[enh] regenerate code with external mpython package

Author: johmedr

.mpython/templates/setup.py

@@ -10,9 +10,7 @@
     "from spm import * \n",
     "\n",
     "import numpy as np\n",
-    "import os.path as op\n",
-    "import os \n",
-    "import scipy.io as sio"
+    "import os.path as op"
    ]
   },
   {
@@ -120,9 +118,9 @@
    "source": [
     "DCM = Struct() \n",
     "\n",
-    "xY1 = Runtime.call('load', op.join(data_path,'GLM','VOI_V1_1.mat'))['xY'];\n",
-    "xY2 = Runtime.call('load', op.join(data_path,'GLM','VOI_V5_1.mat'))['xY'];\n",
-    "xY3 = Runtime.call('load', op.join(data_path,'GLM','VOI_SPC_1.mat'))['xY'];\n",
+    "xY1 = Runtime.call('load', op.join(data_path,'GLM','VOI_V1_1.mat'))['xY']\n",
+    "xY2 = Runtime.call('load', op.join(data_path,'GLM','VOI_V5_1.mat'))['xY']\n",
+    "xY3 = Runtime.call('load', op.join(data_path,'GLM','VOI_SPC_1.mat'))['xY']\n",
     "\n",
     "DCM.xY = StructArray(xY1, xY2, xY3)"
    ]
@@ -134,7 +132,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "DCM.n = 3;     \n",
+    "DCM.n = 3     \n",
     "DCM.v = xY1['u'].shape[0]; "
    ]
   },
@@ -165,8 +163,8 @@
    "outputs": [],
    "source": [
     "DCM.Y = Struct()\n",
-    "DCM.Y.dt  = SPM.xY.RT;\n",
-    "DCM.Y.X0  = xY1.X0;\n",
+    "DCM.Y.dt  = SPM.xY.RT\n",
+    "DCM.Y.X0  = xY1.X0\n",
     "\n",
     "DCM.Y.y = np.concatenate([xY.u for xY in (xY1, xY2, xY3)], axis=1)\n",
     "DCM.Y.name = [xY.name for xY in  (xY1, xY2, xY3)]\n",
@@ -198,8 +196,8 @@
    "outputs": [],
    "source": [
     "DCM.U = Struct()\n",
-    "DCM.U.dt   =  SPM.Sess.U[0].dt;\n",
-    "DCM.U.name = [u.name for u in SPM.Sess.U];\n",
+    "DCM.U.dt   =  SPM.Sess.U[0].dt\n",
+    "DCM.U.name = [u.name for u in SPM.Sess.U]\n",
     "DCM.U.u    = np.concatenate([\n",
     "        u.u[32:] for u in SPM.Sess.U\n",
     "    ], axis=1);"
@@ -230,13 +228,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "DCM.delays = np.repeat([[SPM['xY']['RT']/2]], DCM.n, 1);\n",
-    "DCM.TE     = 0.04;\n",
+    "DCM.delays = np.repeat([[SPM['xY']['RT']/2]], DCM.n, 1)\n",
+    "DCM.TE     = 0.04\n",
     "\n",
     "DCM.options = Struct()\n",
-    "DCM.options.nonlinear  = 0;\n",
-    "DCM.options.two_state  = 0;\n",
-    "DCM.options.stochastic = 0;\n",
+    "DCM.options.nonlinear  = 0\n",
+    "DCM.options.two_state  = 0\n",
+    "DCM.options.stochastic = 0\n",
     "DCM.options.nograph    = 1;"
    ]
   },
@@ -265,11 +263,11 @@
    "outputs": [],
    "source": [
     "DCM.a = np.array([[1, 1, 0], [1, 1, 1], [0, 1, 1]])\n",
-    "DCM.b = np.zeros((3,3,3));  \n",
-    "DCM.b[1,0,1] = 1;  \n",
-    "DCM.b[1,2,2] = 1;\n",
+    "DCM.b = np.zeros((3,3,3))  \n",
+    "DCM.b[1,0,1] = 1  \n",
+    "DCM.b[1,2,2] = 1\n",
     "DCM.c = np.array([[1, 0, 0], [0, 0, 0], [0, 0, 0]])\n",
-    "DCM.d = np.zeros((3,3,0));\n",
+    "DCM.d = np.zeros((3,3,0))\n",
     "\n",
     "DCMbwd = spm_dcm_estimate(DCM)"
    ]
@@ -295,9 +293,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "DCM.b = np.zeros((3,3,3));  \n",
-    "DCM.b[1,0,1] = 1;  \n",
-    "DCM.b[1,0,2] = 1;\n",
+    "DCM.b = np.zeros((3,3,3))  \n",
+    "DCM.b[1,0,1] = 1  \n",
+    "DCM.b[1,0,2] = 1\n",
     "\n",
     "DCMfwd = spm_dcm_estimate(DCM)"
    ]

