{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Processing pupil size data and epoching\n", "\n", "When working with event-based recordings, it's often useful to extract and analyze data segments surrounding those events, rather than processing the entire recording. In mobile eye-tracking, such events could include stimulus presentations or the participant entering a specific area. In this tutorial, we'll demonstrate how to epoch data around these events using the `pyneon.Epochs` class, with the sample recording `screenFlash`." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from pyneon import Recording, get_sample_data\n", "\n", "# Create a Recording object\n", "rec_dir = (\n", " get_sample_data(\"screenFlash\")\n", " / \"Timeseries Data + Scene Video\"\n", " / \"screenflash-54b2f924\"\n", ")\n", "rec = Recording(rec_dir)\n", "video = rec.video\n", "blinks = rec.blinks\n", "events = rec.events\n", "eye_states = rec.eye_states" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This recording features a participant observing a screen that flashes from black to white (flash duration = 0.75 s), with a 3-second interval between flashes. We expect the pupil to constrict in response to each flash, making this dataset ideal for demonstrating epoching. Here is how the flash appears to the participant:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Resetting video...\n", "Resetting video...\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "# Create a figure\n", "fig, axs = plt.subplots(1, 2, figsize=(8, 3))\n", "\n", "# Visualize two frames from the video that correspond to the dark and flash periods\n", "video.plot_frame(180, ax=axs[0], auto_title=False, show=False)\n", "video.plot_frame(190, ax=axs[1], auto_title=False, show=False)\n", "axs[0].set_title(\"Dark\")\n", "axs[1].set_title(\"Flash\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualizing raw pupil size data and repairing blink artifacts\n", "\n", "Let's inspect the raw pupil size data along with blink events. The shaded region shows when the screen is bright; dashed lines indicate the onset of blinks." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 3))\n", "\n", "# Visualize the flashes\n", "flash_idx = np.where(events.data[\"name\"] == \"Flash onset\")\n", "for flash_start in events.start_ts[flash_idx]:\n", " dur = plt.axvspan(\n", " flash_start, flash_start + 0.75 * 1e9, color=\"lightgray\", label=\"Flashes\"\n", " ) # Each flash lasts 2 seconds\n", "\n", "# Visualize the blinks\n", "for blink_start in blinks.start_ts:\n", " line = plt.axvline(blink_start, color=\"k\", linestyle=\"--\", lw=1, label=\"Blinks\")\n", "\n", "# Plot the pupil data\n", "(pupil_l,) = plt.plot(eye_states[\"pupil diameter left [mm]\"])\n", "\n", "plt.xlabel(\"Timestamp [ns]\")\n", "plt.ylabel(\"Left pupil diameter [mm]\")\n", "plt.legend(handles=[dur, line])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From the plot we can note:\n", "- Pupil size decreases promptly after each change in screen brightness.\n", "- The participant frequently blinks in response to flashes, and blinks introduce distinct transient artifacts in the pupil size measurement.\n", " \n", "First, we’ll address blink artifacts using the `interpolate_events()` method of the `Stream` class. This method masks the data during events (in this case, blinks) and interpolates values around them, effectively removing the transient artifacts." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "eye_states.interpolate_events(blinks, inplace=True)\n", "\n", "plt.figure(figsize=(8, 3))\n", "\n", "# Visualize the flashes\n", "flash_idx = np.where(events.data[\"name\"] == \"Flash onset\")\n", "for flash_start in events.start_ts[flash_idx]:\n", " dur = plt.axvspan(\n", " flash_start, flash_start + 7.5 * 1e8, color=\"lightgray\", label=\"Flashes\"\n", " ) # Each flash lasts 2 seconds\n", "\n", "# Visualize the blinks\n", "for blink_start in blinks.start_ts:\n", " line = plt.axvline(blink_start, color=\"k\", linestyle=\"--\", lw=1, label=\"Blinks\")\n", "\n", "# Plot the pupil data\n", "(pupil_l,) = plt.plot(eye_states[\"pupil diameter left [mm]\"])\n", "\n", "plt.xlabel(\"Timestamp [ns]\")\n", "plt.ylabel(\"Left pupil diameter [mm]\")\n", "plt.legend(handles=[dur, line])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Defining Epochs: Creating the `times_df` DataFrame\n", "\n", "In order to perform epoching, we require information about the timing and lenghts of epochs. Explicitly, every epoch requires:\n", "- A reference time `t_ref`\n", "- A time window defined by `t_before` and `t_after` to extract the data from\n", "- An event `description` to annotate the epoch.