From ddc2fa096f37ad7b97b8070b7d82072a93fb825b Mon Sep 17 00:00:00 2001
From: didihou <didi.hou@rwth-aachen.de>
Date: Thu, 14 Sep 2023 13:50:19 +0200
Subject: [PATCH] /

---
 ...lize_interareal_connectivity-checkpoint.py |   3 +-
 .../M2E_visualize_interareal_connectivity.py  |   3 +-
 multi-area-model.ipynb                        | 197 ++++++------------
 .../viscortex_processed_data.json             |   2 +-
 4 files changed, 67 insertions(+), 138 deletions(-)

diff --git a/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py b/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py
index 4932f57..196fe25 100644
--- a/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py
+++ b/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py
@@ -79,7 +79,8 @@ def visualize_interareal_connectivity(M):
     """
     # M = MultiAreaModel({})
     M_full_scale = MultiAreaModel({})
-
+    
+    datapath = './multiarea_model/data_multiarea/'
     with open(os.path.join(datapath, 'viscortex_processed_data.json'), 'r') as f:
         proc = json.load(f)
     with open(os.path.join(datapath, 'viscortex_raw_data.json'), 'r') as f:
diff --git a/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py b/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py
index 4932f57..196fe25 100644
--- a/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py
+++ b/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py
@@ -79,7 +79,8 @@ def visualize_interareal_connectivity(M):
     """
     # M = MultiAreaModel({})
     M_full_scale = MultiAreaModel({})
-
+    
+    datapath = './multiarea_model/data_multiarea/'
     with open(os.path.join(datapath, 'viscortex_processed_data.json'), 'r') as f:
         proc = json.load(f)
     with open(os.path.join(datapath, 'viscortex_raw_data.json'), 'r') as f:
diff --git a/multi-area-model.ipynb b/multi-area-model.ipynb
index e6e9efe..ddb32cb 100644
--- a/multi-area-model.ipynb
+++ b/multi-area-model.ipynb
@@ -480,7 +480,7 @@
      "output_type": "stream",
      "text": [
       "Initializing network from dictionary.\n",
-      "RAND_DATA_LABEL 2812\n"
+      "RAND_DATA_LABEL 4230\n"
      ]
     },
     {
@@ -514,11 +514,62 @@
       "/srv/main-spack-instance-2305/spack/var/spack/environments/ebrains-23-06/.spack-env/view/lib/python3.8/site-packages/dicthash/dicthash.py:47: UserWarning:Float too small for safe conversion tointeger. Rounding down to zero.\n"
      ]
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Initializing network from dictionary.\n",
+      "RAND_DATA_LABEL 5307\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/main-spack-instance-2305/spack/opt/spack/linux-ubuntu20.04-x86_64/gcc-10.3.0/py-numpy-1.22.4-2oqgru7t5upcffz4fffhepvquuy3hdsh/lib/python3.8/site-packages/numpy/core/fromnumeric.py:3474: RuntimeWarning:Mean of empty slice.\n",
+      "/srv/main-spack-instance-2305/spack/opt/spack/linux-ubuntu20.04-x86_64/gcc-10.3.0/py-numpy-1.22.4-2oqgru7t5upcffz4fffhepvquuy3hdsh/lib/python3.8/site-packages/numpy/core/_methods.py:189: RuntimeWarning:invalid value encountered in double_scalars\n",
+      "Error in library(\"aod\") : there is no package called ‘aod’\n",
+      "Execution halted\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "No R installation or IndexError, taking hard-coded SLN fit parameters.\n",
+      "\n",
+      "\n",
+      "========================================\n",
+      "Customized parameters\n",
+      "--------------------\n",
+      "{}\n",
+      "========================================\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/main-spack-instance-2305/spack/var/spack/environments/ebrains-23-06/.spack-env/view/lib/python3.8/site-packages/dicthash/dicthash.py:47: UserWarning:Float too small for safe conversion tointeger. Rounding down to zero.\n"
+     ]
+    },
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "[Errno 2] No such file or directory: '../../multiarea_model/data_multiarea/viscortex_processed_data.json'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [12], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# %%capture captured\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mM2E_visualize_interareal_connectivity\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m visualize_interareal_connectivity\n\u001b[0;32m----> 3\u001b[0m visualize_interareal_connectivity(M)\n",
