diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 8da40cad6..0b0051a14 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -47,28 +47,30 @@ nav: - Home: index.md - Installation: installation.md - Miscellaneous: - - FigURL: misc/figurl_views.md - - Session Groups: misc/session_groups.md - - Insert Data: misc/insert_data.md - - Merge Tables: misc/merge_tables.md + - FigURL: misc/figurl_views.md + - Session Groups: misc/session_groups.md + - Insert Data: misc/insert_data.md + - Merge Tables: misc/merge_tables.md - Tutorials: + - General: - Setup: notebooks/00_Setup.ipynb - Insert Data: notebooks/01_Insert_Data.ipynb - - Spike Sorting: notebooks/02_Spike_Sorting.ipynb - - Curation: notebooks/03_Curation.ipynb - - LFP: notebooks/03_lfp.ipynb - - Position: - - Information: notebooks/4_position_info.ipynb - - Pipeline: notebooks/04_Trodes_position.ipynb - - From Scratch: notebooks/05_DLC_from_scratch.ipynb - - From Pre-Trained: notebooks/06_DLC_from_dir.ipynb - - Linearization Pipeline: notebooks/07_linearization.ipynb - - Mark Indicators: notebooks/08_Extract_Mark_indicators.ipynb - - GPU: notebooks/09_Decoding_with_GPUs_on_the_GPU_cluster.ipynb - - 1D Clusterless Decoding: notebooks/10_1D_Clusterless_Decoding.ipynb - - 2D Clusterless Decoding: notebooks/11_2D_Clusterless_Decoding.ipynb - - Ripple Detection: notebooks/12_Ripple_Detection.ipynb - - Spyglass Kachery Setup: notebooks/Spyglass_kachery_setup.ipynb + - Data Sync: notebooks/02_Data_Sync.ipynb + - Ephys: + - Spike Sorting: notebooks/10_Spike_Sorting.ipynb + - Curation: notebooks/11_Curation.ipynb + - LFP: notebooks/12_LFP.ipynb + - Theta: notebooks/14_Theta.ipynb + - Position: + - Position Trodes: notebooks/20_Position_Trodes.ipynb + - Position DLC 1: notebooks/21_Position_DLC_1.ipynb + - Position DLC 2: notebooks/22_Position_DLC_2.ipynb + - Linearization: notebooks/24_Linearization.ipynb + - Combined: + - Ripple Detection: notebooks/30_Ripple_Detection.ipynb + - Extract Mark Indicators: notebooks/31_Extract_Mark_Indicators.ipynb + - Decoding with GPUs: notebooks/32_Decoding_with_GPUs.ipynb + - Decoding Clusterless: notebooks/33_Decoding_Clusterless.ipynb - API Reference: api/ # defer to gen-files + literate-nav - How to Contribute: contribute.md - Change Log: CHANGELOG.md diff --git a/notebooks/00_Setup.ipynb b/notebooks/00_Setup.ipynb index 915f121a0..d1a906d2b 100644 --- a/notebooks/00_Setup.ipynb +++ b/notebooks/00_Setup.ipynb @@ -231,19 +231,54 @@ "source": [ "### Loading the config\n", "\n", - "We can check that the paths are correctly set up by loading the config.\n" + "We can check that the paths are correctly set up by loading the config from \n", + "the main Spyglass directory.\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "912ac84b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'debug_mode': True,\n", + " 'prepopulate': True,\n", + " 'SPYGLASS_BASE_DIR': '/stelmo/nwb',\n", + " 'SPYGLASS_RAW_DIR': '/stelmo/nwb/raw',\n", + " 'SPYGLASS_ANALYSIS_DIR': '/stelmo/nwb/analysis',\n", + " 'SPYGLASS_RECORDING_DIR': '/stelmo/nwb/recording',\n", + " 'SPYGLASS_SORTING_DIR': '/stelmo/nwb/spikesorting',\n", + " 'SPYGLASS_WAVEFORMS_DIR': '/stelmo/nwb/waveforms',\n", + " 'SPYGLASS_TEMP_DIR': '/stelmo/nwb/tmp',\n", + " 'SPYGLASS_VIDEO_DIR': '/stelmo/nwb/video',\n", + " 'KACHERY_CLOUD_DIR': '/stelmo/nwb/kachery_storage',\n", + " 'KACHERY_STORAGE_DIR': '/stelmo/nwb/kachery_storage',\n", + " 'KACHERY_TEMP_DIR': '/stelmo/nwb/tmp',\n", + " 'KACHERY_ZONE': 'franklab.default',\n", + " 'FIGURL_CHANNEL': 'franklab2',\n", + " 'DJ_SUPPORT_FILEPATH_MANAGEMENT': 'TRUE',\n", + " 'KACHERY_CLOUD_EPHEMERAL': 'TRUE'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "from spyglass.settings import load_config\n", + "import os\n", + "import datajoint as dj\n", "\n", - "load_config()" + "if os.path.basename(os.getcwd()) == \"notebooks\":\n", + " os.chdir(\"..\")\n", + "dj.config.load(\"dj_local_conf.json\")\n", + "\n", + "from spyglass.settings import config\n", + "\n", + "config" ] }, { @@ -260,10 +295,32 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "afb63913-4e6b-4049-ae1d-55ab1ac8d42c", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2023-09-28 08:07:06,176][INFO]: Connecting root@localhost:3307\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2023-09-28 08:07:06,254][INFO]: Connected root@localhost:3307\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Populate: Populating table DataAcquisitionDeviceSystem with data {'data_acquisition_device_system': 'SpikeGadgets'} using insert1.\n", + "Populate: Populating table DataAcquisitionDeviceAmplifier with data {'data_acquisition_device_amplifier': 'Intan'} using insert1.\n" + ] + }, { "data": { "text/html": [ @@ -319,38 +376,14 @@ " }\n", " \n", " \n", - " \n", + " Table for holding the NWB files.\n", "
\n",
" nwb_file_name \n", - " \n", - " | \n",
- " sort_group_id \n", - " \n", + " name of the NWB file\n", " | \n",
- " sort_interval_name \n", - " \n", - " | \n",
- " filter_parameter_set_name \n", - " \n", - " | \n",
- " sorter_name \n", - " \n", - " | \n",
- " spikesorter_parameter_set_name \n", - " \n", - " | \n",
- " sorting_id \n", - " \n", - " | \n",
- " analysis_file_name \n", - " \n", - " | \n",
