diff --git a/docs/toc.yml b/docs/toc.yml index 21e973c..a4cd990 100644 --- a/docs/toc.yml +++ b/docs/toc.yml @@ -2,55 +2,66 @@ href: ../README.md - name: Linear Dynamical Systems -- name: Getting Started - href: ../examples/LinearDynamicalSystems/README.md -- name: Kinematics -- name: Simulated Data - href: ../examples/LinearDynamicalSystems/Kinematics/SimulatedData/README.md -- name: Zebrafish Centroid Tracking - href: ../examples/LinearDynamicalSystems/Kinematics/ZebrafishCentroidTracking/README.md -- name: Foraging Mouse - href: ../examples/LinearDynamicalSystems/Kinematics/ForagingMouse/README.md -- name: Optimizing Model Parameters for Foraging Mouse - href: ../examples/LinearDynamicalSystems/Kinematics/ModelOptimizationForagingMouse/README.md -- name: Forecasting Foraging Mouse Kinematics - href: ../examples/LinearDynamicalSystems/Kinematics/ForecastingForagingMouse/README.md -- name: Linear Regression -- name: Simulated Data - href: ../examples/LinearDynamicalSystems/LinearRegression/SimulatedData/README.md -- name: Receptive Field Simple Cell - href: ../examples/LinearDynamicalSystems/LinearRegression/ReceptiveFieldSimpleCell/README.md - + items: + - name: Kinematics + items: + - name: Simulated Data + href: ../examples/LinearDynamicalSystems/Kinematics/SimulatedData/README.md + - name: Zebrafish Centroid Tracking + href: ../examples/LinearDynamicalSystems/Kinematics/ZebrafishCentroidTracking/README.md + - name: Foraging Mouse + href: ../examples/LinearDynamicalSystems/Kinematics/ForagingMouse/README.md + - name: Optimizing Model Parameters for Foraging Mouse + href: ../examples/LinearDynamicalSystems/Kinematics/ModelOptimizationForagingMouse/README.md + - name: Forecasting Foraging Mouse Kinematics + href: ../examples/LinearDynamicalSystems/Kinematics/ForecastingForagingMouse/README.md + - name: Linear Regression + items: + - name: Simulated Data + href: ../examples/LinearDynamicalSystems/LinearRegression/SimulatedData/README.md + - name: Receptive Field Simple Cell + href: ../examples/LinearDynamicalSystems/LinearRegression/ReceptiveFieldSimpleCell/README.md + - name: Neural Latents + items: + - name: Estimating Parameters of LDS + href: ../examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/README.md + - name: Online Filtering + href: ../examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/README.md + - name: Hidden Markov Models -- name: Getting Started - href: ../examples/HiddenMarkovModels/README.md -- name: Simulated Data - href: ../examples/HiddenMarkovModels/SimulatedData/README.md -- name: Inferring Behavioral State from Kinematics - href: ../examples/HiddenMarkovModels/InferringBehavioralStateFromKinematics/README.md -- name: Extended Model Configuration - href: ../examples/HiddenMarkovModels/ExtendedModelConfiguration/README.md + items: + - name: Getting Started + href: ../examples/HiddenMarkovModels/README.md + - name: Simulated Data + href: ../examples/HiddenMarkovModels/SimulatedData/README.md + - name: Inferring Behavioral State from Kinematics + href: ../examples/HiddenMarkovModels/InferringBehavioralStateFromKinematics/README.md + - name: Extended Model Configuration + href: ../examples/HiddenMarkovModels/ExtendedModelConfiguration/README.md - name: Torch -- name: Linear Regression - href: ../examples/Torch/LinearRegression/README.md + items: + - name: Linear Regression + href: ../examples/Torch/LinearRegression/README.md -- name: Torch Models -- name: Custom PyTorch Model - href: ../examples/Torch/CustomPyTorchModel/README.md -- name: Pretrained Neural Network for Image Classification - href: ../examples/Torch/NeuralNetsPretrainedModel/README.md -- name: Downloading and Running a TorchHub Model - href: ../examples/Torch/NeuralNetsTorchHub/README.md -- name: Training a Neural Network Online - href: ../examples/Torch/NeuralNetsTrainedOnline/README.md + - name: Neural Networks + items: + - name: Exporting a PyTorch Model + href: ../examples/Torch/CustomPyTorchModel/README.md + - name: Running a Pretrained Neural Network for Image Classification + href: ../examples/Torch/NeuralNetsPretrainedModel/README.md + - name: Downloading and Running a TorchHub Model + href: ../examples/Torch/NeuralNetsTorchHub/README.md + - name: Training a Neural Network Online + href: ../examples/Torch/NeuralNetsTrainedOnline/README.md - name: Point Process Decoder -- name: Decode Position from Hippocampus using Sorted Spikes - href: ../examples/PointProcessDecoder/DecodePositionFromHippocampusSortedUnits/README.md -- name: Decode Position from Hippocampus using Clusterless Marks - href: ../examples/PointProcessDecoder/DecodePositionFromHippocampusClusterless/README.md -- name: Decode Position from Striatum using Sorted Spikes - href: ../examples/PointProcessDecoder/DecodePositionFromStriatumSortedUnits/README.md -- name: Classify Dynamics and Decode Position from Hippocampal Sorted Units - href: ../examples/PointProcessDecoder/ClassifyPositionFromHippocampusSortedUnits/README.md \ No newline at end of file + items: + - name: Decode Position from Hippocampus using Sorted Spikes + href: ../examples/PointProcessDecoder/DecodePositionFromHippocampusSortedUnits/README.md + - name: Decode Position from Hippocampus using Clusterless Marks + href: ../examples/PointProcessDecoder/DecodePositionFromHippocampusClusterless/README.md + - name: Decode Position from Striatum using Sorted Spikes + href: ../examples/PointProcessDecoder/DecodePositionFromStriatumSortedUnits/README.md + - name: Classify Dynamics and Decode Position from Hippocampal Sorted Units + href: ../examples/PointProcessDecoder/ClassifyPositionFromHippocampusSortedUnits/README.md \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Bonsai.config b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Bonsai.config new file mode 100644 index 0000000..e23fc91 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Bonsai.config @@ -0,0 +1,134 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/NuGet.config b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/NuGet.config new file mode 100644 index 0000000..aa5beec --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/NuGet.config @@ -0,0 +1,5 @@ + + + + + diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Setup.ps1 b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Setup.ps1 new file mode 100644 index 0000000..76b5c46 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Setup.ps1 @@ -0,0 +1,21 @@ +Push-Location $PSScriptRoot +if (!(Test-Path "./Bonsai.exe")) { + $release = "https://github.com/bonsai-rx/bonsai/releases/latest/download/Bonsai.zip" + $configPath = "./Bonsai.config" + if (Test-Path $configPath) { + [xml]$config = Get-Content $configPath + $bootstrapper = $config.PackageConfiguration.Packages.Package.where{$_.id -eq 'Bonsai'} + if ($bootstrapper) { + $version = $bootstrapper.version + $release = "https://github.com/bonsai-rx/bonsai/releases/download/$version/Bonsai.zip" + } + } + Invoke-WebRequest $release -OutFile "temp.zip" + Move-Item -Path "NuGet.config" "temp.config" -ErrorAction SilentlyContinue + Expand-Archive "temp.zip" -DestinationPath "." -Force + Move-Item -Path "temp.config" "NuGet.config" -Force -ErrorAction SilentlyContinue + Remove-Item -Path "temp.zip" + Remove-Item -Path "Bonsai32.exe" +} +& .