(len(midd_seclist)):
		somatic_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])] = []
		for k in range(num_var):
			somatic_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])].append(soma_syn[i].var_list.varList[k].secList[2][j])

	for j in range(len(dist_seclist)):
		somatic_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])] = []
		for k in range(num_var):
			somatic_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])].append(soma_syn[i].var_list.varList[k].secList[3][j])

	## SYNAPSES INSERTED IN PROXIMAL DENDRITES
	proximal_list["delta_{0}".format(timesteps[i])] = dict()
	# Dictionaries of data recorded from each area of the cell
	proximal_list["delta_{0}".format(timesteps[i])]["soma"] = dict()
	proximal_list["delta_{0}".format(timesteps[i])]["prox"] = dict()
	proximal_list["delta_{0}".format(timesteps[i])]["midd"] = dict()
	proximal_list["delta_{0}".format(timesteps[i])]["dist"] = dict()

	# add data to dictionaries
	proximal_list["delta_{0}".format(timesteps[i])]["soma"]["soma"] = []
	for k in range(num_var):
		proximal_list["delta_{0}".format(timesteps[i])]["soma"]["soma"].append(prox_syn[i].var_list.varList[k].secList[0][0]) ### what is the seclist[1]?????/not working with index 0 which should be soma

	for j in range(len(prox_seclist)):
		proximal_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])] = []
		for k in range(num_var):
			proximal_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])].append(prox_syn[i].var_list.varList[k].secList[1][j])

	for j in range(len(midd_seclist)):
		proximal_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])] = []
		for k in range(num_var):
			proximal_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])].append(prox_syn[i].var_list.varList[k].secList[2][j])

	for j in range(len(dist_seclist)):
		proximal_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])] = []
		for k in range(num_var):
			proximal_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])].append(prox_syn[i].var_list.varList[k].secList[3][j])

	## SYNAPSES INSERTED IN MIDDLE DENDRITES
	middle_list["delta_{0}".format(timesteps[i])] = dict()
	# Dictionaries of data recorded from each area of the cell
	middle_list["delta_{0}".format(timesteps[i])]["soma"] = dict()
	middle_list["delta_{0}".format(timesteps[i])]["prox"] = dict()
	middle_list["delta_{0}".format(timesteps[i])]["midd"] = dict()
	middle_list["delta_{0}".format(timesteps[i])]["dist"] = dict()

	# add data to dictionaries
	middle_list["delta_{0}".format(timesteps[i])]["soma"]["soma"] = []
	for k in range(num_var):
		middle_list["delta_{0}".format(timesteps[i])]["soma"]["soma"].append(midd_syn[i].var_list.varList[k].secList[0][0]) ### what is the seclist[1]?????/not working with index 0 which should be soma

	for j in range(len(prox_seclist)):
		middle_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])] = []
		for k in range(num_var):
			middle_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])].append(midd_syn[i].var_list.varList[k].secList[1][j])

	for j in range(len(midd_seclist)):
		middle_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])] = []
		for k in range(num_var):
			middle_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])].append(midd_syn[i].var_list.varList[k].secList[2][j])

	for j in range(len(dist_seclist)):
		middle_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])] = []
		for k in range(num_var):
			middle_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])].append(midd_syn[i].var_list.varList[k].secList[3][j])


#print middle_list["delta_-50"]["prox"].keys()
	## SYNAPSES INSERTED IN DISTAL DENDRITES
	distal_list["delta_{0}".format(timesteps[i])] = dict()
	# Dictionaries of data recorded from each area of the cell
	distal_list["delta_{0}".format(timesteps[i])]["soma"] = dict()
	distal_list["delta_{0}".format(timesteps[i])]["prox"] = dict()
	distal_list["delta_{0}".format(timesteps[i])]["midd"] = dict()
	distal_list["delta_{0}".format(timesteps[i])]["dist"] = dict()

	# add data to dictionaries
	distal_list["delta_{0}".format(timesteps[i])]["soma"]["soma"] = []
	for k in range(num_var):
		distal_list["delta_{0}".format(timesteps[i])]["soma"]["soma"].append(dist_syn[i].var_list.varList[k].secList[0][0]) ### what is the seclist[1]?????/not working with index 0 which should be soma

	for j in range(len(prox_seclist)):
		distal_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])] = []
		for k in range(num_var):
			distal_list["delta_{0}".format(timesteps[i])]["prox"]["dend_{0}".format(prox_seclist[j])].append(dist_syn[i].var_list.varList[k].secList[1][j])

	for j in range(len(midd_seclist)):
		distal_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])] = []
		for k in range(num_var):
			distal_list["delta_{0}".format(timesteps[i])]["midd"]["dend_{0}".format(midd_seclist[j])].append(dist_syn[i].var_list.varList[k].secList[2][j])

	for j in range(len(dist_seclist)):
		distal_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])] = []
		for k in range(num_var):
			distal_list["delta_{0}".format(timesteps[i])]["dist"]["dend_{0}".format(dist_seclist[j])].append(dist_syn[i].var_list.varList[k].secList[3][j])