- " time_of_sort \n", - " in Unix time, to the nearest second\n", - " | \n",
- " units_object_id \n", + "nwb_file_abs_path \n", " \n", " |
---|---|---|---|---|---|---|---|---|---|
Total: 3
Total: 2
\n", " " ], "text/plain": [ "*lab_member_na google_user_na datajoint_user\n", "+------------+ +------------+ +------------+\n", - "Alison Comrie comrie.alison@ alison \n", "Firstname Last example1@gmail example1 \n", "Firstname2 Las example2@gmail example2 \n", - " (Total: 3)" + " (Total: 2)" ] }, "execution_count": 6, @@ -990,26 +1032,24 @@ "lab_member_name
\n", " \n", " \n", - "Total: 5
\n", + "Total: 4
\n", " " ], "text/plain": [ "*team_name *lab_member_na\n", "+------------+ +------------+\n", - "Beans Alison Comrie \n", "Firstname Last Firstname Last\n", "My Team Firstname Last\n", "Firstname2 Las Firstname2 Las\n", "My Team Firstname2 Las\n", - " (Total: 5)" + " (Total: 4)" ] }, "execution_count": 8, @@ -1025,7 +1065,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Inserting from NWB\n", + "## Inserting from NWB\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "\n", "`spyglass.data_import.insert_sessions` helps take the many fields of data\n", "present in an NWB file and insert them into various tables across Spyglass. If\n", @@ -1036,64 +1082,17 @@ "- neural activity (extracellular recording of multiple brain areas)\n", "- etc.\n", "\n", - "_Note:_ this may take a while because it makes a copy of the NWB file.\n" + "_Note:_ this may take time as Spyglass creates the copy. You may see a prompt \n", + "about inserting device information." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Creating a copy of NWB file minirec20230622.nwb with link to raw ephys data: minirec20230622_.nwb\n", - "Populate Session...\n", - "No config found at file path /home/cb/wrk/zOther/data/raw/minirec20230622_spyglass_config.yaml\n", - "Institution...\n", - "Lab...\n", - "LabMember...\n", - "Subject...\n", - "Populate DataAcquisitionDevice...\n", - "Inserted or referenced data acquisition device(s): dict_keys(['dataacq_device0'])\n", - "\n", - "Populate CameraDevice...\n", - "Inserted camera devices ['test camera 1']\n", - "\n", - "Populate Probe...\n", - "Probe ID '128c-4s6mm6cm-15um-26um-sl' already exists in the database. Spyglass will use that and not create a new Probe, Shanks, or Electrodes.\n", - "Inserted probes {'128c-4s6mm6cm-15um-26um-sl'}\n", - "\n", - "Skipping Apparatus for now...\n", - "IntervalList...\n", - "LabMember with name lastname, firstname does not exist. Cannot link Session with LabMember in Session.Experimenter.\n", - "LabMember with name lastname2, firstname2 does not exist. Cannot link Session with LabMember in Session.Experimenter.\n", - "Populate ElectrodeGroup...\n", - "Populate Electrode...\n", - "No config found at file path /home/cb/wrk/zOther/data/raw/minirec20230622_spyglass_config.yaml\n", - "Populate Raw...\n", - "Estimating sampling rate...\n", - "Estimated sampling rate: 30000.0\n", - "Importing raw data: Sampling rate:\t30000.0 Hz\n", - "Number of valid intervals:\t2\n", - "Populate SampleCount...\n", - "Populate DIOEvents...\n", - "Populate TaskEpochs\n", - "Populate StateScriptFile\n", - "Populate VideoFile\n", - "No video found corresponding to epoch 01_s1\n", - "No video found corresponding to epoch 02_s2\n", - "RawPosition...\n", - "Processing raw position data. Estimated sampling rate: 30.0 Hz\n", - "Processing raw position data. Estimated sampling rate: 30.0 Hz\n", - "Processing raw position data. Estimated sampling rate: 30.0 Hz\n", - "Processing raw position data. Estimated sampling rate: 30.0 Hz\n" - ] - } - ], + "outputs": [], "source": [ "sgi.insert_sessions(nwb_file_name)" ] @@ -1118,7 +1117,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -1196,7 +1195,7 @@ " (Total: 1)" ] }, - "execution_count": 28, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -1214,7 +1213,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -1231,7 +1230,7 @@ " 'experiment_description']" ] }, - "execution_count": 29, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -1249,7 +1248,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -1258,7 +1257,7 @@ "['nwb_file_name']" ] }, - "execution_count": 30, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -1276,7 +1275,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -1386,7 +1385,7 @@ " (Total: 1)" ] }, - "execution_count": 12, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -1404,7 +1403,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -1440,7 +1439,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -1479,7 +1478,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -1589,7 +1588,7 @@ " (Total: 1)" ] }, - "execution_count": 14, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1607,21 +1606,21 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ - "Total: 7
\n", + "Total: 5