+      "File \u001b[0;32m~/MAM2EBRAINS/./figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py:83\u001b[0m, in \u001b[0;36mvisualize_interareal_connectivity\u001b[0;34m(M)\u001b[0m\n\u001b[1;32m     80\u001b[0m \u001b[38;5;66;03m# M = MultiAreaModel({})\u001b[39;00m\n\u001b[1;32m     81\u001b[0m M_full_scale \u001b[38;5;241m=\u001b[39m MultiAreaModel({})\n\u001b[0;32m---> 83\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdatapath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mviscortex_processed_data.json\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mr\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[1;32m     84\u001b[0m     proc \u001b[38;5;241m=\u001b[39m json\u001b[38;5;241m.\u001b[39mload(f)\n\u001b[1;32m     85\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(datapath, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mviscortex_raw_data.json\u001b[39m\u001b[38;5;124m'\u001b[39m), \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '../../multiarea_model/data_multiarea/viscortex_processed_data.json'"
+     ]
+    },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1080x476.769 with 4 Axes>"
+       "<Figure size 1080x317.846 with 3 Axes>"
       ]
      },
      "metadata": {
@@ -563,88 +614,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "15778e9c",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Prepared simulation in 0.00 seconds.\n",
-      "\n",
-      "Sep 14 13:36:30 SimulationManager::set_status [Info]: \n",
-      "    Temporal resolution changed from 0.1 to 0.1 ms.\n",
-      "Rank 0: created area V1 with 0 local nodes\n",
-      "Memory after V1 : 1514.97 MB\n",
-      "Rank 0: created area V2 with 0 local nodes\n",
-      "Memory after V2 : 1541.68 MB\n",
-      "Rank 0: created area VP with 0 local nodes\n",
-      "Memory after VP : 1570.82 MB\n",
-      "Rank 0: created area V3 with 0 local nodes\n",
-      "Memory after V3 : 1599.06 MB\n",
-      "Rank 0: created area V3A with 0 local nodes\n",
-      "Memory after V3A : 1619.04 MB\n",
-      "Rank 0: created area MT with 0 local nodes\n",
-      "Memory after MT : 1644.58 MB\n",
-      "Rank 0: created area V4t with 0 local nodes\n",
-      "Memory after V4t : 1669.54 MB\n",
-      "Rank 0: created area V4 with 0 local nodes\n",
-      "Memory after V4 : 1696.47 MB\n",
-      "Rank 0: created area VOT with 0 local nodes\n",
-      "Memory after VOT : 1721.05 MB\n",
-      "Rank 0: created area MSTd with 0 local nodes\n",
-      "Memory after MSTd : 1741.16 MB\n",
-      "Rank 0: created area PIP with 0 local nodes\n",
-      "Memory after PIP : 1762.50 MB\n",
-      "Rank 0: created area PO with 0 local nodes\n",
-      "Memory after PO : 1783.95 MB\n",
-      "Rank 0: created area DP with 0 local nodes\n",
-      "Memory after DP : 1804.21 MB\n",
-      "Rank 0: created area MIP with 0 local nodes\n",
-      "Memory after MIP : 1825.82 MB\n",
-      "Rank 0: created area MDP with 0 local nodes\n",
-      "Memory after MDP : 1847.16 MB\n",
-      "Rank 0: created area VIP with 0 local nodes\n",
-      "Memory after VIP : 1869.14 MB\n",
-      "Rank 0: created area LIP with 0 local nodes\n",
-      "Memory after LIP : 1893.07 MB\n",
-      "Rank 0: created area PITv with 0 local nodes\n",
-      "Memory after PITv : 1918.38 MB\n",
-      "Rank 0: created area PITd with 0 local nodes\n",
-      "Memory after PITd : 1943.52 MB\n",
-      "Rank 0: created area MSTl with 0 local nodes\n",
-      "Memory after MSTl : 1965.05 MB\n",
-      "Rank 0: created area CITv with 0 local nodes\n",
-      "Memory after CITv : 1984.18 MB\n",
-      "Rank 0: created area CITd with 0 local nodes\n",
-      "Memory after CITd : 2003.47 MB\n",
-      "Rank 0: created area FEF with 0 local nodes\n",
-      "Memory after FEF : 2024.96 MB\n",
-      "Rank 0: created area TF with 0 local nodes\n",
-      "Memory after TF : 2040.63 MB\n",
-      "Rank 0: created area AITv with 0 local nodes\n",
-      "Memory after AITv : 2063.18 MB\n",
-      "Rank 0: created area FST with 0 local nodes\n",
