modified decoder code, decision function and added LP decoding

notebooks/decode_LP.py

@@ -0,0 +1,64 @@
+import sys
+sys.path.append(r"C:\Users\shailaja.akella\Dropbox (Personal)\DR\dynamic_routing_analysis_ethan\src")
+import npc_lims
+from dynamic_routing_analysis import decoding_utils
+from npc_sessions import DynamicRoutingSession
+
+# 1A get all uploaded & annotated ephys sessions
+# ephys_sessions = tuple(s for s in npc_lims.get_session_info(is_ephys=True, is_uploaded=True, is_annotated=True))
+
+# 2 set savepath and filename
+savepath = r"C:\Users\shailaja.akella\Dropbox (Personal)\DR\dynamic_routing_analysis_ethan\results"
+filename = 'decoding_results_linear_shift_20_units_re_run.pkl'
+
+except_list = {}
+
+# 3 set parameters
+# linear shift decoding currently just takes the average firing rate over all bins defined here
+spikes_binsize = 0.2  # bin size in seconds
+spikes_time_before = 0.2  # time before the stimulus per trial
+spikes_time_after = 0.01  # time after the stimulus per trial
+
+# #not used for linear shift decoding, were used in a previous iteration of decoding analysis
+# decoder_binsize=0.2
+# decoder_time_before=0.2
+# decoder_time_after=0.1
+
+params = {
+    'n_units': 20,  # number of units to sample for each area
+    'n_repeats': 25,  # number of times to repeat decoding with different randomly sampled units
+    'input_data_type': 'LP',  # spikes or facemap or LP
+    'vid_angle_facemotion': 'face', # behavior, face, eye
+    'vid_angle_LP': 'behavior',
+    'central_section': '4_blocks_plus',
+    # for linear shift decoding, how many trials to use for the shift. '4_blocks_plus' is best
+    'exclude_cue_trials': False,  # option to totally exclude autorewarded trials
+    'n_unit_threshold': 20,  # minimum number of units to include an area in the analysis
+    'keep_n_SVDs': 500,  # number of SVD components to keep for facemap data
+    'LP_parts_to_keep': ['ear_base_l', 'eye_bottom_l', 'jaw', 'nose_tip', 'whisker_pad_l_side'],
+    'spikes_binsize': spikes_binsize,
+    'spikes_time_before': spikes_time_before,
+    'spikes_time_after': spikes_time_after,
+    # 'decoder_binsize':decoder_binsize,
+    # 'decoder_time_before':decoder_time_before,
+    # 'decoder_time_after':decoder_time_after,
+    'savepath': savepath,
+    'filename': filename,
+    'use_structure_probe': True,  # if True, appedn probe name to area name when multiple probes in the same area
+    'crossval': '5_fold',  # '5_fold' or 'blockwise' - blockwise untested with linear shift
+    'labels_as_index': True,  # convert labels (context names) to index [0,1]
+    'decoder_type': 'linearSVC',  # 'linearSVC' or 'LDA' or 'RandomForest' or 'LogisticRegression'
+}
+# ephys_sessions[:]
+
+for ephys_session in ['713655_2024-08-05']:
+    try:
+        session = DynamicRoutingSession(ephys_session)
+        print(session.id + ' loaded')
+        if 'structure' in session.electrodes[:].columns:
+            decoding_utils.decode_context_with_linear_shift(session, params)
+        else:
+            print('no structure column found in electrodes table, moving to next recording')
+        session = []
+    except Exception as e:
+        except_list[session.id] = repr(e)