\n", " " ], "text/plain": [ @@ -1915,13 +1910,11 @@ "minirec2023062 02_s2 =BLOB= \n", "minirec2023062 pos 0 valid ti =BLOB= \n", "minirec2023062 pos 1 valid ti =BLOB= \n", - "minirec2023062 pos 2 valid ti =BLOB= \n", - "minirec2023062 pos 3 valid ti =BLOB= \n", "minirec2023062 raw data valid =BLOB= \n", - " (Total: 7)" + " (Total: 5)" ] }, - "execution_count": 37, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1944,16 +1937,16 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([], shape=(0, 2), dtype=float64)" + "array([[1.68747483e+09, 1.68747484e+09]])" ] }, - "execution_count": 17, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1978,17 +1971,17 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array(['01_s1', '02_s2', 'pos 0 valid times', 'pos 3 valid times',\n", - " 'raw data valid times'], dtype=object)" + "array(['01_s1', '02_s2', 'pos 0 valid times', 'raw data valid times'],\n", + " dtype=object)" ] }, - "execution_count": 18, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -2022,7 +2015,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -2132,7 +2125,7 @@ " (Total: 1)" ] }, - "execution_count": 48, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -2152,11 +2145,56 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2023-09-28 08:29:15,814][INFO]: Deleting 4 rows from `common_behav`.`_raw_position__pos_object`\n", + "INFO:datajoint:Deleting 4 rows from `common_behav`.`_raw_position__pos_object`\n", + "[2023-09-28 08:29:15,822][INFO]: Deleting 2 rows from `common_behav`.`_raw_position`\n", + "INFO:datajoint:Deleting 2 rows from `common_behav`.`_raw_position`\n", + "[2023-09-28 08:29:15,834][INFO]: Deleting 4 rows from `common_behav`.`position_source__spatial_series`\n", + "INFO:datajoint:Deleting 4 rows from `common_behav`.`position_source__spatial_series`\n", + "[2023-09-28 08:29:15,841][INFO]: Deleting 2 rows from `common_behav`.`position_source`\n", + "INFO:datajoint:Deleting 2 rows from `common_behav`.`position_source`\n", + "[2023-09-28 08:29:15,851][INFO]: Deleting 7 rows from `common_dio`.`_d_i_o_events`\n", + "INFO:datajoint:Deleting 7 rows from `common_dio`.`_d_i_o_events`\n", + "[2023-09-28 08:29:15,871][INFO]: Deleting 128 rows from `common_ephys`.`_electrode`\n", + "INFO:datajoint:Deleting 128 rows from `common_ephys`.`_electrode`\n", + "[2023-09-28 08:29:15,879][INFO]: Deleting 1 rows from `common_ephys`.`_electrode_group`\n", + "INFO:datajoint:Deleting 1 rows from `common_ephys`.`_electrode_group`\n", + "[2023-09-28 08:29:15,887][INFO]: Deleting 1 rows from `common_ephys`.`_raw`\n", + "INFO:datajoint:Deleting 1 rows from `common_ephys`.`_raw`\n", + "[2023-09-28 08:29:15,896][INFO]: Deleting 1 rows from `common_ephys`.`_sample_count`\n", + "INFO:datajoint:Deleting 1 rows from `common_ephys`.`_sample_count`\n", + "[2023-09-28 08:29:15,908][INFO]: Deleting 2 rows from `common_behav`.`__position_interval_map`\n", + "INFO:datajoint:Deleting 2 rows from `common_behav`.`__position_interval_map`\n", + "[2023-09-28 08:29:15,918][INFO]: Deleting 2 rows from `common_task`.`_task_epoch`\n", + "INFO:datajoint:Deleting 2 rows from `common_task`.`_task_epoch`\n", + "[2023-09-28 08:29:15,924][INFO]: Deleting 5 rows from `common_interval`.`interval_list`\n", + "INFO:datajoint:Deleting 5 rows from `common_interval`.`interval_list`\n", + "[2023-09-28 08:29:15,931][INFO]: Deleting 1 rows from `common_session`.`_session`\n", + "INFO:datajoint:Deleting 1 rows from `common_session`.`_session`\n", + "[2023-09-28 08:29:18,765][INFO]: Deletes committed.\n", + "INFO:datajoint:Deletes committed.\n" + ] + }, + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# session_entry.delete()" + "session_entry.delete()" ] }, { @@ -2168,7 +2206,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -2270,7 +2308,7 @@ " (Total: 0)" ] }, - "execution_count": 51, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -2281,7 +2319,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -2365,7 +2403,7 @@ " (Total: 0)" ] }, - "execution_count": 52, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -2505,8 +2543,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In the [next notebook](./02_Spike_Sorting.ipynb), we'll dive into the Spike\n", - "Sorting pipeline.\n" + "## Up Next" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the [next notebook](./02_Data_Sync.ipynb), we'll explore tools for syncing.\n" ] } ], diff --git a/notebooks/02_Data_Sync.ipynb b/notebooks/02_Data_Sync.ipynb index 8c6913adb..f7d57ef40 100644 --- a/notebooks/02_Data_Sync.ipynb +++ b/notebooks/02_Data_Sync.ipynb @@ -7,15 +7,6 @@ "# Sync Data\n" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "DEV note: \n", - " - set up as host, then as client\n", - " - test as collaborator" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -29,7 +20,7 @@ "source": [ "This notebook will cover ...\n", "\n", - "1. [General Kachery information](#intro) \n", + "1. [General Kachery information](#kachery) \n", "2. Setting up Kachery as a [host](#host-setup). If you'll use an existing host, \n", " skip this.\n", "3. Setting up Kachery in your [database](#database-setup). If you're using an \n", @@ -41,19 +32,120 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Intro\n" + "## Imports\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "_Developer Note:_ if you may make a PR in the future, be sure to copy this\n", + "notebook, and use the `gitignore` prefix `temp` to avoid future conflicts.\n", + "\n", + "This is one notebook in a multi-part series on Spyglass.