\n", "\n", "PyNeon's `Epochs` implementation allows epochs of variable lengths, where `t_before` and `t_after` may differ for each event. As a result, defining all epochs requires a DataFrame (`times_df`) with columns: `t_ref`, `t_before`, `t_after`, and `description`.\n", "\n", "While constructing such a DataFrame by hand is possible, it's easier to generate one using event information from PyNeon `Events` objects. The `events_to_times_df` function streamlines this process by using the onsets of events and user-defined `t_before`/`t_after` values.\n", "\n", "In this example, we’ll use `\"Flash onset\"` events, extracting 0.5 seconds before to 3 seconds after each event; the description is set to the event name automatically." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Flash times DataFrame:\n", " t_ref t_before t_after description\n", "0 1748359118207381000 500000000 3000000000 Flash onset\n", "1 1748359122083310000 500000000 3000000000 Flash onset\n", "2 1748359126042722000 500000000 3000000000 Flash onset\n", "3 1748359129933171000 500000000 3000000000 Flash onset\n", "4 1748359133927133000 500000000 3000000000 Flash onset\n" ] } ], "source": [ "from pyneon import events_to_times_df, Epochs\n", "\n", "# For complex events, such as those from `events.csv`, we need to specify the event name\n", "flash_times_df = events_to_times_df(\n", " events, t_before=0.5, t_after=3, t_unit=\"s\", event_name=\"Flash onset\"\n", ")\n", "\n", "# Print the epoching-ready times_df\n", "print(\"\\nFlash times DataFrame:\")\n", "print(flash_times_df.head())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Creating `Epochs` objects\n", "\n", "With the `times_df` DataFrame, we can create epochs by passing it along with the relevant `Stream` or `Events` data to the `Epochs` class.\n", "\n", "In this example, we create two types of epochs to test two hypotheses:\n", "- `eye_ep`: epochs from `eye_states` (a `Stream` object), containing pupil size. We hypothesize pupil size will decrease after each flash.\n", "- `blink_ep`: epochs from `blinks` (an `Events` object), letting us check if blinks cluster after each flash." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10 epochs created from 10 events\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:445: RuntimeWarning: No data found for epoch 1.\n", " warnings.warn(f\"No data found for epoch {i}.\", RuntimeWarning)\n", "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:445: RuntimeWarning: No data found for epoch 2.\n", " warnings.warn(f\"No data found for epoch {i}.\", RuntimeWarning)\n", "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:445: RuntimeWarning: No data found for epoch 6.\n", " warnings.warn(f\"No data found for epoch {i}.\", RuntimeWarning)\n", "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:445: RuntimeWarning: No data found for epoch 7.\n", " warnings.warn(f\"No data found for epoch {i}.\", RuntimeWarning)\n", "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:445: RuntimeWarning: No data found for epoch 8.\n", " warnings.warn(f\"No data found for epoch {i}.\", RuntimeWarning)\n", "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:445: RuntimeWarning: No data found for epoch 9.\n", " warnings.warn(f\"No data found for epoch {i}.\", RuntimeWarning)\n" ] } ], "source": [ "eye_ep = Epochs(eye_states, flash_times_df)\n", "blink_ep = Epochs(blinks, flash_times_df)\n", "print(f\"{len(eye_ep)} epochs created from {len(flash_times_df)} events\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Given that we have very sparse blink events, it is not surprising that PyNeon emits a warning when creating the `blink_ep` epochs.