###########################################
# Cl Reversal Potential
###########################################

soma_ecl = np.zeros(len(timesteps))
prox_ecl = np.zeros(len(timesteps))
midd_ecl = np.zeros(len(timesteps))
dist_ecl = np.zeros(len(timesteps))

for i in range(len(timesteps)):
	soma_ecl[i] = soma_syn[i].var_list.varList[0].secList[0]
	prox_ecl[i] = prox_syn[i].var_list.varList[0].secList[1][0]  #<name of file read in>.<list of variables>[Ecl=0/KCC2=1/Ca=2/Kin=3/phos=4].<list of sections>[soma=0/prox=1/midd=2/dist=3]
	##### NOTE: secList indices 1,2,3 contain vectors with recordings from all sections ... how do we want to organize this data?
	midd_ecl[i] = midd_syn[i].var_list.varList[0].secList[2][0]
	dist_ecl[i] = dist_syn[i].var_list.varList[0].secList[3][0]

###########################################
# Membrane Phosphorylated KCC2 (proportion)
###########################################
soma_MP = np.zeros(len(timesteps))
prox_MP = np.zeros(len(timesteps))
midd_MP = np.zeros(len(timesteps))
dist_MP = np.zeros(len(timesteps))

for i in range(len(timesteps)):
	soma_MP[i] = soma_syn[i].var_list.varList[1].secList[0]
	prox_MP[i] = prox_syn[i].var_list.varList[1].secList[1]  #<name of file read in>.<list of variables>[Ecl=0/KCC2=1/Ca=2/Kin=3/phos=4].<list of sections>[soma=0/prox=1/midd=2/dist=3]
	midd_MP[i] = midd_syn[i].var_list.varList[1].secList[2]
	dist_MP[i] = dist_syn[i].var_list.varList[1].secList[3]


###########################################
# Calcium Concentration
###########################################
soma_cal = np.zeros(len(timesteps))
prox_cal = np.zeros(len(timesteps))
midd_cal = np.zeros(len(timesteps))
dist_cal = np.zeros(len(timesteps))

for i in range(len(timesteps)):
	soma_cal[i] = soma_syn[i].var_list.varList[1].secList[0]
	prox_cal[i] = prox_syn[i].var_list.varList[1].secList[1]  #<name of file read in>.<list of variables>[Ecl=0/KCC2=1/Ca=2/Kin=3/phos=4].<list of sections>[soma=0/prox=1/midd=2/dist=3]
	midd_cal[i] = midd_syn[i].var_list.varList[1].secList[2]
	dist_cal[i] = dist_syn[i].var_list.varList[1].secList[3]

###########################################
# Active Kinase (proportion)
###########################################
soma_kin = np.zeros(len(timesteps))
prox_kin = np.zeros(len(timesteps))
midd_kin = np.zeros(len(timesteps))
dist_kin = np.zeros(len(timesteps))

for i in range(len(timesteps)):
	soma_kin[i] = soma_syn[i].var_list.varList[1].secList[0]
	prox_kin[i] = prox_syn[i].var_list.varList[1].secList[1]  #<name of file read in>.<list of variables>[Ecl=0/KCC2=1/Ca=2/Kin=3/phos=4].<list of sections>[soma=0/prox=1/midd=2/dist=3]
	midd_kin[i] = midd_syn[i].var_list.varList[1].secList[2]
	dist_kin[i] = dist_syn[i].var_list.varList[1].secList[3]

###########################################
# Active Phosphatase (proportion)
###########################################
soma_phos = np.zeros(len(timesteps))
prox_phos = np.zeros(len(timesteps))
midd_phos = np.zeros(len(timesteps))
dist_phos = np.zeros(len(timesteps))

for i in range(len(timesteps)):
	soma_phos[i] = soma_syn[i].var_list.varList[1].secList[0]
	prox_phos[i] = prox_syn[i].var_list.varList[1].secList[1]  #<name of file read in>.<list of variables>[Ecl=0/KCC2=1/Ca=2/Kin=3/phos=4].<list of sections>[soma=0/prox=1/midd=2/dist=3]
	midd_phos[i] = midd_syn[i].var_list.varList[1].secList[2]
	dist_phos[i] = dist_syn[i].var_list.varList[1].secList[3]