examples/DCM_fMRI_Attention.ipynb

@@ -59,11 +59,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "a      = .9;\n",
-    "A1 = np.array([[.5, .5], [.5, .5], [0, 0], [0, 0]]);\n",
-    "A2 = np.array([[0, 0], [0, 0], [a, (1 - a)], [(1 - a), a]]);\n",
-    "A3 = np.array([[0, 0], [0, 0], [(1 - a), a], [a, (1 - a)]]);\n",
-    "A4 = np.array([[1, 0], [0, 1], [0, 0], [0, 0]]);\n",
+    "a      = .9\n",
+    "A1 = np.array([[.5, .5], [.5, .5], [0, 0], [0, 0]])\n",
+    "A2 = np.array([[0, 0], [0, 0], [a, (1 - a)], [(1 - a), a]])\n",
+    "A3 = np.array([[0, 0], [0, 0], [(1 - a), a], [a, (1 - a)]])\n",
+    "A4 = np.array([[1, 0], [0, 1], [0, 0], [0, 0]])\n",
     "A = block_diag(A1, A2, A3, A4);"
    ]
   },
@@ -94,10 +94,10 @@
     "B = [[]]*4\n",
     "i = 0\n",
     "for i, _ in enumerate(B):\n",
-    "    B[i] = np.zeros((4,4));\n",
-    "    B[i][1:3, 1:3] = np.eye(2);\n",
-    "    B[i][i,[0, 3]]  = 1;\n",
-    "    B[i] = np.kron(B[i],np.eye(2));"
+    "    B[i] = np.zeros((4,4))\n",
+    "    B[i][1:3, 1:3] = np.eye(2)\n",
+    "    B[i][i,[0, 3]]  = 1\n",
+    "    B[i] = np.kron(B[i],np.eye(2))"
    ]
   },
   {
@@ -178,16 +178,16 @@
    "source": [
     "MDP = Struct()\n",
     "\n",
-    "MDP.N = 8;                          # number of variational iterations\n",
-    "MDP.S = S;                          # true initial state\n",
-    "MDP.A = A;                          # observation model\n",
-    "MDP.B = B;                          # transition probabilities (priors)\n",
-    "MDP.C = C;                          # terminal cost probabilities (priors)\n",
-    "MDP.D = D;                          # initial state probabilities (priors)\n",
-    "MDP.V = V;                          # allowable policies\n",
+    "MDP.N = 8                          # number of variational iterations\n",
+    "MDP.S = S                          # true initial state\n",
+    "MDP.A = A                          # observation model\n",
+    "MDP.B = B                          # transition probabilities (priors)\n",
+    "MDP.C = C                          # terminal cost probabilities (priors)\n",
+    "MDP.D = D                          # initial state probabilities (priors)\n",
+    "MDP.V = V                          # allowable policies\n",
     "\n",
-    "MDP.alpha  = 64;                    # gamma hyperparameter\n",
-    "MDP.beta   = 4;                     # gamma hyperparameter\n",
+    "MDP.alpha  = 64                    # gamma hyperparameter\n",
+    "MDP.beta   = 4                     # gamma hyperparameter\n",
     "MDP['lambda'] = 0.25                   # precision update rate"
    ]
   },