\n", "\n", "The `Epochs` class provides two key attributes (For details, see the [API reference](https://ncc-brain.github.io/PyNeon/reference/epochs.html)):\n", "- `epochs`: a nested DataFrame, indexed by epoch number, with data for each epoch stored under the `data` column.\n", "- `data`: (not to be confused with the `data` column in `Epochs.epochs`) a DataFrame in the same structure as the source, but annotated with epoch membership and timing information (`epoch index`, `epoch time`, and `epoch description`). As a flattened version of `Epochs.epochs`, `Epochs.data` may contain overlapping epochs; in such cases, the additional columns will only show information from the most recent epoch a time point belongs to. Therefore, we recommend primarily using `Epochs.epochs` for analysis." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epochs.epochs contains:\n", "Index(['t_ref', 't_before', 't_after', 'description', 'data'], dtype='object')\n", "\n", "Its `data` column contains:\n", "Index(['pupil diameter left [mm]', 'pupil diameter right [mm]',\n", " 'eyeball center left x [mm]', 'eyeball center left y [mm]',\n", " 'eyeball center left z [mm]', 'eyeball center right x [mm]',\n", " 'eyeball center right y [mm]', 'eyeball center right z [mm]',\n", " 'optical axis left x', 'optical axis left y', 'optical axis left z',\n", " 'optical axis right x', 'optical axis right y', 'optical axis right z',\n", " 'eyelid angle top left [rad]', 'eyelid angle bottom left [rad]',\n", " 'eyelid aperture left [mm]', 'eyelid angle top right [rad]',\n", " 'eyelid angle bottom right [rad]', 'eyelid aperture right [mm]',\n", " 'epoch time'],\n", " dtype='object')\n", "\n", "Epochs.data contains:\n", "Index(['pupil diameter left [mm]', 'pupil diameter right [mm]',\n", " 'eyeball center left x [mm]', 'eyeball center left y [mm]',\n", " 'eyeball center left z [mm]', 'eyeball center right x [mm]',\n", " 'eyeball center right y [mm]', 'eyeball center right z [mm]',\n", " 'optical axis left x', 'optical axis left y', 'optical axis left z',\n", " 'optical axis right x', 'optical axis right y', 'optical axis right z',\n", " 'eyelid angle top left [rad]', 'eyelid angle bottom left [rad]',\n", " 'eyelid aperture left [mm]', 'eyelid angle top right [rad]',\n", " 'eyelid angle bottom right [rad]', 'eyelid aperture right [mm]',\n", " 'epoch index', 'epoch time', 'epoch description'],\n", " dtype='object')\n", "\n" ] } ], "source": [ "print(f\"Epochs.epochs contains:\\n{eye_ep.epochs.columns}\\n\")\n", "print(f\"Its `data` column contains:\\n{eye_ep.epochs.data[0].columns}\\n\")\n", "print(f\"Epochs.data contains:\\n{eye_ep.data.columns}\\n\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualizing epoch data\n", "\n", "The `plot()` method provides a convenient way to visualize data across epochs.\n", "\n", "For `Epochs` created from a `Stream` (like eye states), specify the desired column to plot all across epochs in a single figure, colored by epoch index. We can observe from the following plot that pupil restriction occurs after each flash consistently, except for the first flash, likely due to a different baseline pupil size." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8, 3))\n", "fig, ax = eye_ep.plot(\"pupil diameter left [mm]\", ax=ax)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For `Events`-based `Epochs` (like blinks), simply call `plot()` with no arguments. Here, each event is displayed as a horizontal line spanning its duration, vertically sorted by epoch. We can see that blinks (N=4 in this example) tend to happen 1 to 1.5 seconds after each flash." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = blink_ep.plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Converting `Stream`-based `Epochs` to a Numpy array\n", "\n", "Rather than viewing epochs as nested DataFrames, under the right conditions, you can convert an `Epochs` object to a 3D NumPy array useful for time-series analyses (like with [MNE-Python](https://mne.tools/stable/generated/mne.Epochs.html)). \n", "\n", "For this:\n", "- The source must be a uniformly sampled `Stream` (constant intervals between samples).\n", "- All epochs must have the same durations (`t_before` and `t_after` equal).