\n", + "\n", + "- To set up your Spyglass environment and database, see\n", + " [the Setup notebook](./00_Setup.ipynb)\n", + "- To fully demonstate syncing features, we'll need to run some basic analyses. \n", + " This can either be done with code in this notebook or by running another\n", + " notebook (e.g., [LFP](./12_LFP.ipynb))\n", + "- For additional info on DataJoint syntax, including table definitions and\n", + " inserts, see\n", + " [these additional tutorials](https://github.com/datajoint/datajoint-tutorials)\n", + "\n", + "Let's start by importing the `spyglass` package.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2023-09-28 09:39:48,974][INFO]: Connecting root@localhost:3307\n", + "[2023-09-28 09:39:49,050][INFO]: Connected root@localhost:3307\n" + ] + } + ], + "source": [ + "import os\n", + "import datajoint as dj\n", + "import pandas as pd\n", + "\n", + "# change to the upper level folder to detect dj_local_conf.json\n", + "if os.path.basename(os.getcwd()) == \"notebooks\":\n", + " os.chdir(\"..\")\n", + "dj.config.load(\"dj_local_conf.json\") # load config for database connection\n", + "\n", + "import spyglass.common as sgc\n", + "import spyglass.sharing as sgs\n", + "from spyglass.settings import config\n", + "\n", + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "This is one notebook in a multi-part series on Spyglass. Before running, be sure\n", - "to [setup your environment](./00_Setup.ipynb) and run some analyses (e.g. \n", - "[LFP](./12_LFP.ipynb)).\n", + "For example analysis files, run the code hidden below.\n", "\n", - "### Cloud\n", + " \n",
+ " nwb_file_name \n", + " name of the NWB file\n", + " | \n",
+ " interval_list_name \n", + " descriptive name of this interval list\n", + " |
---|---|
minirec20230622_.nwb | \n", + "pos 0 valid times |
minirec20230622_.nwb | \n", + "pos 1 valid times |
Total: 2
Total: 2
\n", + "Total: 3
\n", " " ], "text/plain": [ @@ -277,18 +379,33 @@ "+------------+ +--------+\n", "default =BLOB= \n", "default_led0 =BLOB= \n", - " (Total: 2)" + "single_led =BLOB= \n", + " (Total: 3)" ] }, - "execution_count": 5, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "parameters[\"led1_is_front\"] = 0\n", + "trodes_params_name = \"single_led\"\n", + "trodes_params = {\n", + " \"max_separation\": 10000.0,\n", + " \"max_speed\": 300.0,\n", + " \"position_smoothing_duration\": 0.125,\n", + " \"speed_smoothing_std_dev\": 0.1,\n", + " \"orient_smoothing_std_dev\": 0.001,\n", + " \"led1_is_front\": 1,\n", + " \"is_upsampled\": 0,\n", + " \"upsampling_sampling_rate\": None,\n", + " \"upsampling_interpolation_method\": \"linear\",\n", + "}\n", "sgp.v1.TrodesPosParams.insert1(\n", - " {\"trodes_pos_params_name\": \"default_led0\", \"params\": parameters},\n", + " {\n", + " \"trodes_pos_params_name\": trodes_params_name,\n", + " \"params\": trodes_params,\n", + " },\n", " skip_duplicates=True,\n", ")\n", "sgp.v1.TrodesPosParams()" @@ -390,49 +507,31 @@ "Total: 12
\n", + "Total: 6
\n", " " ], "text/plain": [ "*nwb_file_name *interval_list valid_time\n", "+------------+ +------------+ +--------+\n", "minirec2023062 01_s1 =BLOB= \n", - "minirec2023062 01_s1_first9 =BLOB= \n", - "minirec2023062 01_s1_first9 l =BLOB= \n", "minirec2023062 02_s2 =BLOB= \n", "minirec2023062 lfp_test_01_s1 =BLOB= \n", - "minirec2023062 minirec2023062 =BLOB= \n", - "minirec2023062 minirec2023062 =BLOB= \n", "minirec2023062 pos 0 valid ti =BLOB= \n", "minirec2023062 pos 1 valid ti =BLOB= \n", - "minirec2023062 pos 2 valid ti =BLOB= \n", - "minirec2023062 pos 3 valid ti =BLOB= \n", "minirec2023062 raw data valid =BLOB= \n", - " (Total: 12)" + " (Total: 6)" ] }, "execution_count": 6, @@ -485,13 +584,17 @@ " \n", "267 rows × 2 columns
\n", + "267 rows × 4 columns
\n", "" ], "text/plain": [ - " xloc yloc\n", - "time \n", - "1.687475e+09 445 567\n", - "1.687475e+09 445 567\n", - "1.687475e+09 445 567\n", - "1.687475e+09 444 568\n", - "1.687475e+09 444 568\n", - "... ... ...\n", - "1.687475e+09 479 536\n", - "1.687475e+09 480 534\n", - "1.687475e+09 480 533\n", - "1.687475e+09 481 530\n", - "1.687475e+09 481 530\n", + " xloc1 yloc1 xloc2 yloc2\n", + "time \n", + "1.687475e+09 445 567 0 0\n", + "1.687475e+09 445 567 0 0\n", + "1.687475e+09 445 567 0 0\n", + "1.687475e+09 444 568 0 0\n", + "1.687475e+09 444 568 0 0\n", + "... ... ... ... ...\n", + "1.687475e+09 479 536 0 0\n", + "1.687475e+09 480 534 0 0\n", + "1.687475e+09 480 533 0 0\n", + "1.687475e+09 481 530 0 0\n", + "1.687475e+09 481 530 0 0\n", "\n", - "[267 rows x 2 columns]" + "[267 rows x 4 columns]" ] }, "execution_count": 7, @@ -600,7 +725,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "df3d7797-6514-4ddc-9e5d-012a2b8a3e0c", "metadata": {}, "outputs": [ @@ -610,7 +735,7 @@ "Text(0.5, 1.0, 'Raw Position')" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, @@ -627,7 +752,7 @@ ], "source": [ "fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n", - "ax.plot(raw_position_df.xloc, raw_position_df.yloc, color=\"green\")\n", + "ax.plot(raw_position_df.xloc1, raw_position_df.yloc1, color=\"green\")\n", "# Uncomment for multiple LEDs\n", "# ax.plot(raw_position_df.xloc2, raw_position_df.yloc2, color=\"red\")\n", "ax.set_xlabel(\"x-position [pixels]\", fontsize=18)\n", @@ -654,17 +779,18 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "id": "9757d864-942e-4f4f-b7eb-5e454ff7151b", "metadata": {}, "outputs": [], "source": [ + "trodes_s_key = {\n", + " \"nwb_file_name\": nwb_copy_file_name,\n", + " \"interval_list_name\": interval_list_name,\n", + " \"trodes_pos_params_name\": trodes_params_name,\n", + "}\n", "sgp.v1.TrodesPosSelection.insert1(\n", - " {\n", - " \"nwb_file_name\": nwb_copy_file_name,\n", - " \"interval_list_name\": interval_list_name,\n", - " \"trodes_pos_params_name\": \"default\",\n", - " },\n", + " trodes_s_key,\n", " skip_duplicates=True,\n", ")" ] @@ -679,20 +805,12 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 10, "id": "0fcc42c3-ae95-4d56-be13-a7bc740d0dda", "metadata": {}, "outputs": [], "source": [ - "sgp.v1.TrodesPosSelection()\n", - "trodes_key = (\n", - " sgp.v1.TrodesPosSelection()\n", - " & {\n", - " \"nwb_file_name\": nwb_copy_file_name,\n", - " \"interval_list_name\": interval_list_name,\n", - " \"trodes_pos_params_name\": \"default\",\n", - " }\n", - ").fetch1(\"KEY\")" + "trodes_key = (sgp.v1.TrodesPosSelection() & trodes_s_key).fetch1(\"KEY\")" ] }, { @@ -714,42 +832,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 11, "id": "75412566-c9ea-4590-a7d0-c6b4af214fcf", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Computing position for: {'nwb_file_name': 'minirec20230622_.nwb', 'interval_list_name': 'pos 0 valid times', 'trodes_pos_params_name': 'default'}\n", - "Writing new NWB file minirec20230622_T3GNPZC8A2.nwb\n" - ] - }, - { - "ename": "KeyError", - "evalue": "\"['xloc2', 'yloc2'] not in index\"", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m sgp\u001b[39m.\u001b[39;49mv1\u001b[39m.\u001b[39;49mTrodesPosV1\u001b[39m.\u001b[39;49mpopulate(trodes_key)\n", - "File \u001b[0;32m~/wrk/datajoint-python/datajoint/autopopulate.py:241\u001b[0m, in \u001b[0;36mAutoPopulate.populate\u001b[0;34m(self, suppress_errors, return_exception_objects, reserve_jobs, order, limit, max_calls, display_progress, processes, make_kwargs, *restrictions)\u001b[0m\n\u001b[1;32m 237\u001b[0m \u001b[39mif\u001b[39;00m processes \u001b[39m==\u001b[39m \u001b[39m1\u001b[39m:\n\u001b[1;32m 238\u001b[0m \u001b[39mfor\u001b[39;00m key \u001b[39min\u001b[39;00m (\n\u001b[1;32m 239\u001b[0m tqdm(keys, desc\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m) \u001b[39mif\u001b[39;00m display_progress \u001b[39melse\u001b[39;00m keys\n\u001b[1;32m 240\u001b[0m ):\n\u001b[0;32m--> 241\u001b[0m error \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_populate1(key, jobs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mpopulate_kwargs)\n\u001b[1;32m 242\u001b[0m \u001b[39mif\u001b[39;00m error \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m 243\u001b[0m error_list\u001b[39m.\u001b[39mappend(error)\n", - "File \u001b[0;32m~/wrk/datajoint-python/datajoint/autopopulate.py:292\u001b[0m, in \u001b[0;36mAutoPopulate._populate1\u001b[0;34m(self, key, jobs, suppress_errors, return_exception_objects, make_kwargs)\u001b[0m\n\u001b[1;32m 290\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m\u001b[39m.\u001b[39m_allow_insert \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m\n\u001b[1;32m 291\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 292\u001b[0m make(\u001b[39mdict\u001b[39;49m(key), \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49m(make_kwargs \u001b[39mor\u001b[39;49;00m {}))\n\u001b[1;32m 293\u001b[0m \u001b[39mexcept\u001b[39;00m (\u001b[39mKeyboardInterrupt\u001b[39;00m, \u001b[39mSystemExit\u001b[39;00m, \u001b[39mException\u001b[39;00m) \u001b[39mas\u001b[39;00m error:\n\u001b[1;32m 294\u001b[0m \u001b[39mtry\u001b[39;00m:\n", - "File \u001b[0;32m~/wrk/spyglass/src/spyglass/position/v1/position_trodes_position.py:133\u001b[0m, in \u001b[0;36mTrodesPosV1.make\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 130\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m 131\u001b[0m \u001b[39m# calculate the processed position\u001b[39;00m\n\u001b[1;32m 132\u001b[0m spatial_series \u001b[39m=\u001b[39m raw_position[\u001b[39m\"\u001b[39m\u001b[39mraw_position\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[0;32m--> 133\u001b[0m position_info \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mcalculate_position_info_from_spatial_series(\n\u001b[1;32m 134\u001b[0m spatial_series,\n\u001b[1;32m 135\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mmax_separation\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 136\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mmax_speed\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 137\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mspeed_smoothing_std_dev\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 138\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mposition_smoothing_duration\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 139\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39morient_smoothing_std_dev\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 140\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mled1_is_front\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 141\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mis_upsampled\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 142\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mupsampling_sampling_rate\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 143\u001b[0m position_info_parameters[\u001b[39m\"\u001b[39;49m\u001b[39mupsampling_interpolation_method\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m 144\u001b[0m )\n\u001b[1;32m 145\u001b[0m \u001b[39m# create nwb objects for insertion into analysis nwb file\u001b[39;00m\n\u001b[1;32m 146\u001b[0m position\u001b[39m.