examples/DEM_demo_Maze.ipynb

@@ -85,48 +85,48 @@
    "source": [
     "#- read data \n",
     "#--------------------------------------------------------------------------\n",
-    "S = Struct();\n",
-    "S.data = op.join(datapath, 'OPM_meg_001.cMEG');\n",
-    "S.positions = op.join(datapath, 'OPM_HelmConfig.tsv');\n",
-    "D = spm_opm_create(S);\n",
+    "S = Struct()\n",
+    "S.data = op.join(datapath, 'OPM_meg_001.cMEG')\n",
+    "S.positions = op.join(datapath, 'OPM_HelmConfig.tsv')\n",
+    "D = spm_opm_create(S)\n",
     "\n",
     "#- highpass\n",
     "#--------------------------------------------------------------------------\n",
-    "S = Struct();\n",
-    "S.D = D;\n",
-    "S.freq = 10;\n",
-    "S.band = 'high';\n",
-    "fD = spm_eeg_ffilter(S);\n",
-    "fr = S.freq;\n",
+    "S = Struct()\n",
+    "S.D = D\n",
+    "S.freq = 10\n",
+    "S.band = 'high'\n",
+    "fD = spm_eeg_ffilter(S)\n",
+    "fr = S.freq\n",
     "\n",
     "#- lowpass\n",
     "#--------------------------------------------------------------------------\n",
-    "S = Struct();\n",
-    "S.D = fD;\n",
-    "S.freq = 70;\n",
-    "S.band = 'low';\n",
-    "fD = spm_eeg_ffilter(S);\n",
+    "S = Struct()\n",
+    "S.D = fD\n",
+    "S.freq = 70\n",
+    "S.band = 'low'\n",
+    "fD = spm_eeg_ffilter(S)\n",
     "\n",
     "#- adaptive multipole models\n",
     "#--------------------------------------------------------------------------\n",
-    "S = Struct();\n",
-    "S.D = fD;\n",
-    "S.corrLim = .98;\n",
-    "mD = spm_opm_amm(S);\n",
+    "S = Struct()\n",
+    "S.D = fD\n",
+    "S.corrLim = .98\n",
+    "mD = spm_opm_amm(S)\n",
     "\n",
     "#- epoch \n",
     "#--------------------------------------------------------------------------\n",
-    "S = Struct();\n",
-    "S.D = mD;\n",
-    "S.timewin = np.array([-50, 200]);\n",
-    "S.triggerChannels = {'Trigger 6 Z'};\n",
-    "eD = spm_opm_epoch_trigger(S);\n",
+    "S = Struct()\n",
+    "S.D = mD\n",
+    "S.timewin = np.array([-50, 200])\n",
+    "S.triggerChannels = {'Trigger 6 Z'}\n",
+    "eD = spm_opm_epoch_trigger(S)\n",
     "\n",
     "#- baseline correction \n",
     "#--------------------------------------------------------------------------\n",
-    "S = Struct();\n",
-    "S.D = eD;\n",
-    "S.timewin = np.array([-50, 0]);\n",
+    "S = Struct()\n",
+    "S.D = eD\n",
+    "S.timewin = np.array([-50, 0])\n",
     "eD = spm_eeg_bc(S);"
    ]
   },
@@ -171,9 +171,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "S = Struct();\n",
-    "S.D = eD;\n",
-    "S.headfile = op.join(datapath, 'head.obj');\n",
+    "S = Struct()\n",
+    "S.D = eD\n",
+    "S.headfile = op.join(datapath, 'head.obj')\n",
     "\n",
     "S.helmetref = np.array(\n",
     "     [[0,133.9,-24],  \n",
@@ -220,10 +220,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "S = Struct();\n",
-    "S.dir = datapath;\n",
-    "S.D = eD.fullfile();\n",
-    "S.space = 'Head';\n",
+    "S = Struct()\n",
+    "S.dir = datapath\n",
+    "S.D = eD.fullfile()\n",
+    "S.space = 'Head'\n",
     "BF = bf_wizard_data(S);"
    ]
   },
@@ -248,10 +248,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "S = Struct();\n",
-    "S.BF = BF;\n",
-    "S.method = 'grid';\n",
-    "S.grid = Struct(resolution=5);\n",
+    "S = Struct()\n",
+    "S.BF = BF\n",
+    "S.method = 'grid'\n",
+    "S.grid = Struct(resolution=5)\n",
     "BF = bf_wizard_sources(S);"
    ]
   },
@@ -299,9 +299,9 @@
    "outputs": [],
    "source": [
     "S = Struct()\n",
-    "S.BF = BF;\n",
-    "S.method = 'minimumnorm';\n",
-    "S.minimumnorm = dict(snr=10^2);\n",
+    "S.BF = BF\n",
+    "S.method = 'minimumnorm'\n",
+    "S.minimumnorm = dict(snr=10^2)\n",
     "BF = bf_wizard_inverse(S);"
    ]
   },
@@ -327,9 +327,9 @@
    "outputs": [],
    "source": [
     "S = Struct()\n",
-    "S.BF = BF;\n",
-    "S.act = 90;\n",
-    "S.base = 1;\n",
+    "S.BF = BF\n",
+    "S.act = 90\n",
+    "S.base = 1\n",
     "bf_stat_evoked_t(S, nargout=0);"
    ]
   },

