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10 | 10 | "from spm import * \n",
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11 | 11 | "\n",
|
12 | 12 | "import numpy as np\n",
|
13 |
| - "import os.path as op\n", |
14 |
| - "import os \n", |
15 |
| - "import scipy.io as sio" |
| 13 | + "import os.path as op" |
16 | 14 | ]
|
17 | 15 | },
|
18 | 16 | {
|
|
120 | 118 | "source": [
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121 | 119 | "DCM = Struct() \n",
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122 | 120 | "\n",
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123 |
| - "xY1 = Runtime.call('load', op.join(data_path,'GLM','VOI_V1_1.mat'))['xY'];\n", |
124 |
| - "xY2 = Runtime.call('load', op.join(data_path,'GLM','VOI_V5_1.mat'))['xY'];\n", |
125 |
| - "xY3 = Runtime.call('load', op.join(data_path,'GLM','VOI_SPC_1.mat'))['xY'];\n", |
| 121 | + "xY1 = Runtime.call('load', op.join(data_path,'GLM','VOI_V1_1.mat'))['xY']\n", |
| 122 | + "xY2 = Runtime.call('load', op.join(data_path,'GLM','VOI_V5_1.mat'))['xY']\n", |
| 123 | + "xY3 = Runtime.call('load', op.join(data_path,'GLM','VOI_SPC_1.mat'))['xY']\n", |
126 | 124 | "\n",
|
127 | 125 | "DCM.xY = StructArray(xY1, xY2, xY3)"
|
128 | 126 | ]
|
|
134 | 132 | "metadata": {},
|
135 | 133 | "outputs": [],
|
136 | 134 | "source": [
|
137 |
| - "DCM.n = 3; \n", |
| 135 | + "DCM.n = 3 \n", |
138 | 136 | "DCM.v = xY1['u'].shape[0]; "
|
139 | 137 | ]
|
140 | 138 | },
|
|
165 | 163 | "outputs": [],
|
166 | 164 | "source": [
|
167 | 165 | "DCM.Y = Struct()\n",
|
168 |
| - "DCM.Y.dt = SPM.xY.RT;\n", |
169 |
| - "DCM.Y.X0 = xY1.X0;\n", |
| 166 | + "DCM.Y.dt = SPM.xY.RT\n", |
| 167 | + "DCM.Y.X0 = xY1.X0\n", |
170 | 168 | "\n",
|
171 | 169 | "DCM.Y.y = np.concatenate([xY.u for xY in (xY1, xY2, xY3)], axis=1)\n",
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172 | 170 | "DCM.Y.name = [xY.name for xY in (xY1, xY2, xY3)]\n",
|
|
198 | 196 | "outputs": [],
|
199 | 197 | "source": [
|
200 | 198 | "DCM.U = Struct()\n",
|
201 |
| - "DCM.U.dt = SPM.Sess.U[0].dt;\n", |
202 |
| - "DCM.U.name = [u.name for u in SPM.Sess.U];\n", |
| 199 | + "DCM.U.dt = SPM.Sess.U[0].dt\n", |
| 200 | + "DCM.U.name = [u.name for u in SPM.Sess.U]\n", |
203 | 201 | "DCM.U.u = np.concatenate([\n",
|
204 | 202 | " u.u[32:] for u in SPM.Sess.U\n",
|
205 | 203 | " ], axis=1);"
|
|
230 | 228 | "metadata": {},
|
231 | 229 | "outputs": [],
|
232 | 230 | "source": [
|
233 |
| - "DCM.delays = np.repeat([[SPM['xY']['RT']/2]], DCM.n, 1);\n", |
234 |
| - "DCM.TE = 0.04;\n", |
| 231 | + "DCM.delays = np.repeat([[SPM['xY']['RT']/2]], DCM.n, 1)\n", |
| 232 | + "DCM.TE = 0.04\n", |
235 | 233 | "\n",
|
236 | 234 | "DCM.options = Struct()\n",
|
237 |
| - "DCM.options.nonlinear = 0;\n", |
238 |
| - "DCM.options.two_state = 0;\n", |
239 |
| - "DCM.options.stochastic = 0;\n", |
| 235 | + "DCM.options.nonlinear = 0\n", |
| 236 | + "DCM.options.two_state = 0\n", |
| 237 | + "DCM.options.stochastic = 0\n", |
240 | 238 | "DCM.options.nograph = 1;"
|
241 | 239 | ]
|
242 | 240 | },
|
|
265 | 263 | "outputs": [],
|
266 | 264 | "source": [
|
267 | 265 | "DCM.a = np.array([[1, 1, 0], [1, 1, 1], [0, 1, 1]])\n",
|
268 |
| - "DCM.b = np.zeros((3,3,3)); \n", |
269 |
| - "DCM.b[1,0,1] = 1; \n", |
270 |
| - "DCM.b[1,2,2] = 1;\n", |
| 266 | + "DCM.b = np.zeros((3,3,3)) \n", |
| 267 | + "DCM.b[1,0,1] = 1 \n", |
| 268 | + "DCM.b[1,2,2] = 1\n", |
271 | 269 | "DCM.c = np.array([[1, 0, 0], [0, 0, 0], [0, 0, 0]])\n",
|
272 |
| - "DCM.d = np.zeros((3,3,0));\n", |
| 270 | + "DCM.d = np.zeros((3,3,0))\n", |
273 | 271 | "\n",
|
274 | 272 | "DCMbwd = spm_dcm_estimate(DCM)"
|
275 | 273 | ]
|
|
295 | 293 | "metadata": {},
|
296 | 294 | "outputs": [],
|
297 | 295 | "source": [
|
298 |
| - "DCM.b = np.zeros((3,3,3)); \n", |
299 |
| - "DCM.b[1,0,1] = 1; \n", |
300 |
| - "DCM.b[1,0,2] = 1;\n", |
| 296 | + "DCM.b = np.zeros((3,3,3)) \n", |
| 297 | + "DCM.b[1,0,1] = 1 \n", |
| 298 | + "DCM.b[1,0,2] = 1\n", |
301 | 299 | "\n",
|
302 | 300 | "DCMfwd = spm_dcm_estimate(DCM)"
|
303 | 301 | ]
|
|
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