\u001b[39mcreate_spatial_series(\n\u001b[1;32m 147\u001b[0m name\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mposition\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m 148\u001b[0m timestamps\u001b[39m=\u001b[39mposition_info[\u001b[39m\"\u001b[39m\u001b[39mtime\u001b[39m\u001b[39m\"\u001b[39m],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 153\u001b[0m description\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mx_position, y_position\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m 154\u001b[0m )\n", - "File \u001b[0;32m~/wrk/spyglass/src/spyglass/position/v1/position_trodes_position.py:248\u001b[0m, in \u001b[0;36mTrodesPosV1.calculate_position_info_from_spatial_series\u001b[0;34m(spatial_series, max_LED_separation, max_plausible_speed, speed_smoothing_std_dev, position_smoothing_duration, orient_smoothing_std_dev, led1_is_front, is_upsampled, upsampling_sampling_rate, upsampling_interpolation_method)\u001b[0m\n\u001b[1;32m 245\u001b[0m \u001b[39m# Get spatial series properties\u001b[39;00m\n\u001b[1;32m 246\u001b[0m time \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39masarray(spatial_series\u001b[39m.\u001b[39mtimestamps) \u001b[39m# seconds\u001b[39;00m\n\u001b[1;32m 247\u001b[0m position \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39masarray(\n\u001b[0;32m--> 248\u001b[0m pd\u001b[39m.\u001b[39;49mDataFrame(\n\u001b[1;32m 249\u001b[0m spatial_series\u001b[39m.\u001b[39;49mdata,\n\u001b[1;32m 250\u001b[0m columns\u001b[39m=\u001b[39;49mspatial_series\u001b[39m.\u001b[39;49mdescription\u001b[39m.\u001b[39;49msplit(\u001b[39m\"\u001b[39;49m\u001b[39m, \u001b[39;49m\u001b[39m\"\u001b[39;49m),\n\u001b[1;32m 251\u001b[0m )\u001b[39m.\u001b[39;49mloc[:, [\u001b[39m\"\u001b[39;49m\u001b[39mxloc\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39myloc\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39mxloc2\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39myloc2\u001b[39;49m\u001b[39m\"\u001b[39;49m]]\n\u001b[1;32m 252\u001b[0m ) \u001b[39m# meters\u001b[39;00m\n\u001b[1;32m 254\u001b[0m \u001b[39m# remove NaN times\u001b[39;00m\n\u001b[1;32m 255\u001b[0m is_nan_time \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39misnan(time)\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexing.py:1097\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1095\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1096\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mobj\u001b[39m.\u001b[39m_get_value(\u001b[39m*\u001b[39mkey, takeable\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_takeable)\n\u001b[0;32m-> 1097\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_getitem_tuple(key)\n\u001b[1;32m 1098\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 1099\u001b[0m \u001b[39m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1100\u001b[0m axis \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39maxis \u001b[39mor\u001b[39;00m \u001b[39m0\u001b[39m\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexing.py:1289\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1286\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_multi_take_opportunity(tup):\n\u001b[1;32m 1287\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_multi_take(tup)\n\u001b[0;32m-> 1289\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_getitem_tuple_same_dim(tup)\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexing.py:955\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_tuple_same_dim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 952\u001b[0m \u001b[39mif\u001b[39;00m com\u001b[39m.\u001b[39mis_null_slice(key):\n\u001b[1;32m 953\u001b[0m \u001b[39mcontinue\u001b[39;00m\n\u001b[0;32m--> 955\u001b[0m retval \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39;49m(retval, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mname)\u001b[39m.\u001b[39;49m_getitem_axis(key, axis\u001b[39m=\u001b[39;49mi)\n\u001b[1;32m 956\u001b[0m \u001b[39m# We should never have retval.ndim < self.ndim, as that should\u001b[39;00m\n\u001b[1;32m 957\u001b[0m \u001b[39m# be handled by the _getitem_lowerdim call above.\u001b[39;00m\n\u001b[1;32m 958\u001b[0m \u001b[39massert\u001b[39;00m retval\u001b[39m.\u001b[39mndim \u001b[39m==\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mndim\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexing.py:1332\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1329\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mhasattr\u001b[39m(key, \u001b[39m\"\u001b[39m\u001b[39mndim\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mand\u001b[39;00m key\u001b[39m.