examples/SourceLevelEvokedResponse.ipynb

@@ -2,7 +2,6 @@
 import os.path as op
 import platform
 import subprocess
-import sys
 import urllib.request
 import zipfile
 from itertools import product
@@ -170,7 +169,7 @@ def setup_matlab_environment(download):
     runtime_installed = download_and_install_matlab_runtime()
 
     if not runtime_installed:
-        raise SystemError(f'Failed to install Matlab Runtime. Please try manually.')
+        raise SystemError('Failed to install Matlab Runtime. Please try manually.')
 
     runtime_found = add_matlab_to_path('R2024b')
 

scripts/setup_matlab.py

@@ -19,3 +19,26 @@
 from .spm_spm_ui import spm_spm_ui
 from .spm_tbx_config2cfg import spm_tbx_config2cfg
 
+
+__all__ = [
+    "loadxml",
+    "savexml",
+    "spm_add",
+    "spm_adjmean_fmri_ui",
+    "spm_adjmean_ui",
+    "spm_atranspa",
+    "spm_chi2_plot",
+    "spm_digamma",
+    "spm_dirichlet",
+    "spm_eeval",
+    "spm_fMRI_design_show",
+    "spm_imcalc_ui",
+    "spm_load_float",
+    "spm_matlab_version_chk",
+    "spm_mean",
+    "spm_mean_ui",
+    "spm_read_hdr",
+    "spm_resss",
+    "spm_spm_ui",
+    "spm_tbx_config2cfg"
+]

spm/__compat/__init__.py

@@ -1,4 +1,4 @@
-from spm.__wrapper__ import Runtime
+from mpython import Runtime
 
 
 def loadxml(*args, **kwargs):

spm/__compat/loadxml.py

@@ -1,4 +1,4 @@
-from spm.__wrapper__ import Runtime
+from mpython import Runtime
 
 
 def savexml(*args, **kwargs):

spm/__compat/savexml.py

@@ -1,4 +1,4 @@
-from spm.__wrapper__ import Runtime
+from mpython import Runtime
 
 
 def spm_add(*args, **kwargs):