notebooks/decode_context_from_LP_parts.ipynb

@@ -0,0 +1,246 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "6350a309-0b19-4c9e-bb9b-6e29602b3b5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.append(r\"C:\\Users\\shailaja.akella\\Dropbox (Personal)\\DR\\dynamic_routing_analysis_ethan\\src\")\n",
+    "\n",
+    "import npc_lims\n",
+    "from dynamic_routing_analysis import decoding_utils\n",
+    "from npc_sessions import DynamicRoutingSession\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "6a608c57-4bb6-401a-8c17-fb8f85dec95f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#1A get all uploaded & annotated ephys sessions\n",
+    "ephys_sessions = tuple(s for s in npc_lims.get_session_info(is_ephys=True, is_uploaded=True, is_annotated=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "3aa8b197-c24a-451e-ac1b-1368b1db91cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "644867_2023-02-23_0 loaded\n",
+      "no cached trials table, using npc_sessions\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\shailaja.akella\\Anaconda3\\envs\\npc_sessions2\\lib\\site-packages\\numcodecs\\abc.py:107: UserWarning: Multi-threading is supported for wavpack version>=5.6.4, but current version is 5.5.0. Parallel decoding will not be available.\n",
+      "  return cls(**config)\n",
+      "aligning sound waveforms: 100%|████████████| 537/537 [01:03<00:00,  8.49trial/s]\n",
+      "Long exposure times detected for s3://aind-ephys-data/ecephys_644867_2023-02-23_12-14-29/behavior_videos/Behavior_20230223T121631.mp4, suggesting multiple videos captured on sync: len(exposing_time_blocks)=2\n",
+      "Long exposure times detected for s3://aind-ephys-data/ecephys_644867_2023-02-23_12-14-29/behavior_videos/Face_20230223T121631.mp4, suggesting multiple videos captured on sync: len(exposing_time_blocks)=2\n",
+      "Long exposure times detected for s3://aind-ephys-data/ecephys_644867_2023-02-23_12-14-29/behavior_videos/Eye_20230223T121631.mp4, suggesting multiple videos captured on sync: len(exposing_time_blocks)=2\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "finished 644867_2023-02-23 0\n",
+      "finished 644867_2023-02-23\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 2 set savepath and filename\n",
+    "savepath = r\"C:\\Users\\shailaja.akella\\Dropbox (Personal)\\DR\\dynamic_routing_analysis_ethan\\results\\all_features_LP_updated/\"\n",
+    "filename = 'decoding_results_linear_shift_LP.pkl'\n",
+    "\n",
+    "except_list = {}\n",
+    "\n",
+    "# 3 set parameters\n",
+    "# linear shift decoding currently just takes the average firing rate over all bins defined here\n",
+    "spikes_binsize = 0.2  # bin size in seconds\n",
+    "spikes_time_before = 0.2  # time before the stimulus per trial\n",
+    "spikes_time_after = 0.01  # time after the stimulus per trial\n",
+    "\n",
+    "# #not used for linear shift decoding, were used in a previous iteration of decoding analysis\n",
+    "# decoder_binsize=0.2\n",
+    "# decoder_time_before=0.2\n",
+    "# decoder_time_after=0.1\n",
+    "\n",
+    "params = {\n",
+    "    'n_units': 20,  # number of units to sample for each area\n",
+    "    'n_repeats': 25,  # number of times to repeat decoding with different randomly sampled units\n",
+    "    'input_data_type': 'LP',  # spikes or facemap or LP\n",
+    "    'vid_angle_facemotion': 'face', # behavior, face, eye\n",
+    "    'vid_angle_LP': 'behavior',\n",
+    "    'central_section': '4_blocks_plus',\n",
+    "    # for linear shift decoding, how many trials to use for the shift. '4_blocks_plus' is best\n",
+    "    'exclude_cue_trials': False,  # option to totally exclude autorewarded trials\n",
+    "    'n_unit_threshold': 20,  # minimum number of units to include an area in the analysis\n",
+    "    'keep_n_SVDs': 500,  # number of SVD components to keep for facemap data\n",
+    "    'LP_parts_to_keep': ['ear_base_l', 'jaw', 'nose_tip', 'whisker_pad_l_side'],\n",
+    "    'spikes_binsize': spikes_binsize,\n",
+    "    'spikes_time_before': spikes_time_before,\n",
+    "    'spikes_time_after': spikes_time_after,\n",
+    "    # 'decoder_binsize':decoder_binsize,\n",
+    "    # 'decoder_time_before':decoder_time_before,\n",
+    "    # 'decoder_time_after':decoder_time_after,\n",
+    "    'savepath': savepath,\n",
+    "    'filename': filename,\n",
+    "    'use_structure_probe': True,  # if True, appedn probe name to area name when multiple probes in the same area\n",
+    "    'crossval': '5_fold',  # '5_fold' or 'blockwise' - blockwise untested with linear shift\n",
+    "    'labels_as_index': True,  # convert labels (context names) to index [0,1]\n",
+    "    'decoder_type': 'linearSVC',  # 'linearSVC' or 'LDA' or 'RandomForest' or 'LogisticRegression'\n",
+    "}\n",
+    "\n",
+    "\n",
+    "for ephys_session in ephys_sessions[105:106]:\n",
+    "    try:\n",
+    "        session = DynamicRoutingSession(ephys_session)\n",
+    "        print(session.id + ' loaded')\n",
+    "        if 'structure' in session.electrodes[:].columns:\n",
+    "            decoding_utils.decode_context_with_linear_shift(session, params)\n",
+    "        else:\n",
+    "            print('no structure column found in electrodes table, moving to next recording')\n",
+    "        session = []\n",
+    "    except Exception as e:\n",
+    "        except_list[session.id] = repr(e)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "92cfdfc7-29dd-4083-92a9-ef7e794e8742",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([105], dtype=int64),)"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "session_ids = [session.id for session in ephys_sessions[:]]\n",
+    "np.where(np.array(session_ids) == '644867_2023-02-23')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "e34c3f1d-cade-4103-8d16-2e53c8957780",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{}"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "except_list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "340acbf2-182c-405f-afb9-00daab7c9f4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "644866_2023-02-10, \n",
+    "676909_2023-12-12, \n",
+    "676909_2023-12-13\t"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ab14fea9-3e45-4927-993a-9de808874de0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# missing nice\n",
+    "\n",
+    "# '706401'\n",
+    "#  '703880'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "81bd49bd-4081-4029-aca4-070d080ffe2f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(30, '706401_2024-04-22'),\n",
+       " (31, '703880_2024-04-18'),\n",
+       " (34, '703880_2024-04-17'),\n",
+       " (36, '703880_2024-04-15')]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "[(i, s.id) for i, s in enumerate(ephys_sessions[:]) if '706401' in s.id or '703880' in s.id]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "95ca8b3b-1c2d-4684-b13d-f746e70db822",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}