-      "Memory after FST : 2079.90 MB\n",
-      "Rank 0: created area 7a with 0 local nodes\n",
-      "Memory after 7a : 2101.22 MB\n",
-      "Rank 0: created area STPp with 0 local nodes\n",
-      "Memory after STPp : 2119.93 MB\n",
-      "Rank 0: created area STPa with 0 local nodes\n",
-      "Memory after STPa : 2139.07 MB\n",
-      "Rank 0: created area 46 with 0 local nodes\n",
-      "Memory after 46 : 2154.39 MB\n",
-      "Rank 0: created area AITd with 0 local nodes\n",
-      "Memory after AITd : 2176.82 MB\n",
-      "Rank 0: created area TH with 0 local nodes\n",
-      "Memory after TH : 2189.11 MB\n",
-      "Created areas and internal connections in 2.17 seconds.\n",
-      "Created cortico-cortical connections in 21.99 seconds.\n",
-      "Simulated network in 84.94 seconds.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# %%capture captured\n",
     "# run the simulation, depending on the model parameter and downscale ratio, the running time varies largely.\n",
@@ -671,30 +644,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "c1d7aa61-e85a-4e6a-9e01-e018413a572b",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Sep 14 13:36:54 NodeManager::prepare_nodes [Info]: \n",
-      "loading spikes\n",
-      "    Preparing 20780 nodes for simulation.\n",
-      "\n",
-      "Sep 14 13:36:54 SimulationManager::start_updating_ [Info]: \n",
-      "    Number of local nodes: 20780\n",
-      "    Simulation time (ms): 2000\n",
-      "    Number of OpenMP threads: 1\n",
-      "    Number of MPI processes: 1\n",
-      "\n",
-      "Sep 14 13:38:19 SimulationManager::run [Info]: \n",
-      "    Simulation finished.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Instantiate an analysis class and load spike data\n",
     "A = Analysis(network=M, \n",
@@ -715,23 +668,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "bea30fc8",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1080x476.769 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from M2E_visualize_instantaneous_and_mean_firing_rates import plot_instan_mean_firing_rate\n",
     "plot_instan_mean_firing_rate(M)"
@@ -758,25 +698,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "ae19bcc3",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "ename": "ImportError",
-     "evalue": "cannot import name 'original_data_path' from 'helpers' (/opt/app-root/src/MAM2EBRAINS/./figures/Schmidt2018/helpers.py)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn [16], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mM2E_visualize_resting_state\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m plot_resting_state\n\u001b[1;32m      2\u001b[0m plot_resting_state(M, A, data_path)\n",
-      "File \u001b[0;32m~/MAM2EBRAINS/./figures/MAM2EBRAINS/M2E_visualize_resting_state.py:8\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01msys\u001b[39;00m\n\u001b[1;32m      6\u001b[0m sys\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m./figures/Schmidt2018_dyn\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mhelpers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m original_data_path, population_labels\n\u001b[1;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmultiarea_model\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m MultiAreaModel\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mplotcolors\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m myred, myblue\n",
-      "\u001b[0;31mImportError\u001b[0m: cannot import name 'original_data_path' from 'helpers' (/opt/app-root/src/MAM2EBRAINS/./figures/Schmidt2018/helpers.py)"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from M2E_visualize_resting_state import plot_resting_state\n",
     "plot_resting_state(M, A, data_path)"
diff --git a/multiarea_model/data_multiarea/viscortex_processed_data.json b/multiarea_model/data_multiarea/viscortex_processed_data.json
index 8421316..75c6ed0 100644
--- a/multiarea_model/data_multiarea/viscortex_processed_data.json
+++ b/multiarea_model/data_multiarea/viscortex_processed_data.json
@@ -1 +1 @@
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\ No newline at end of file
-- 
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