\Bonsai.exe --no-editor +Pop-Location \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Setup.sh b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Setup.sh new file mode 100644 index 0000000..941d850 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/Setup.sh @@ -0,0 +1,41 @@ +#! /bin/bash + +SETUP_SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" + +DEFAULT_VERSION="latest" +VERSION="$DEFAULT_VERSION" + +while [[ "$#" -gt 0 ]]; do + case $1 in + --version) VERSION="$2"; shift ;; + *) echo "Unknown parameter passed: $1"; exit 1 ;; + esac + shift +done + +echo "Setting up Bonsai v=$VERSION environment..." + +if [ ! -f "$SETUP_SCRIPT_DIR/Bonsai.exe" ]; then + CONFIG="$SETUP_SCRIPT_DIR/Bonsai.config" + if [ -f "$CONFIG" ]; then + DETECTED=$(xmllint --xpath '//PackageConfiguration/Packages/Package[@id="Bonsai"]/@version' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + echo "Version detected v=$DETECTED." + RELEASE="https://github.com/bonsai-rx/bonsai/releases/download/$DETECTED/Bonsai.zip" + else + if [ $VERSION = "latest" ]; then + RELEASE="https://github.com/bonsai-rx/bonsai/releases/latest/download/Bonsai.zip" + else + RELEASE="https://github.com/bonsai-rx/bonsai/releases/download/$VERSION/Bonsai.zip" + fi + fi + echo "Download URL: $RELEASE" + wget $RELEASE -O "$SETUP_SCRIPT_DIR/temp.zip" + mv -f "$SETUP_SCRIPT_DIR/NuGet.config" "$SETUP_SCRIPT_DIR/temp.config" + unzip -d "$SETUP_SCRIPT_DIR" -o "$SETUP_SCRIPT_DIR/temp.zip" + mv -f "$SETUP_SCRIPT_DIR/temp.config" "$SETUP_SCRIPT_DIR/NuGet.config" + rm -rf "$SETUP_SCRIPT_DIR/temp.zip" + rm -rf "$SETUP_SCRIPT_DIR/Bonsai32.exe" +fi + +source "$SETUP_SCRIPT_DIR/activate" +source "$SETUP_SCRIPT_DIR/run" --no-editor diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/activate b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/activate new file mode 100644 index 0000000..ddf75f3 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/activate @@ -0,0 +1,15 @@ +#!/bin/bash +# activate.sh +if [[ -v BONSAI_EXE_PATH ]]; then + echo "Error! Cannot have multiple bonsai environments activated at the same time. Please deactivate the current environment before activating the new one." + return +fi +BONSAI_ENV_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" +export BONSAI_ENV_DIR +export BONSAI_EXE_PATH="$BONSAI_ENV_DIR/Bonsai.exe" +export ORIGINAL_PS1="$PS1" +export PS1="($(basename "$BONSAI_ENV_DIR")) $PS1" +alias bonsai='source "$BONSAI_ENV_DIR"/run' +alias bonsai-clean='GTK_DATA_PREFIX= source "$BONSAI_ENV_DIR"/run' +alias deactivate='source "$BONSAI_ENV_DIR"/deactivate' +echo "Activated bonsai environment in $BONSAI_ENV_DIR" \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/deactivate b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/deactivate new file mode 100644 index 0000000..43233d9 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/deactivate @@ -0,0 +1,8 @@ +#!/bin/bash +unset BONSAI_EXE_PATH +export PS1="$ORIGINAL_PS1" +unset ORIGINAL_PS1 +unalias bonsai +unalias bonsai-clean +unalias deactivate +echo "Deactivated bonsai environment." \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/run b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/run new file mode 100644 index 0000000..bffd6cf --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.bonsai/run @@ -0,0 +1,58 @@ +#!/bin/bash +# run.sh + +SETUP_SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" +CONFIG="$SETUP_SCRIPT_DIR/Bonsai.config" + +cleanup() { + update_paths_to_windows +} + +update_paths_to_linux() { + ASSEMBLYLOCATIONS=$(xmllint --xpath '//PackageConfiguration/AssemblyLocations/AssemblyLocation/@location' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for ASSEMBLYLOCATION in $ASSEMBLYLOCATIONS; do + NEWASSEMBLYLOCATION="${ASSEMBLYLOCATION//\\/\/}" + xmlstarlet edit --inplace --update "/PackageConfiguration/AssemblyLocations/AssemblyLocation[@location='$ASSEMBLYLOCATION']/@location" --value "$NEWASSEMBLYLOCATION" "$CONFIG" + done + + LIBRARYFOLDERS=$(xmllint --xpath '//PackageConfiguration/LibraryFolders/LibraryFolder/@path' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for LIBRARYFOLDER in $LIBRARYFOLDERS; do + NEWLIBRARYFOLDER="${LIBRARYFOLDER//\\/\/}" + xmlstarlet edit --inplace --update "//PackageConfiguration/LibraryFolders/LibraryFolder[@path='$LIBRARYFOLDER']/@path" --value "$NEWLIBRARYFOLDER" "$CONFIG" + done +} + +update_paths_to_windows() { + ASSEMBLYLOCATIONS=$(xmllint --xpath '//PackageConfiguration/AssemblyLocations/AssemblyLocation/@location' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for ASSEMBLYLOCATION in $ASSEMBLYLOCATIONS; do + NEWASSEMBLYLOCATION="${ASSEMBLYLOCATION//\//\\}" + xmlstarlet edit --inplace --update "/PackageConfiguration/AssemblyLocations/AssemblyLocation[@location='$ASSEMBLYLOCATION']/@location" --value "$NEWASSEMBLYLOCATION" "$CONFIG" + done + + LIBRARYFOLDERS=$(xmllint --xpath '//PackageConfiguration/LibraryFolders/LibraryFolder/@path' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for LIBRARYFOLDER in $LIBRARYFOLDERS; do + NEWLIBRARYFOLDER="${LIBRARYFOLDER//\//\\}" + xmlstarlet edit --inplace --update "//PackageConfiguration/LibraryFolders/LibraryFolder[@path='$LIBRARYFOLDER']/@path" --value "$NEWLIBRARYFOLDER" "$CONFIG" + done +} + +if [[ -v BONSAI_EXE_PATH ]]; then + if [ ! -f "$BONSAI_EXE_PATH" ]; then + bash "$BONSAI_ENV_DIR"/Setup.sh + bash "$BONSAI_ENV_DIR"/run "$@" + else + BONSAI_VERSION=$(xmllint --xpath "//PackageConfiguration/Packages/Package[@id='Bonsai']/@version" "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + if [[ -z ${BONSAI_VERSION+x} ]] && [ "$BONSAI_VERSION" \< "2.8.4" ]; then + echo "Updating paths to Linux format..." + trap cleanup EXIT INT TERM + update_paths_to_linux + mono "$BONSAI_EXE_PATH" "$@" + cleanup + else + mono "$BONSAI_EXE_PATH" "$@" + fi + fi +else + echo "BONSAI_EXE_PATH is not set. Please set the path to the Bonsai executable." + return +fi \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.python-version b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/EstimateParameters.bonsai b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/EstimateParameters.bonsai new file mode 100644 index 0000000..46f1c88 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/EstimateParameters.bonsai @@ -0,0 +1,277 @@ + + + + + + LoadData + + + + + ../../../../datasets/sub-Jenkins_ses-small_desc-train_behavior+ecephys.bin + 0 + 0 + 142 + 0 + F64 + RowMajor + + + + + + + + + + + + + + 142 + -1 + + + + + + + 1 + 0 + + + + + SpikeCounts + + + + + + + + + + + + + + LearnParameters + + + + SpikeCounts + + + + 10 + 10 + 0.1 + true + true + true + true + true + true + true + + + + ExpectationMaximization + true + + + + + + + + + Source1 + + + Finished + + + + + + + + + + + Parameters + + + KalmanFilterParameters + + + + Float64 + + + + + + + + + + + + KalmanFilterModel + + + + + + + + + + + + + + + InferNeuralLatents + + + + SpikeCounts + + + KalmanFilterModel + + + + + + + + + + + + + + + + + ReplayState + + + + Source1 + + + Mean + + + + 0 + + + + it.unsqueeze(0) + + + Covariance + + + + 0 + + + + it.unsqueeze(0) + + + + + + + PT0S + PT0.01S + + + + + + + + + + + + + + Float32 + [[-8.737335, 0.0842269, 0.009232007, -0.0008691379, -0.01574879, -0.006062153, 0.0008153673, -0.001463936, 0.0005580065, -7.526268E-06]] + [[[0.009540861, 0.001642221, -0.0003729272, 0.0001364285, -0.0003722429, -0.0001043696, 3.902293E-05, -2.020181E-05, 1.850796E-05, 1.132543E-05], [0.001642221, 0.005607077, 0.0002884019, 5.757339E-05, -1.882871E-05, 1.61614E-06, 7.674043E-06, -4.401983E-06, -1.133E-06, 4.295156E-07], [-0.0003729272, 0.0002884019, 0.00456911, -9.982559E-05, -3.125695E-07, -1.271387E-06, -1.342541E-06, 2.8035E-06, 5.200116E-07, 2.058647E-08], [0.0001364285, 5.757339E-05, -9.982559E-05, 0.003710471, 5.307371E-07, 4.996915E-07, 3.508996E-06, -1.049549E-07, 9.021393E-07, -2.722985E-07], [-0.0003722429, -1.882871E-05, -3.125695E-07, 5.307371E-07, 0.003082175, -4.211043E-06, 1.827337E-06, -8.512937E-07, 4.143237E-07, 1.848511E-07], [-0.0001043696, 1.61614E-06, -1.271387E-06, 4.996915E-07, -4.211043E-06, 0.001288361, 1.71188E-06, -1.227383E-06, 2.295068E-07, -1.284648E-07], [3.902293E-05, 7.674043E-06, -1.342541E-06, 3.508996E-06, 1.827337E-06, 1.71188E-06, 0.0005039083, -2.359678E-07, -8.154034E-08, -1.028429E-07], [-2.020181E-05, -4.401983E-06, 2.8035E-06, -1.049549E-07, -8.512937E-07, -1.227383E-06, -2.359678E-07, 0.0004041222, -5.05107E-09, 1.07337E-08], [1.850796E-05, -1.133E-06, 5.200116E-07, 9.021393E-07, 4.143237E-07, 2.295068E-07, -8.154034E-08, -5.05107E-09, 0.0001370257, -3.074566E-08], [1.132543E-05, 4.295156E-07, 2.058647E-08, -2.722985E-07, 1.848511E-07, -1.284648E-07, -1.028429E-07, 1.07337E-08, -3.074566E-08, 4.862578E-05]]] + + + + + + + + + + + + + + + + + + + + + + + KalmanFilterModel + + + + + + + + + + + + + + + + + + + + + + + NeuralLatents + true + + + + + + + + + + \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/NeuralLatentsEstimatingParameters.gif b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/NeuralLatentsEstimatingParameters.gif new file mode 100644 index 0000000..cc8e93b Binary files /dev/null and b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/NeuralLatentsEstimatingParameters.gif