\n", "\n", "If these are not met, PyNeon will raise a `ValueError` when `to_numpy()` is called." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Error converting to numpy: The source must be a uniformly-sampled Stream to convert to NumPy array.\n" ] } ], "source": [ "try:\n", " epochs_interp_np, info = eye_ep.to_numpy()\n", "except Exception as e:\n", " print(f\"Error converting to numpy: {e}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To ensure compatibility, interpolate the `Stream` data prior to epoching, and maintain constant window sizes across epochs. The resulting array will be shaped `(n_epochs, n_channels, n_times)`." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(n_epochs, n_channels, n_times) = (10, 20, 699)\n", "dict_keys(['column_ids', 'epoch_times', 'nan_flag'])\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:275: RuntimeWarning: NaN values were found in the data.\n", " warnings.warn(\"NaN values were found in the data.\", RuntimeWarning)\n" ] } ], "source": [ "# Create an epoch with the interpolated data\n", "epochs_interp = Epochs(eye_states.interpolate(), flash_times_df)\n", "epochs_interp_np, info = epochs_interp.to_numpy()\n", "\n", "print(f\"(n_epochs, n_channels, n_times) = {epochs_interp_np.shape}\")\n", "print(info.keys())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this case, we have 10 epochs, 20 data channels, and 699 time steps—consistent with the 200 Hz sampling rate and the 3.5-second epoch window. The `info` object contains lists of column IDs and epoch times. Now, the grand average is easily computed:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Average the first channel (Pupil diameter left [mm]) across all epochs\n", "pupil_mean = epochs_interp_np[:, 0, :].mean(axis=0)\n", "pupil_std = epochs_interp_np[:, 0, :].std(axis=0)\n", "\n", "plt.figure(figsize=(8, 4))\n", "\n", "# Show a vertical line at 0\n", "plt.axvline(x=0, color=\"k\", linestyle=\"--\")\n", "# Plot the mean pupil diameter and standard deviation\n", "plt.plot(info[\"epoch_times\"], pupil_mean)\n", "plt.fill_between(\n", " info[\"epoch_times\"], pupil_mean - pupil_std, pupil_mean + pupil_std, alpha=0.2\n", ")\n", "plt.xlim(-0.5, 3)\n", "plt.xlabel(\"Flash onset time [s]\")\n", "plt.ylabel(\"Pupil Diameter left [mm]\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Baseline correction\n", "\n", "Optionally, we can also perform `baseline_correction()` on the data to address global fluctuations in data. approach is to subtract the mean of a pre-event baseline (`method=\"mean\"`). If there exists a linear trend in the baseline that extends into the entire epoch, `method=\"linear\"` will fit and remove it.\n", "\n", "Here, we apply `baseline_correction()` with `method=\"mean\"` to compare pupil size relative to a 500 ms pre-flash baseline, centering pre-flash values around zero and reducing variance." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\qian.chu\\Documents\\GitHub\\PyNeon\\pyneon\\epochs.py:275: RuntimeWarning: NaN values were found in the data.\n", " warnings.warn(\"NaN values were found in the data.\", RuntimeWarning)\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Perform baseline correction\n", "epochs_interp.baseline_correction(inplace=True, baseline=(-0.5, 0), method=\"mean\")\n", "epochs_interp_np, info = epochs_interp.to_numpy()\n", "\n", "# Average the first channel (Pupil diameter left [mm]) across all epochs\n", "pupil_mean = epochs_interp_np[:, 0, :].mean(axis=0)\n", "pupil_std = epochs_interp_np[:, 0, :].std(axis=0)\n", "\n", "plt.figure(figsize=(8, 4))\n", "\n", "# Show a vertical line at 0\n", "plt.axvline(x=0, color=\"k\", linestyle=\"--\")\n", "# Plot the mean pupil diameter and standard deviation\n", "plt.plot(info[\"epoch_times\"], pupil_mean)\n", "plt.fill_between(\n", " info[\"epoch_times\"], pupil_mean - pupil_std, pupil_mean + pupil_std, alpha=0.2\n", ")\n", "plt.xlim(-0.5, 3)\n", "plt.xlabel(\"Flash onset time [s]\")\n", "plt.ylabel(\"Pupil Diameter left [mm]\")\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "pyneon", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.2" } }, "nbformat": 4, "nbformat_minor": 2 }