\u001b[39mndim \u001b[39m>\u001b[39m \u001b[39m1\u001b[39m:\n\u001b[1;32m 1330\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mCannot index with multidimensional key\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m-> 1332\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_getitem_iterable(key, axis\u001b[39m=\u001b[39;49maxis)\n\u001b[1;32m 1334\u001b[0m \u001b[39m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1335\u001b[0m \u001b[39mif\u001b[39;00m is_nested_tuple(key, labels):\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexing.py:1272\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_iterable\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1269\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_validate_key(key, axis)\n\u001b[1;32m 1271\u001b[0m \u001b[39m# A collection of keys\u001b[39;00m\n\u001b[0;32m-> 1272\u001b[0m keyarr, indexer \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_get_listlike_indexer(key, axis)\n\u001b[1;32m 1273\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mobj\u001b[39m.\u001b[39m_reindex_with_indexers(\n\u001b[1;32m 1274\u001b[0m {axis: [keyarr, indexer]}, copy\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m, allow_dups\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m\n\u001b[1;32m 1275\u001b[0m )\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexing.py:1462\u001b[0m, in \u001b[0;36m_LocIndexer._get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1459\u001b[0m ax \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mobj\u001b[39m.\u001b[39m_get_axis(axis)\n\u001b[1;32m 1460\u001b[0m axis_name \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mobj\u001b[39m.\u001b[39m_get_axis_name(axis)\n\u001b[0;32m-> 1462\u001b[0m keyarr, indexer \u001b[39m=\u001b[39m ax\u001b[39m.\u001b[39;49m_get_indexer_strict(key, axis_name)\n\u001b[1;32m 1464\u001b[0m \u001b[39mreturn\u001b[39;00m keyarr, indexer\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexes/base.py:5876\u001b[0m, in \u001b[0;36mIndex._get_indexer_strict\u001b[0;34m(self, key, axis_name)\u001b[0m\n\u001b[1;32m 5873\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 5874\u001b[0m keyarr, indexer, new_indexer \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_reindex_non_unique(keyarr)\n\u001b[0;32m-> 5876\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_raise_if_missing(keyarr, indexer, axis_name)\n\u001b[1;32m 5878\u001b[0m keyarr \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtake(indexer)\n\u001b[1;32m 5879\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(key, Index):\n\u001b[1;32m 5880\u001b[0m \u001b[39m# GH 42790 - Preserve name from an Index\u001b[39;00m\n", - "File \u001b[0;32m~/miniconda3/envs/spy/lib/python3.9/site-packages/pandas/core/indexes/base.py:5938\u001b[0m, in \u001b[0;36mIndex._raise_if_missing\u001b[0;34m(self, key, indexer, axis_name)\u001b[0m\n\u001b[1;32m 5935\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mKeyError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mNone of [\u001b[39m\u001b[39m{\u001b[39;00mkey\u001b[39m}\u001b[39;00m\u001b[39m] are in the [\u001b[39m\u001b[39m{\u001b[39;00maxis_name\u001b[39m}\u001b[39;00m\u001b[39m]\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m 5937\u001b[0m not_found \u001b[39m=\u001b[39m \u001b[39mlist\u001b[39m(ensure_index(key)[missing_mask\u001b[39m.\u001b[39mnonzero()[\u001b[39m0\u001b[39m]]\u001b[39m.\u001b[39munique())\n\u001b[0;32m-> 5938\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mKeyError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mnot_found\u001b[39m}\u001b[39;00m\u001b[39m not in index\u001b[39m\u001b[39m\"\u001b[39m)\n", - "\u001b[0;31mKeyError\u001b[0m: \"['xloc2', 'yloc2'] not in index\"" - ] - } - ], + "outputs": [], "source": [ "sgp.v1.TrodesPosV1.populate(trodes_key)" ] @@ -764,7 +850,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "64355919-a952-4e88-8b5a-5e678922ddde", "metadata": {}, "outputs": [ @@ -774,21 +860,23 @@ "\n", " \n", " \n", - " \n", - " \n", - " \n",
- " position_info_param_name \n", - " name for this set of parameters\n", - " | \n",
- " nwb_file_name \n", - " name of the NWB file\n", - " | \n",
- " interval_list_name \n", - " descriptive name of this interval list\n", - " |
---|---|---|
default_decoding | \n", - "CH6120211203_.nwb | \n", - "pos 0 valid times |
default_decoding | \n", - "CH6520211125_.nwb | \n", - "pos 0 valid times |
default_decoding | \n", - "CH6520211201_.nwb | \n", - "pos 0 valid times |
default | \n", - "chimi20200216_new_.nwb | \n", - "pos 1 valid times |
default_decoding | \n", - "chimi20200216_new_.nwb | \n", - "pos 1 valid times |
default_lfp | \n", - "chimi20200216_new_.nwb | \n", - "pos 1 valid times |
default | \n", - "fern20211007_.nwb | \n", - "pos 0 valid times |
default_decoding | \n", - "fern20211007_.nwb | \n", - "pos 0 valid times |
default | \n", - "fern20211007_.nwb | \n", - "pos 1 valid times |
default_decoding | \n", - "fern20211007_.nwb | \n", - "pos 1 valid times |
default | \n", - "fern20211007_.nwb | \n", - "pos 10 valid times |
default_decoding | \n", - "fern20211007_.nwb | \n", - "pos 10 valid times |
...