differ diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/README.md b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/README.md new file mode 100644 index 0000000..4639845 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/README.md @@ -0,0 +1,36 @@ +# Estimating Parameters of Kalman Filter + +In the following example, you will see how the `Bonsai.ML.Lds.Torch` package can be used to estimate the parameters of a Kalman filter and perform acausal smoothing of neural spike counts. + +### Download the Dataset + +To run the example, you need to download the dataset from DANDI and transform the raw spike data into binned spike counts. We provide a convenient python script and `uv` environment to easily download and transform the raw data. First, make sure `uv` is installed on your computer, which you can do by following the guide [here](https://docs.astral.sh/uv/getting-started/installation/). + +Next, open up a terminal and run the following commands. + +```bash +cd examples/Torch.LDS/NeuralLatents/EstimatingParameters +uv run download_data.py +``` + +When the script finishes, you should see 2 different datasets saved, one for training and the other for testing. + +### Running the Workflow + +The example workflow is shown here: + +:::workflow +![Estimate Parameters](EstimateParameters.bonsai) +::: + +The first group node, `LoadData`, loads the training dataset and converts it into a `Tensor` object. It then reshapes it so that the dimensions are `time` x `neurons` and passes it to a `ReplaySubject` called `SpikeCounts` to be used in the downstream processing pipeline. In this example, the entire batch of data is loaded at once. + +The `LoadModel` group node uses the `CreateKalmanFilter` node to specify the model. We leave the optional parameters blank. We set the `NumStates` to `10` and the `NumObservations` to `142` to match the number of spiking neurons contained in the dataset. This then feeds into a `BehaviorSubject` node called `KalmanFilterModel` for use in other parts of the workflow. + +In the `LearnParameters` group node, the `SpikeCounts` are fed into the `ExpectationMaximization` node which uses the EM algorithm to iteratively optimize the models selected parameters given the spike count data. The EM algorithm will iterate until it reaches the `MaxIterations` count or until the algorithm converges to less than the `Tolerance`. After some time, the algorithm will finish and the output will be passed to a `BehaviorSubject` called `ExpectationMaximizationResult` to trigger the inference procedure. + +The last group node, `InferNeuralLatents`, contains the inference pipeline and starts when the `ExpectationMaximizationResult` is emitted. The `Filter` step runs causal filtering over the entire batch of `SpikeCounts`. The `UpdatedFilterResult` is then run through the `Smooth` step, which runs acausal smoothing from the last data point all the way back to the initial data point. This `UpdatedSmoothedResult` is then fed into the `Orthogonalize` node, which essentially node extracts the principal, orthogonal components of the measurement function and projects the state mean and covariance into the orthogonalized space to focus only on the most informative directions. The `OrthogonalizedResult` is then decomposed into individual observations over time and gated to produce values at a frequency of a ~100Hz. + +When you start the workflow, you should see a window pop up with the title `NeuralLatents`. As the EM algorithm runs, nothing will be displayed at first. After 10 iterations, the EM algorithm will finish, and once the data are filtered, smoothed, and orthogonalized, you will start to see the inferred latents displayed in the chart. This is how it should appear: + +![](./NeuralLatentsEstimatingParameters.gif) diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/download_data.py b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/download_data.py new file mode 100644 index 0000000..2582820 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/download_data.py @@ -0,0 +1,59 @@ +# Import libraries +import numpy as np +import remfile, h5py +from dandi.dandiapi import DandiAPIClient +from pynwb import NWBHDF5IO +import os + +# set base directory to save data +base_dir = os.path.join(os.path.realpath(os.path.dirname(__file__)), "..", "..", "..", "..", "datasets") + +# dandi dataset info +dandiset_ID = "000140" +dandi_filenames = [ + "sub-Jenkins/sub-Jenkins_ses-small_desc-train_behavior+ecephys.nwb", + "sub-Jenkins/sub-Jenkins_ses-small_desc-test_ecephys.nwb" +] + +for dandi_filepath in dandi_filenames: + + print(f"Downloading and processing {dandi_filepath}...") + + # download data using remfile and dandi + with DandiAPIClient() as client: + asset = client.get_dandiset(dandiset_ID, + "draft").get_asset_by_path(dandi_filepath) + s3_path = asset.get_content_url(follow_redirects=1, strip_query=True) + cache = remfile.DiskCache(os.path.join(base_dir, "remfile_cache")) + rf = remfile.File(s3_path, disk_cache=cache) + with h5py.File(rf, "r") as h: + with NWBHDF5IO(file=h, mode="r") as io: + nwbfile = io.read() + # extract spike sorted units dataframe + units_df = nwbfile.units.to_dataframe() + + print(f"Data downloaded. Processing spikes...") + + # bin spikes + n_clusters = units_df.shape[0] + bin_size = 0.02 + + spike_times = [units_df.iloc[n]['spike_times'] for n in range(n_clusters)] + t_max = max(max(st) for st in spike_times if len(st) > 0) + + bin_edges = np.arange(0, t_max + bin_size, bin_size) + bin_centers = (bin_edges[1:] + bin_edges[:-1]) / 2 + n_bins = len(bin_edges) - 1 + + spike_counts = np.zeros((n_clusters, n_bins), dtype=int) + + for n, spikes in enumerate(spike_times): + spike_counts[n], _ = np.histogram(spikes, bins=bin_edges) + + # transform binned spikes using square-root transform + spike_counts = np.sqrt(spike_counts + 0.5) + + output_filename = dandi_filepath.split("/")[-1].replace(".nwb", ".bin") + spike_counts.astype(float).tofile(os.path.join(base_dir, output_filename)) + + print(f"Processed spikes saved to {os.path.realpath(os.path.join(base_dir, output_filename))}") \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/pyproject.toml b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/pyproject.toml new file mode 100644 index 0000000..29a08db --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/pyproject.toml @@ -0,0 +1,13 @@ +[project] +name = "estimatingneurallatents" +version = "0.1.0" +description = "Example for estimating neural latents" +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "dandi>=0.71.4", + "h5py>=3.14.0", + "numpy>=2.3.3", + "pynwb>=3.1.2", + "remfile>=0.1.13", +] diff --git a/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/uv.lock b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/uv.lock new file mode 100644 index 0000000..ba10581 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/EstimatingParameters/uv.lock @@ -0,0 +1,1833 @@ +version = 1 +revision = 2 +requires-python = ">=3.12" 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a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Bonsai.config b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Bonsai.config new file mode 100644 index 0000000..bafd848 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Bonsai.config @@ -0,0 +1,136 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/NuGet.config b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/NuGet.config new file mode 100644 index 0000000..aa5beec --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/NuGet.config @@ -0,0 +1,5 @@ + + + + + diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Setup.ps1 b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Setup.ps1 new file mode 100644 index 0000000..76b5c46 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Setup.ps1 @@ -0,0 +1,21 @@ +Push-Location $PSScriptRoot +if (!