Merge pull request #952 from int-brain-lab/docs

Docs

Author: mayofaulkner

examples/exploring_data/data_download.ipynb

@@ -142,16 +142,18 @@
    ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "### Find recordings of a specific brain region\n",
     "If we are interested in a given brain region, we can use the `search_insertions` method to find all recordings associated with that region. For example, to find all recordings associated with the **Rhomboid Nucleus (RH)** region of the thalamus."
    ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# this is the query that yields the few recordings for the Rhomboid Nucleus (RH) region\n",
     "insertions_rh = one.search_insertions(atlas_acronym='RH', datasets='spikes.times.npy', project='brainwide')\n",
@@ -161,9 +163,7 @@
     "\n",
     "# the Allen brain regions parcellation is hierarchical, and searching for Thalamus will return all child Rhomboid Nucleus (RH) regions\n",
     "assert set(insertions_rh).issubset(set(insertions_th))\n"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -183,7 +183,7 @@
    "outputs": [],
    "source": [
     "# Find sessions that have spikes.times datasets\n",
-    "sessions_with_spikes = one.search(project='brainwide', dataset='spikes.times')"
+    "sessions_with_spikes = one.search(project='brainwide', datasets='spikes.times.npy')"
    ]
   },
   {
@@ -253,7 +253,7 @@
    "outputs": [],
    "source": [
     "# Find an example session with trials data\n",
-    "eid, *_ = one.search(project='brainwide', dataset='_ibl_trials.table.pqt')\n",
+    "eid, *_ = one.search(project='brainwide', datasets='_ibl_trials.table.pqt')\n",
     "# List datasets associated with a session, in the alf collection\n",
     "datasets = one.list_datasets(eid, collection='alf*')\n",
     "\n",
@@ -279,7 +279,7 @@
    "source": [
     "# Find an example session with spike data\n",
     "# Note: Restricting by task and project makes searching for data much quicker\n",
-    "eid, *_ = one.search(project='brainwide', dataset='spikes', task='ephys')\n",
+    "eid, *_ = one.search(project='brainwide', datasets='spikes.times.npy', task='ephys')\n",
     "\n",
     "# Data for each probe insertion are stored in the alf/probeXX folder.\n",
     "datasets = one.list_datasets(eid, collection='alf/probe*')\n",
@@ -375,7 +375,7 @@
     "lab_name = list(labs)[0]\n",
     "\n",
     "# Searching for RS sessions with specific lab name\n",
-    "sessions_lab = one.search(dataset='spikes', lab=lab_name)"
+    "sessions_lab = one.search(datasets='spikes', lab=lab_name)"
    ]
   },
   {

examples/loading_data/loading_photometry_data.ipynb

@@ -61,7 +61,7 @@
    "source": [
     "from one.api import ONE\n",
     "one = ONE()\n",
-    "sessions = one.search(dataset='photometry.signal.pqt')\n",
+    "sessions = one.search(datasets='photometry.signal.pqt')\n",
     "print(f'{len(sessions)} sessions with photometry data found')"
    ]
   },
@@ -271,7 +271,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

examples/loading_data/loading_trials_data.ipynb

@@ -50,7 +50,10 @@
    "cell_type": "markdown",
    "id": "a5d358e035a91310",
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
    },
    "source": [
     "## Loading a single session's trials\n"
@@ -77,7 +80,10 @@
    "cell_type": "markdown",
    "id": "d6c98a81f5426445",
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
    },
    "source": [
     "For combining trials data with various recording modalities for a given session, the `SessionLoader` class is more convenient:"
@@ -130,8 +136,12 @@
     "from one.api import ONE\n",
     "one = ONE()\n",
     "subject = 'SWC_043'\n",
+    "# Load in subject trials table\n",
     "trials = one.load_aggregate('subjects', subject, '_ibl_subjectTrials.table')\n",
     "\n",
+    "# Load in subject sessions table\n",
+    "sessions = one.load_aggregate('subjects', subject, '_ibl_subjectSessions.table')\n",
+    "\n",
     "# Load training status and join to trials table\n",
     "training = one.load_aggregate('subjects', subject, '_ibl_subjectTraining.table')\n",
     "trials = (trials\n",
@@ -141,10 +151,9 @@
     "trials['training_status'] = trials.training_status.fillna(method='ffill')\n",
     "\n",
     "# Join sessions table for number, task_protocol, etc.\n",
-    "trials = one.load_aggregate('subjects', subject, '_ibl_subjectTrials.table')\n",
     "if 'task_protocol' in trials:\n",
-    "    trials.drop('task_protocol', axis=1)\n",
-    "trials = trials.set_index('session').join(one._cache.sessions.drop('date', axis=1))"
+    "    trials = trials.drop('task_protocol', axis=1)\n",
+    "trials = trials.join(sessions.drop('date', axis=1))"
    ]
   },
   {
@@ -302,7 +311,10 @@
    "cell_type": "markdown",
    "id": "55ad2e5d71ac301",
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
    },
    "source": [
     "### Example 5: Computing the inter-trial interval (ITI)\n",
@@ -345,9 +357,9 @@
  "metadata": {
   "celltoolbar": "Edit Metadata",
   "kernelspec": {
-   "display_name": "Python [conda env:iblenv] *",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-iblenv-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -359,7 +371,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

examples/loading_data/loading_widefield_data.ipynb

@@ -86,7 +86,7 @@
    "source": [
     "from one.api import ONE\n",
     "one = ONE()\n",
-    "sessions = one.search(dataset='widefieldU.images.npy')\n",
+    "sessions = one.search(datasets='widefieldU.images.npy')\n",
     "print(f'{len(sessions)} sessions with widefield data found')"
    ]
   },
@@ -224,7 +224,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,