\n", - "Total: 1815
655645 rows × 6 columns
\n", + "267 rows × 7 columns
\n", "" ], "text/plain": [ - " head_position_x head_position_y head_orientation \\\n", - "time \n", - "1.581887e+09 91.051650 211.127050 2.680048 \n", - "1.581887e+09 91.039455 211.144123 3.003241 \n", - "1.581887e+09 91.027260 211.161196 3.008398 \n", - "1.581887e+09 91.015065 211.178268 3.012802 \n", - "1.581887e+09 91.002871 211.195341 3.017242 \n", - "... ... ... ... \n", - "1.581888e+09 182.158583 201.299625 -0.944304 \n", - "1.581888e+09 182.158583 201.296373 -0.942329 \n", - "1.581888e+09 182.158583 201.293121 -0.940357 \n", - "1.581888e+09 182.158583 201.289869 -0.953059 \n", - "1.581888e+09 182.158583 201.286617 -0.588081 \n", + " video_frame_ind position_x position_y orientation \\\n", + "time \n", + "1.687475e+09 0.0 22.250000 28.350000 0.905373 \n", + "1.687475e+09 1.0 22.250000 28.350000 0.905373 \n", + "1.687475e+09 2.0 22.250000 28.350000 0.905373 \n", + "1.687475e+09 3.0 22.233333 28.366667 0.906022 \n", + "1.687475e+09 4.0 22.216667 28.383333 0.906671 \n", + "... ... ... ... ... \n", + "1.687475e+09 262.0 23.766667 27.066667 0.850225 \n", + "1.687475e+09 263.0 23.933333 26.800000 0.841843 \n", + "1.687475e+09 264.0 23.983333 26.716667 0.839258 \n", + "1.687475e+09 265.0 24.016667 26.616667 0.836703 \n", + "1.687475e+09 266.0 24.033333 26.550000 0.835110 \n", "\n", - " head_velocity_x head_velocity_y head_speed \n", - "time \n", - "1.581887e+09 1.741550 2.301478 2.886139 \n", - "1.581887e+09 1.827555 2.333931 2.964320 \n", - "1.581887e+09 1.915800 2.366668 3.044898 \n", - "1.581887e+09 2.006286 2.399705 3.127901 \n", - "1.581887e+09 2.099012 2.433059 3.213352 \n", - "... ... ... ... \n", - "1.581888e+09 0.057520 -0.356012 0.360629 \n", - "1.581888e+09 0.053954 -0.356343 0.360404 \n", - "1.581888e+09 0.050477 -0.356407 0.359964 \n", - "1.581888e+09 0.047091 -0.356212 0.359312 \n", - "1.581888e+09 0.043796 -0.355764 0.358450 \n", + " velocity_x velocity_y speed \n", + "time \n", + "1.687475e+09 -0.148627 0.116866 0.189071 \n", + "1.687475e+09 -0.219948 0.162667 0.273565 \n", + "1.687475e+09 -0.298575 0.205042 0.362201 \n", + "1.687475e+09 -0.371837 0.233439 0.439041 \n", + "1.687475e+09 -0.424639 0.238911 0.487234 \n", + "... ... ... ... \n", + "1.687475e+09 2.738364 -3.998619 4.846400 \n", + "1.687475e+09 2.347307 -3.708857 4.389245 \n", + "1.687475e+09 1.907429 -3.237540 3.757652 \n", + "1.687475e+09 1.457185 -2.647347 3.021893 \n", + "1.687475e+09 1.040384 -2.021305 2.273340 \n", "\n", - "[655645 rows x 6 columns]" + "[267 rows x 7 columns]" ] }, - "execution_count": 28, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "upsampled_position_info = (\n", - " sgc.IntervalPositionInfo()\n", + " sgp.v1.TrodesPosV1()\n", " & {\n", " \"nwb_file_name\": nwb_copy_file_name,\n", - " \"interval_list_name\": \"pos 1 valid times\",\n", - " \"position_info_param_name\": \"default_decoding\",\n", + " \"position_info_param_name\": trodes_params_up_name,\n", " }\n", ").fetch1_dataframe()\n", "\n", @@ -1845,150 +1754,152 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "1a1f6d12-3199-4136-ab66-9ac80241d4b5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Text(0.5, 1.0, 'Upsampled Head Position')" + "Text(0.5, 1.0, 'Upsampled Position')" ] }, - "execution_count": 24, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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