(Test-Path "./Bonsai.exe")) { + $release = "https://github.com/bonsai-rx/bonsai/releases/latest/download/Bonsai.zip" + $configPath = "./Bonsai.config" + if (Test-Path $configPath) { + [xml]$config = Get-Content $configPath + $bootstrapper = $config.PackageConfiguration.Packages.Package.where{$_.id -eq 'Bonsai'} + if ($bootstrapper) { + $version = $bootstrapper.version + $release = "https://github.com/bonsai-rx/bonsai/releases/download/$version/Bonsai.zip" + } + } + Invoke-WebRequest $release -OutFile "temp.zip" + Move-Item -Path "NuGet.config" "temp.config" -ErrorAction SilentlyContinue + Expand-Archive "temp.zip" -DestinationPath "." -Force + Move-Item -Path "temp.config" "NuGet.config" -Force -ErrorAction SilentlyContinue + Remove-Item -Path "temp.zip" + Remove-Item -Path "Bonsai32.exe" +} +& .\Bonsai.exe --no-editor +Pop-Location \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Setup.sh b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Setup.sh new file mode 100644 index 0000000..941d850 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/Setup.sh @@ -0,0 +1,41 @@ +#! /bin/bash + +SETUP_SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" + +DEFAULT_VERSION="latest" +VERSION="$DEFAULT_VERSION" + +while [[ "$#" -gt 0 ]]; do + case $1 in + --version) VERSION="$2"; shift ;; + *) echo "Unknown parameter passed: $1"; exit 1 ;; + esac + shift +done + +echo "Setting up Bonsai v=$VERSION environment..." + +if [ ! -f "$SETUP_SCRIPT_DIR/Bonsai.exe" ]; then + CONFIG="$SETUP_SCRIPT_DIR/Bonsai.config" + if [ -f "$CONFIG" ]; then + DETECTED=$(xmllint --xpath '//PackageConfiguration/Packages/Package[@id="Bonsai"]/@version' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + echo "Version detected v=$DETECTED." + RELEASE="https://github.com/bonsai-rx/bonsai/releases/download/$DETECTED/Bonsai.zip" + else + if [ $VERSION = "latest" ]; then + RELEASE="https://github.com/bonsai-rx/bonsai/releases/latest/download/Bonsai.zip" + else + RELEASE="https://github.com/bonsai-rx/bonsai/releases/download/$VERSION/Bonsai.zip" + fi + fi + echo "Download URL: $RELEASE" + wget $RELEASE -O "$SETUP_SCRIPT_DIR/temp.zip" + mv -f "$SETUP_SCRIPT_DIR/NuGet.config" "$SETUP_SCRIPT_DIR/temp.config" + unzip -d "$SETUP_SCRIPT_DIR" -o "$SETUP_SCRIPT_DIR/temp.zip" + mv -f "$SETUP_SCRIPT_DIR/temp.config" "$SETUP_SCRIPT_DIR/NuGet.config" + rm -rf "$SETUP_SCRIPT_DIR/temp.zip" + rm -rf "$SETUP_SCRIPT_DIR/Bonsai32.exe" +fi + +source "$SETUP_SCRIPT_DIR/activate" +source "$SETUP_SCRIPT_DIR/run" --no-editor diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/activate b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/activate new file mode 100644 index 0000000..ddf75f3 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/activate @@ -0,0 +1,15 @@ +#!/bin/bash +# activate.sh +if [[ -v BONSAI_EXE_PATH ]]; then + echo "Error! Cannot have multiple bonsai environments activated at the same time. Please deactivate the current environment before activating the new one." + return +fi +BONSAI_ENV_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" +export BONSAI_ENV_DIR +export BONSAI_EXE_PATH="$BONSAI_ENV_DIR/Bonsai.exe" +export ORIGINAL_PS1="$PS1" +export PS1="($(basename "$BONSAI_ENV_DIR")) $PS1" +alias bonsai='source "$BONSAI_ENV_DIR"/run' +alias bonsai-clean='GTK_DATA_PREFIX= source "$BONSAI_ENV_DIR"/run' +alias deactivate='source "$BONSAI_ENV_DIR"/deactivate' +echo "Activated bonsai environment in $BONSAI_ENV_DIR" \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/deactivate b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/deactivate new file mode 100644 index 0000000..43233d9 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/deactivate @@ -0,0 +1,8 @@ +#!/bin/bash +unset BONSAI_EXE_PATH +export PS1="$ORIGINAL_PS1" +unset ORIGINAL_PS1 +unalias bonsai +unalias bonsai-clean +unalias deactivate +echo "Deactivated bonsai environment." \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/run b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/run new file mode 100644 index 0000000..bffd6cf --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.bonsai/run @@ -0,0 +1,58 @@ +#!/bin/bash +# run.sh + +SETUP_SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" +CONFIG="$SETUP_SCRIPT_DIR/Bonsai.config" + +cleanup() { + update_paths_to_windows +} + +update_paths_to_linux() { + ASSEMBLYLOCATIONS=$(xmllint --xpath '//PackageConfiguration/AssemblyLocations/AssemblyLocation/@location' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for ASSEMBLYLOCATION in $ASSEMBLYLOCATIONS; do + NEWASSEMBLYLOCATION="${ASSEMBLYLOCATION//\\/\/}" + xmlstarlet edit --inplace --update "/PackageConfiguration/AssemblyLocations/AssemblyLocation[@location='$ASSEMBLYLOCATION']/@location" --value "$NEWASSEMBLYLOCATION" "$CONFIG" + done + + LIBRARYFOLDERS=$(xmllint --xpath '//PackageConfiguration/LibraryFolders/LibraryFolder/@path' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for LIBRARYFOLDER in $LIBRARYFOLDERS; do + NEWLIBRARYFOLDER="${LIBRARYFOLDER//\\/\/}" + xmlstarlet edit --inplace --update "//PackageConfiguration/LibraryFolders/LibraryFolder[@path='$LIBRARYFOLDER']/@path" --value "$NEWLIBRARYFOLDER" "$CONFIG" + done +} + +update_paths_to_windows() { + ASSEMBLYLOCATIONS=$(xmllint --xpath '//PackageConfiguration/AssemblyLocations/AssemblyLocation/@location' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for ASSEMBLYLOCATION in $ASSEMBLYLOCATIONS; do + NEWASSEMBLYLOCATION="${ASSEMBLYLOCATION//\//\\}" + xmlstarlet edit --inplace --update "/PackageConfiguration/AssemblyLocations/AssemblyLocation[@location='$ASSEMBLYLOCATION']/@location" --value "$NEWASSEMBLYLOCATION" "$CONFIG" + done + + LIBRARYFOLDERS=$(xmllint --xpath '//PackageConfiguration/LibraryFolders/LibraryFolder/@path' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for LIBRARYFOLDER in $LIBRARYFOLDERS; do + NEWLIBRARYFOLDER="${LIBRARYFOLDER//\//\\}" + xmlstarlet edit --inplace --update "//PackageConfiguration/LibraryFolders/LibraryFolder[@path='$LIBRARYFOLDER']/@path" --value "$NEWLIBRARYFOLDER" "$CONFIG" + done +} + +if [[ -v BONSAI_EXE_PATH ]]; then + if [ ! -f "$BONSAI_EXE_PATH" ]; then + bash "$BONSAI_ENV_DIR"/Setup.sh + bash "$BONSAI_ENV_DIR"/run "$@" + else + BONSAI_VERSION=$(xmllint --xpath "//PackageConfiguration/Packages/Package[@id='Bonsai']/@version" "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + if [[ -z ${BONSAI_VERSION+x} ]] && [ "$BONSAI_VERSION" \< "2.8.4" ]; then + echo "Updating paths to Linux format..." + trap cleanup EXIT INT TERM + update_paths_to_linux + mono "$BONSAI_EXE_PATH" "$@" + cleanup + else + mono "$BONSAI_EXE_PATH" "$@" + fi + fi +else + echo "BONSAI_EXE_PATH is not set. Please set the path to the Bonsai executable." + return +fi \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.python-version b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/OnlineFiltering.bonsai b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/OnlineFiltering.bonsai new file mode 100644 index 0000000..b5ffb3a --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/OnlineFiltering.bonsai @@ -0,0 +1,139 @@ + + + + + + LoadData + + + + + ../../../../datasets/sub-Jenkins_ses-small_desc-test_ecephys.bin + 0 + 100 + 142 + 1 + F64 + ColumnMajor + + + + + + + + + + + + it.squeeze(null).unsqueeze(0) + + + SpikeCounts + + + + + + + + + + + + LoadModel + + + + + /home/nicholas/machinelearning/docs/examples/datasets/NeuralLatents + Float64 + + + + + Float64 + + + + + + + + + + + + KalmanFilterModel + + + + + + + + + + InferNeuralLatents + + + + SpikeCounts + + + KalmanFilterModel + + + + + + + + + + + + + + KalmanFilterModel + + + + + + + + + + + + + + + + + + + + + NeuralLatents + true + + + + + + + + + + \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/README.md b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/README.md new file mode 100644 index 0000000..43f34f5 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/README.md @@ -0,0 +1,42 @@ +# Inferring Neural Latents using Online Kalman Filtering + +In the following example, you will see how the `Bonsai.ML.Lds.Torch` package can be used for inferring neural latents online using a Kalman filter from binned spike counts. + +### Download the Dataset + +To run the example, you need to download the dataset from DANDI and transform the raw spike data into binned spike counts. We provide a convenient python script and `uv` environment to easily download and transform the raw data. First, make sure `uv` is installed on your computer, which you can do by following the guide [here](https://docs.astral.sh/uv/getting-started/installation/). + +Next, open up a terminal and run the following commands. + +```bash +cd examples/Torch/NeuralLatents/OnlineFiltering +uv run download_data.py +``` + +When the script finishes, you should see 2 different datasets saved, one for training and the other for testing. + +Next, run the python script to train the model on the training dataset and save the parameters of the model to disk. + +```bash +uv run train_model.py +``` + +You can change the training procedure by passing parameters to the script. By default, this script will run 100 iterations, which can take several hours. You may want to consider changing this amount depending on your needs. + +### Running the Workflow + +The example workflow is shown here: + +:::workflow +![Online Filtering of Neural Latents](OnlineFiltering.bonsai) +::: + +The first group node, `LoadData`, loads the testing dataset and produces a sequence of binned spike counts, one spike count vector for each time point. Each spike count vector gets converted into a `Tensor` object and then reshaped into a column vector of `time` x `neurons` (in this case, time is `1`). This data then feeds into a `PublishSubject` called `SpikeCounts` to be used in the downstream processing pipeline. + +The `LoadModel` group node uses the `CreateKalmanFilter` node to specify the model. We leave most of the optional parameters blank, but use `0.01` and `0.1` as our initial guesses of the `MeasurementNoiseVariance` and `ProcessNoiseVariance`, respectively. We set the `NumStates` to `10` and the `NumObservations` to `142` to match the number of spiking neurons contained in the dataset. + +In the `LearnParameters` group node, the `SpikeCounts` are fed into `Buffer`, which will collect the spike counts into a small batch of `1000`. Realistically, you would want to increase the size of this batch to include more data when running the EM algorithm. The sequence completes once the first batch is fed into the `ExpectationMaximization` node, which uses the EM algorithm to iteratively optimize the models selected parameters given the batch of spike count data. In this example, all the model parameters are estimated, but we set a very small number of iterations and large tolerance. Again, in a real experiment, you would likely need to increase the number of iterations to get accurate estimates. The EM algorithm will iterate until it reaches the `MaxIterations` count or until the algorithm converges to less than the `Tolerance`. After some time, the algorithm will finish and the output will be passed to a `BehaviorSubject` called `ExpectationMaximizationResult` to trigger the inference procedure. + +The last group node, `InferNeuralLatents`, contains the inference pipeline and starts when the `ExpectationMaximizationResult` is emitted. The `Filter` step runs causal filtering over each new data point it observes from the `SpikeCounts` subject. This output is fed into the `Orthogonalize` node, which extracts the principal components of the measurement function and projects the state mean and covariance into the orthogonalized space. + +When you start the workflow, a window will pop up with the title `NeuralLatents`. As the EM algorithm runs, nothing will be displayed at first. After some time (~1 min), the EM algorithm will finish, and you will start to see the filtered latents displayed in the chart. \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/download_data.py b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/download_data.py new file mode 100644 index 0000000..2582820 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/download_data.py @@ -0,0 +1,59 @@ +# Import libraries +import numpy as np +import remfile, h5py +from dandi.dandiapi import DandiAPIClient +from pynwb import NWBHDF5IO +import os + +# set base directory to save data +base_dir = os.path.join(os.path.realpath(os.path.dirname(__file__)), "..", "..", "..", "..", "datasets") + +# dandi dataset info +dandiset_ID = "000140" +dandi_filenames = [ + "sub-Jenkins/sub-Jenkins_ses-small_desc-train_behavior+ecephys.nwb", + "sub-Jenkins/sub-Jenkins_ses-small_desc-test_ecephys.nwb" +] + +for dandi_filepath in dandi_filenames: + + print(f"Downloading and processing {dandi_filepath}...") + + # download data using remfile and dandi + with DandiAPIClient() as client: + asset = client.get_dandiset(dandiset_ID, + "draft").get_asset_by_path(dandi_filepath) + s3_path = asset.get_content_url(follow_redirects=1, strip_query=True) + cache = remfile.DiskCache(os.path.join(base_dir, "remfile_cache")) + rf = remfile.File(s3_path, disk_cache=cache) + with h5py.File(rf, "r") as h: + with NWBHDF5IO(file=h, mode="r") as io: + nwbfile = io.read() + # extract spike sorted units dataframe + units_df = nwbfile.units.to_dataframe() + + print(f"Data downloaded. Processing spikes...") + + # bin spikes + n_clusters = units_df.shape[0] + bin_size = 0.02 + + spike_times = [units_df.iloc[n]['spike_times'] for n in range(n_clusters)] + t_max = max(max(st) for st in spike_times if len(st) > 0) + + bin_edges = np.arange(0, t_max + bin_size, bin_size) + bin_centers = (bin_edges[1:] + bin_edges[:-1]) / 2 + n_bins = len(bin_edges) - 1 + + spike_counts = np.zeros((n_clusters, n_bins), dtype=int) + + for n, spikes in enumerate(spike_times): + spike_counts[n], _ = np.histogram(spikes, bins=bin_edges) + + # transform binned spikes using square-root transform + spike_counts = np.sqrt(spike_counts + 0.5) + + output_filename = dandi_filepath.split("/")[-1].replace(".nwb", ".bin") + spike_counts.astype(float).tofile(os.path.join(base_dir, output_filename)) + + print(f"Processed spikes saved to {os.path.realpath(os.path.join(base_dir, output_filename))}") \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/pyproject.toml b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/pyproject.toml new file mode 100644 index 0000000..8ae6f75 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/pyproject.toml @@ -0,0 +1,18 @@ +[project] +name = "estimatingneurallatents" +version = "0.1.0" +description = "Example for estimating neural latents" +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "dandi>=0.71.4", + "h5py>=3.14.0", + "numpy>=2.3.3", + "pynwb>=3.1.2", + "remfile>=0.1.13", + "ssm", + "torch>=2.8.0", +] + +[tool.uv.sources] +ssm = { git = "https://github.com/ncguilbeault/lds_python", rev = "75e3e5e92ce6344009b62a5034db49b238db63ef" } diff --git a/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/train_model.py b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/train_model.py new file mode 100644 index 0000000..02c4302 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/OnlineFiltering/train_model.py @@ -0,0 +1,103 @@ +import numpy as np +import ssm.learning +import os +import argparse +import leb128 + +def convert_type(array): + match array.dtype: + case np.uint8: + return 0 + case np.int8: + return 1 + case np.int16: + return 2 + case np.int32: + return 3 + case np.int64: + return 4 + case np.float16: + return 5 + case np.float32: + return 6 + case np.float64: + return 7 + case np.bool_: + return 11 + case _: + return 4711 + +def save_to_tensor(array, filename): + with open(filename, "wb") as f: + f.write(leb128.u.encode(convert_type(array))) + f.write(leb128.u.encode(len(array.shape))) + for size in array.shape: + f.write(leb128.u.encode(size)) + f.write(array.tobytes()) + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--n_latents", type=int, default=10, + help="Number of latent states") + parser.add_argument("--max_iter", type=int, default=100, + help="Maximum number of EM iterations") + parser.add_argument("--tol", type=float, default=0.1, + help="Convergence tolerance for EM") + parser.add_argument("--output_dir", type=str, default=None, + help="Output directory to save estimated parameters. If not specified, uses the datasets directory.") + parser.add_argument("--seed", type=int, default=0, + help="Random seed for reproducibility") + parser.add_argument("--vars_to_estimate", type=str, default="B,Q,Z,R,m0,V0", + help="Comma-separated list of variables to estimate. Options are B, Q, Z, R, m0, V0.") + args = parser.parse_args() + + n_latents = args.n_latents + max_iter = args.max_iter + tol = args.tol + output_dir = args.output_dir + seed = args.seed + vars_to_estimate_list = [var.strip() for var in args.vars_to_estimate.split(",")] + vars_to_estimate = {var: (var in vars_to_estimate_list) for var in ["B", "Q", "Z", "R", "m0", "V0"]} + + if output_dir is None: + output_dir = os.path.join(os.path.realpath(os.path.dirname(__file__)), "..", "..", "..", "..", "datasets", "NeuralLatents") + + os.makedirs(output_dir, exist_ok=True) + + print("Loading training data...") + + # load training data + training_data_file = os.path.join(os.path.dirname(output_dir), "sub-Jenkins_ses-small_desc-train_behavior+ecephys.bin") + + n_clusters = 142 + transformed_binned_spikes = np.fromfile(training_data_file, dtype=float).reshape(-1, n_clusters).T + + print("Initializing model...") + + # initialize model + np.random.seed(seed) + + B0 = np.diag(np.random.normal(loc=0, scale=0.1, size=n_latents)) + Z0 = np.random.normal(loc=0, scale=0.1, size=(n_clusters, n_latents)) + Q0 = np.diag(np.abs(np.random.normal(loc=0, scale=0.1, size=n_latents))) + R0 = np.diag(np.abs(np.random.normal(loc=0, scale=0.1, size=n_clusters))) + m0_0 = np.random.normal(loc=0, scale=0.1, size=n_latents) + V0_0 = np.diag(np.abs(np.random.normal(loc=0, scale=0.1, size=n_latents))) + + print("Estimating parameters...") + + optim_res = ssm.learning.em_SS_LDS( + y=transformed_binned_spikes, B0=B0, Q0=Q0, Z0=Z0, R0=R0, + m0_0=m0_0, V0_0=V0_0, max_iter=max_iter, tol=tol, + vars_to_estimate=vars_to_estimate, + ) + + # Save estimated parameters + save_to_tensor(optim_res["B"], os.path.join(output_dir, "TransitionMatrix.bin")) + save_to_tensor(optim_res["Z"], os.path.join(output_dir, "MeasurementFunction.bin")) + save_to_tensor(optim_res["Q"], os.path.join(output_dir, "ProcessNoiseCovariance.bin")) + save_to_tensor(optim_res["R"], os.path.join(output_dir, "MeasurementNoiseCovariance.bin")) 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a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Bonsai.config b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Bonsai.config new file mode 100644 index 0000000..c7c1f78 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Bonsai.config @@ -0,0 +1,140 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/NuGet.config b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/NuGet.config new file mode 100644 index 0000000..aa5beec --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/NuGet.config @@ -0,0 +1,5 @@ + + + + + diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Setup.ps1 b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Setup.ps1 new file mode 100644 index 0000000..76b5c46 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Setup.ps1 @@ -0,0 +1,21 @@ +Push-Location $PSScriptRoot +if (!(Test-Path "./Bonsai.exe")) { + $release = "https://github.com/bonsai-rx/bonsai/releases/latest/download/Bonsai.zip" + $configPath = "./Bonsai.config" + if (Test-Path $configPath) { + [xml]$config = Get-Content $configPath + $bootstrapper = $config.PackageConfiguration.Packages.Package.where{$_.id -eq 'Bonsai'} + if ($bootstrapper) { + $version = $bootstrapper.version + $release = "https://github.com/bonsai-rx/bonsai/releases/download/$version/Bonsai.zip" + } + } + Invoke-WebRequest $release -OutFile "temp.zip" + Move-Item -Path "NuGet.config" "temp.config" -ErrorAction SilentlyContinue + Expand-Archive "temp.zip" -DestinationPath "." -Force + Move-Item -Path "temp.config" "NuGet.config" -Force -ErrorAction SilentlyContinue + Remove-Item -Path "temp.zip" + Remove-Item -Path "Bonsai32.exe" +} +& .\Bonsai.exe --no-editor +Pop-Location \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Setup.sh b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Setup.sh new file mode 100644 index 0000000..941d850 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/Setup.sh @@ -0,0 +1,41 @@ +#! /bin/bash + +SETUP_SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" + +DEFAULT_VERSION="latest" +VERSION="$DEFAULT_VERSION" + +while [[ "$#" -gt 0 ]]; do + case $1 in + --version) VERSION="$2"; shift ;; + *) echo "Unknown parameter passed: $1"; exit 1 ;; + esac + shift +done + +echo "Setting up Bonsai v=$VERSION environment..." + +if [ ! -f "$SETUP_SCRIPT_DIR/Bonsai.exe" ]; then + CONFIG="$SETUP_SCRIPT_DIR/Bonsai.config" + if [ -f "$CONFIG" ]; then + DETECTED=$(xmllint --xpath '//PackageConfiguration/Packages/Package[@id="Bonsai"]/@version' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + echo "Version detected v=$DETECTED." + RELEASE="https://github.com/bonsai-rx/bonsai/releases/download/$DETECTED/Bonsai.zip" + else + if [ $VERSION = "latest" ]; then + RELEASE="https://github.com/bonsai-rx/bonsai/releases/latest/download/Bonsai.zip" + else + RELEASE="https://github.com/bonsai-rx/bonsai/releases/download/$VERSION/Bonsai.zip" + fi + fi + echo "Download URL: $RELEASE" + wget $RELEASE -O "$SETUP_SCRIPT_DIR/temp.zip" + mv -f "$SETUP_SCRIPT_DIR/NuGet.config" "$SETUP_SCRIPT_DIR/temp.config" + unzip -d "$SETUP_SCRIPT_DIR" -o "$SETUP_SCRIPT_DIR/temp.zip" + mv -f "$SETUP_SCRIPT_DIR/temp.config" "$SETUP_SCRIPT_DIR/NuGet.config" + rm -rf "$SETUP_SCRIPT_DIR/temp.zip" + rm -rf "$SETUP_SCRIPT_DIR/Bonsai32.exe" +fi + +source "$SETUP_SCRIPT_DIR/activate" +source "$SETUP_SCRIPT_DIR/run" --no-editor diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/activate b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/activate new file mode 100644 index 0000000..ddf75f3 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/activate @@ -0,0 +1,15 @@ +#!/bin/bash +# activate.sh +if [[ -v BONSAI_EXE_PATH ]]; then + echo "Error! Cannot have multiple bonsai environments activated at the same time. Please deactivate the current environment before activating the new one." + return +fi +BONSAI_ENV_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" +export BONSAI_ENV_DIR +export BONSAI_EXE_PATH="$BONSAI_ENV_DIR/Bonsai.exe" +export ORIGINAL_PS1="$PS1" +export PS1="($(basename "$BONSAI_ENV_DIR")) $PS1" +alias bonsai='source "$BONSAI_ENV_DIR"/run' +alias bonsai-clean='GTK_DATA_PREFIX= source "$BONSAI_ENV_DIR"/run' +alias deactivate='source "$BONSAI_ENV_DIR"/deactivate' +echo "Activated bonsai environment in $BONSAI_ENV_DIR" \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/deactivate b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/deactivate new file mode 100644 index 0000000..43233d9 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/deactivate @@ -0,0 +1,8 @@ +#!/bin/bash +unset BONSAI_EXE_PATH +export PS1="$ORIGINAL_PS1" +unset ORIGINAL_PS1 +unalias bonsai +unalias bonsai-clean +unalias deactivate +echo "Deactivated bonsai environment." \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/run b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/run new file mode 100644 index 0000000..bffd6cf --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.bonsai/run @@ -0,0 +1,58 @@ +#!/bin/bash +# run.sh + +SETUP_SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)" +CONFIG="$SETUP_SCRIPT_DIR/Bonsai.config" + +cleanup() { + update_paths_to_windows +} + +update_paths_to_linux() { + ASSEMBLYLOCATIONS=$(xmllint --xpath '//PackageConfiguration/AssemblyLocations/AssemblyLocation/@location' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for ASSEMBLYLOCATION in $ASSEMBLYLOCATIONS; do + NEWASSEMBLYLOCATION="${ASSEMBLYLOCATION//\\/\/}" + xmlstarlet edit --inplace --update "/PackageConfiguration/AssemblyLocations/AssemblyLocation[@location='$ASSEMBLYLOCATION']/@location" --value "$NEWASSEMBLYLOCATION" "$CONFIG" + done + + LIBRARYFOLDERS=$(xmllint --xpath '//PackageConfiguration/LibraryFolders/LibraryFolder/@path' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for LIBRARYFOLDER in $LIBRARYFOLDERS; do + NEWLIBRARYFOLDER="${LIBRARYFOLDER//\\/\/}" + xmlstarlet edit --inplace --update "//PackageConfiguration/LibraryFolders/LibraryFolder[@path='$LIBRARYFOLDER']/@path" --value "$NEWLIBRARYFOLDER" "$CONFIG" + done +} + +update_paths_to_windows() { + ASSEMBLYLOCATIONS=$(xmllint --xpath '//PackageConfiguration/AssemblyLocations/AssemblyLocation/@location' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for ASSEMBLYLOCATION in $ASSEMBLYLOCATIONS; do + NEWASSEMBLYLOCATION="${ASSEMBLYLOCATION//\//\\}" + xmlstarlet edit --inplace --update "/PackageConfiguration/AssemblyLocations/AssemblyLocation[@location='$ASSEMBLYLOCATION']/@location" --value "$NEWASSEMBLYLOCATION" "$CONFIG" + done + + LIBRARYFOLDERS=$(xmllint --xpath '//PackageConfiguration/LibraryFolders/LibraryFolder/@path' "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + for LIBRARYFOLDER in $LIBRARYFOLDERS; do + NEWLIBRARYFOLDER="${LIBRARYFOLDER//\//\\}" + xmlstarlet edit --inplace --update "//PackageConfiguration/LibraryFolders/LibraryFolder[@path='$LIBRARYFOLDER']/@path" --value "$NEWLIBRARYFOLDER" "$CONFIG" + done +} + +if [[ -v BONSAI_EXE_PATH ]]; then + if [ ! -f "$BONSAI_EXE_PATH" ]; then + bash "$BONSAI_ENV_DIR"/Setup.sh + bash "$BONSAI_ENV_DIR"/run "$@" + else + BONSAI_VERSION=$(xmllint --xpath "//PackageConfiguration/Packages/Package[@id='Bonsai']/@version" "$CONFIG" | sed -e 's/^[^"]*"//' -e 's/"$//') + if [[ -z ${BONSAI_VERSION+x} ]] && [ "$BONSAI_VERSION" \< "2.8.4" ]; then + echo "Updating paths to Linux format..." + trap cleanup EXIT INT TERM + update_paths_to_linux + mono "$BONSAI_EXE_PATH" "$@" + cleanup + else + mono "$BONSAI_EXE_PATH" "$@" + fi + fi +else + echo "BONSAI_EXE_PATH is not set. Please set the path to the Bonsai executable." + return +fi \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.python-version b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/LoadModelParameters.bonsai b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/LoadModelParameters.bonsai new file mode 100644 index 0000000..f8af411 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/LoadModelParameters.bonsai @@ -0,0 +1,128 @@ + + + + + + LoadData + + + + + ../../../../datasets/sub-Jenkins_ses-small_desc-test_ecephys.bin + 0 + 100 + 142 + 1 + F64 + ColumnMajor + + + + + + + + + + + + it.squeeze(null).unsqueeze(0) + + + SpikeCounts + + + + + + + + + + + + LoadModel + + + + + transition_matrix.bin + measurement_function.bin + process_noise_covariance.bin + measurement_noise_covariance.bin + initial_mean.bin + initial_covariance.bin + Float32 + + + + + KalmanFilter + Float64 + 10 + 142 + + + + + + + + + + + + + + + + + + InferNeuralLatents + + + + SpikeCounts + + + + KalmanFilter + + + + + KalmanFilter + + + + + + + + + + + + + + NeuralLatents + true + + + + + + + + + + \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/README.md b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/README.md new file mode 100644 index 0000000..6981d8a --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/README.md @@ -0,0 +1,46 @@ +# Saving and Loading Model Parameters + +In the following example, you will use the `Bonsai.ML.Lds.Torch` package to train a Kalman filter model for estimating neural latents in Bonsai, save the parameters of the model to disk, and subsequently load the parameters and create a model in a separate Bonsai workflow. + +### Download the dataset + +To run the example, you need to download the dataset from DANDI and transform the raw spike data into binned spike counts. We provide a convenient python script and `uv` environment to easily download and transform the raw data. First, make sure `uv` is installed on your computer, which you can do by following the guide [here](https://docs.astral.sh/uv/getting-started/installation/). + +Next, open up a terminal and run the following commands. + +```bash +cd examples/Torch/NeuralLatents/SavingAndLoadingParameters +uv run download_data.py +``` + +When the script finishes, you should see 2 different datasets saved, one for training and the other for testing. + +### Saving model parameters in Bonsai + +The example workflow is shown here: + +:::workflow +![Saving Model Parameters](SaveModelParameters.bonsai) +::: + +The first group node, `LoadData`, loads the training dataset and converts it into a `Tensor` object. It then reshapes it so that the dimensions are `time` x `neurons` and passes it to a `Subject` called `SpikeCounts`. In this example, the entire batch of data is loaded. + +The `LoadModel` group node uses the `CreateKalmanFilter` node to specify the model. We leave the optional parameters blank. We set the `NumStates` to `10` and the `NumObservations` to `142` to match the number of spiking neurons contained in the dataset. This then feeds into a `BehaviorSubject` node called `KalmanFilterModel` for use in other parts of the workflow. + +In the `LearnParameters` group node, the `SpikeCounts` are fed into the `ExpectationMaximization` node which uses the EM algorithm to iteratively optimize the models selected parameters given the spike count data. The EM algorithm will iterate until it reaches the `MaxIterations` count or until the algorithm converges to less than the `Tolerance`. After some time, the algorithm will finish and the output will be passed to a `BehaviorSubject` called `ExpectationMaximizationResult`. + +In the `SaveModelParameters` group node, the emission of a value from the `ExpectationMaximizationResult` subject triggers the `SaveModelParameters` node to write the model parameters to binary data files. + +### Loading model parameters in Bonsai + +The example workflow is shown here: + +:::workflow +![Loading Model Parameters](LoadModelParameters.bonsai) +::: + +The first group node, `LoadData`, loads the test dataset and converts it into a `Tensor` object. + +Inside of the `LoadModel` group node, the `LoadKalmanFilterParameters` operator reads in the data files for the different parameters of the model that were created in the previous workflow. These parameters are then used by the `CreateKalmanFilter` operator. + +In the `InferNeuralLatents` group node, the `SpikeCounts` are passed to the model and online filtering is performed, followed by orthogonalization of the values. The inferrence stream can then be visualized online. \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/SaveModelParameters.bonsai b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/SaveModelParameters.bonsai new file mode 100644 index 0000000..3b5536b --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/SaveModelParameters.bonsai @@ -0,0 +1,174 @@ + + + + + + LoadData + + + + + ../../../../datasets/sub-Jenkins_ses-small_desc-train_behavior+ecephys.bin + 0 + 0 + 142 + 0 + F64 + RowMajor + + + + + + + + + + + + + + 142 + -1 + + + + + + + 1 + 0 + + + + + SpikeCounts + + + + + + + + + + + + + + LearnParameters + + + + SpikeCounts + + + + 10 + 142 + 10 + 0.1 + true + true + true + true + true + true + true + + + + true + + + + + + + + + Source1 + + + Finished + + + + + + + + + + + Parameters + + + + Float32 + 2 + 2 + + + + + + + + + + KalmanFilterModel + + + + + + + + + + + + + + SaveModelParameters + + + + KalmanFilterModel + + + + models + false + DateTime + + + + + + + + + + + + + 1 + + + + + + + + + + \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/download_data.py b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/download_data.py new file mode 100644 index 0000000..2582820 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/download_data.py @@ -0,0 +1,59 @@ +# Import libraries +import numpy as np +import remfile, h5py +from dandi.dandiapi import DandiAPIClient +from pynwb import NWBHDF5IO +import os + +# set base directory to save data +base_dir = os.path.join(os.path.realpath(os.path.dirname(__file__)), "..", "..", "..", "..", "datasets") + +# dandi dataset info +dandiset_ID = "000140" +dandi_filenames = [ + "sub-Jenkins/sub-Jenkins_ses-small_desc-train_behavior+ecephys.nwb", + "sub-Jenkins/sub-Jenkins_ses-small_desc-test_ecephys.nwb" +] + +for dandi_filepath in dandi_filenames: + + print(f"Downloading and processing {dandi_filepath}...") + + # download data using remfile and dandi + with DandiAPIClient() as client: + asset = client.get_dandiset(dandiset_ID, + "draft").get_asset_by_path(dandi_filepath) + s3_path = asset.get_content_url(follow_redirects=1, strip_query=True) + cache = remfile.DiskCache(os.path.join(base_dir, "remfile_cache")) + rf = remfile.File(s3_path, disk_cache=cache) + with h5py.File(rf, "r") as h: + with NWBHDF5IO(file=h, mode="r") as io: + nwbfile = io.read() + # extract spike sorted units dataframe + units_df = nwbfile.units.to_dataframe() + + print(f"Data downloaded. Processing spikes...") + + # bin spikes + n_clusters = units_df.shape[0] + bin_size = 0.02 + + spike_times = [units_df.iloc[n]['spike_times'] for n in range(n_clusters)] + t_max = max(max(st) for st in spike_times if len(st) > 0) + + bin_edges = np.arange(0, t_max + bin_size, bin_size) + bin_centers = (bin_edges[1:] + bin_edges[:-1]) / 2 + n_bins = len(bin_edges) - 1 + + spike_counts = np.zeros((n_clusters, n_bins), dtype=int) + + for n, spikes in enumerate(spike_times): + spike_counts[n], _ = np.histogram(spikes, bins=bin_edges) + + # transform binned spikes using square-root transform + spike_counts = np.sqrt(spike_counts + 0.5) + + output_filename = dandi_filepath.split("/")[-1].replace(".nwb", ".bin") + spike_counts.astype(float).tofile(os.path.join(base_dir, output_filename)) + + print(f"Processed spikes saved to {os.path.realpath(os.path.join(base_dir, output_filename))}") \ No newline at end of file diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/pyproject.toml b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/pyproject.toml new file mode 100644 index 0000000..8ae6f75 --- /dev/null +++ b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/pyproject.toml @@ -0,0 +1,18 @@ +[project] +name = "estimatingneurallatents" +version = "0.1.0" +description = "Example for estimating neural latents" +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "dandi>=0.71.4", + "h5py>=3.14.0", + "numpy>=2.3.3", + "pynwb>=3.1.2", + "remfile>=0.1.13", + "ssm", + "torch>=2.8.0", +] + +[tool.uv.sources] +ssm = { git = "https://github.com/ncguilbeault/lds_python", rev = "75e3e5e92ce6344009b62a5034db49b238db63ef" } diff --git a/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/uv.lock b/examples/LinearDynamicalSystems/NeuralLatents/SavingAndLoadingParameters/uv.lock new file mode 100644 index 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b/examples/LinearDynamicalSystems/README.md deleted file mode 100644 index e060f00..0000000 --- a/examples/LinearDynamicalSystems/README.md +++ /dev/null @@ -1,138 +0,0 @@ -# Getting Started - -In general, when using the LinearDynamicalSystems package, you need to configure your Bonsai workflow to run the correct python environment which has the [lds_python](https://github.com/joacorapela/lds_python) package installed. - -If you followed the installation guide, you will have a basic Bonsai-python environment for using the LinearDynamicalSystems package. You will also have installed the basic dependencies required to build and run the Bonsai workflows. However, if you wish to run the examples, we highly recommend following this guide to create and configure the environments needed for each example. This guide has been made for users starting from scratch to get started. Alternatively, you can use the environment you created in the previous guide and install the necessary package dependencies required to run each workflow. - -All of the examples are self-contained and can be found by going to the [Bonsai.ML - Examples](https://github.com/bonsai-rx/machinelearning-examples) repo. For each example, you can bootstrap the python and Bonsai environments from within each example directory. Below, we demonstrate how to get started using the examples by bootstrapping the example environments that are needed to run the example workflow. - -### Windows - -#### Dependencies - -You must have the following installed on your PC in order to run the example workflows: - -- [Python (v3.10)](https://www.python.org/downloads/) *Note: python must be installed using the windows installer and must be added to the system PATH* -- [Git](https://git-scm.com/downloads) -- [Microsoft Visual C++ Redistributable](https://aka.ms/vs/16/release/vc_redist.x64.exe) - -> [!TIP] -> When running windows in a virtual machine, it is necessary to install the [OpenGL mesa drivers](https://github.com/pal1000/mesa-dist-win/releases/) on the windows VM. You can read more about it [here](https://github.com/pal1000/mesa-dist-win) - -#### Instructions - -Open the terminal or powershell. Start by cloning the [Bonsai.ML - Examples](https://github.com/bonsai-rx/machinelearning-examples) repo with: - -```cmd -git clone https://github.com/bonsai-rx/machinelearning-examples.git -``` - -Change directory to one of the examples. For instance, this will bring you to the simulated data example from the LinearDynamicalSystems.Kinematics package: - -```cmd -cd .\machinelearning-examples\examples\LinearDynamicalSystems\Kinematics\SimulatedData -``` - -To create the python virtual environment and install the package, run the following: - -```cmd -python -m venv .venv -.\.venv\Scripts\activate -pip install lds_python@git+https://github.com/joacorapela/lds_python@f761c201f3df883503ecb67acef35ba846e3524c -``` - -> [!TIP] -> If you get an error during this step, you need to make sure that scripts are executable from the terminal. To do this, open a powershell terminal using `Run as Administrator` and enter this line, followed by `yes`: - -```powershell -set-executionpolicy remotesigned -``` - -To create the bonsai environment and install the packages, run the powershell script: - -```cmd -cd .bonsai -powershell .\Setup.ps1 -``` - -Once installed, run the bonsai executable with: - -```cmd -.\Bonsai.exe -``` - -Open the workflow example and start the bonsai workflow. - -### Linux - -#### Notes on Running Bonsai in Linux - -Currently, the examples have only been tested on Ubuntu 22.04. Running Bonsai on Linux is still being tested and should be used with caution. We cannot guarantee that these instructions will work for all Linux distributions or versions. It is important that you consult the general [Bonsai installation guide on Linux](https://github.com/orgs/bonsai-rx/discussions/1101) to ensure that the underlying Bonsai package dependencies are met and installed properly. - -#### Dependencies - -You must have the following installed on your PC in order to run the example workflows: - -- [Python (v3.10)](https://www.python.org/downloads/) *comes installed with the latest version of Ubuntu 22.04* -- [Git](https://git-scm.com/downloads) -- [Mono](https://www.mono-project.com/download/stable/#download-lin) -- [OpenCV and OpenGL binaries](https://github.com/orgs/bonsai-rx/discussions/1101) - - -> [!TIP] -> For installing OpenCV, the simplest method is to follow the instructions on installing OpenCV from pre-built binaries - -#### Instructions - -Open up a terminal and start by cloning the [Bonsai.ML - Examples](https://github.com/bonsai-rx/machinelearning-examples) repo: - -```cmd -git clone https://github.com/bonsai-rx/machinelearning-examples.git -``` - -Change directory to one of the examples. For instance: - -```cmd -cd machinelearning-examples/examples/LinearDynamicalSystems/Kinematics/SimulatedData -``` - -Create the python virtual environment and install the lds python package with the following: - -```cmd -python3 -m venv .venv -source .venv/bin/activate -pip install lds_python@git+https://github.com/joacorapela/lds_python@f761c201f3df883503ecb67acef35ba846e3524c -``` - -> [!TIP] -> If you get an error during this step, it may be because you need to install python virtual environment package on your system. You can do so using the following: - -```cmd -sudo apt install -y python3.10-venv -``` - -Run the `Setup.sh` script using the following: - -```cmd -cd .bonsai -./Setup.sh -``` - -> [!TIP] -> The `Setup.sh` script uses the `xmllint` and `xmlstarlet` packages to convert the assembly location paths in the bonsai config file from Windows to Linux paths. If you do not have these packages already installed on your computer, you can install the `xmllint` and the `xmlstarlet` packages using: - -```cmd -sudo apt install -y libxml2-utils xmlstarlet -``` - -Once the bonsai environment has been created, activate the bonsai environment and run the Bonsai executable: - -```cmd -source ./activate -bonsai -``` - -> [!TIP] -> If your desktop theme is set to dark mode, the Bonsai GUI can display in weird ways due to the way that mono tries to use the desktop theme in applications. If you use the `bonsai-clean` command instead of the `bonsai` command, this will reset the theme that mono uses to the default theme, which can imporove the appearance of the Bonsai GUI. - -Open the workflow example and start the bonsai workflow.