.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/stimuli/plot_psychophysics.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_stimuli_plot_psychophysics.py: =============================================================================== Generating a drifting sinusoidal grating or drifting bar stimulus =============================================================================== *This example shows how to use drifting psychophysics-based stimuli for a retinal implant.* Along with images, videos, and oter built-in stimuli, pulse2percept supports generating :py:class:`~pulse2percept.stimuli.GratingStimulus` and :py:class:`~pulse2percept.stimuli.BarStimulus` as stimuli that can be passed as percepts to implants. Creating a Stimulus ------------------- First, create the stimuli: Shape (`(height, width)` in pixels) is the only required parameter for creating these stimuli. A drifting sinusoidal grating is represented by :py:class:`~pulse2percept.stimuli.GratingStimulus`. The following illustrates one frame of a grating stimulus. .. GENERATED FROM PYTHON SOURCE LINES 24-31 .. code-block:: Python import matplotlib.pyplot as plt from pulse2percept.stimuli import GratingStimulus stim = GratingStimulus((50, 50), spatial_freq=0.1, temporal_freq=0.1) plt.imshow(stim.data[:, 0].reshape(50, 50), cmap='gray') plt.title("Grating Stimulus") plt.show() .. image-sg:: /examples/stimuli/images/sphx_glr_plot_psychophysics_001.png :alt: Grating Stimulus :srcset: /examples/stimuli/images/sphx_glr_plot_psychophysics_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 33-34 You can view the entire stimulus over time using `stim.play()` .. GENERATED FROM PYTHON SOURCE LINES 34-36 .. code-block:: Python stim.play() .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 37-45 Here, the spatial frequency of the grating (i.e., the inverse of how many pixels it takes to represent one cycle of the sinusoid) is given as 0.1 cycles/pixel, whereas the temporal frequency (i.e., the inverse of how many frames it takes to represent one cycle of the sinusoid) is given as 0.1 cycles/frame. By default, the drift direction of the grating will be to the right (0 degrees). A drifting bar is represented by :py:class:`~pulse2percept.stimuli.BarStimulus`. A visual example of a basic sinusoidal grating can be generated as such: .. GENERATED FROM PYTHON SOURCE LINES 45-50 .. code-block:: Python from pulse2percept.stimuli.psychophysics import BarStimulus stim = BarStimulus((50, 50), speed=1) stim.play() .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 51-70 Here, the drift speed of the bar is given as 1 pixel/frame and, by default, the bar will drift to the right (0 degrees). Customizing the Stimulus ------------------------ For both :py:class:`~pulse2percept.stimuli.BarStimulus` and :py:class:`~pulse2percept.stimuli.GratingStimulus`, the only argument you must pass to the constructor is the shape `(height, width)` in pixels. There are many optional arguments that can be passed to change various attributes of the stimulus. In the examples above, we changed the speed at which the GratingStimulus changed with temporal_freq *(scalar, cycles/frame)* and the speed at which the BarStimulus moved with speed *(scalar, pixels/frame)* in order to make the effect easier to visualize. If, for example, we wanted a longer stimulus, we cold set the time parameter (in units of milliseconds) to change the duration of the stimulus: .. GENERATED FROM PYTHON SOURCE LINES 70-74 .. code-block:: Python stim = BarStimulus((50, 50), speed=1, time=1500) stim.play() .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 75-106 We can also change the direction *(scalar in [0, 360) degrees)*, where 0 degrees represents rightward motion, 90 degrees represents upward motion, 180 degrees represents leftward motion, and 270 degrees represents downward motion. .. code:: python BarStimulus((height, width), direction=direction) Or the contrast *(scalar in [0,1])* .. code:: python BarStimulus((height, width), contrast=contrast) For exact info on all of the arguments, please refer to :py:class:`~pulse2percept.stimuli.BarStimulus` and :py:class:`~pulse2percept.stimuli.GratingStimulus`. Passing to an Implant --------------------- Psychophsyics stimuli can be passed to an implant and combined with a model. To demonstrate, we will pass a ``GratingStimululus`` to an :py:class:`~pulse2percept.implants.ArgusII` implant and use the :py:class:`~pulse2percept.models.AxonMapModel` [Beyeler2019]_ to interpret it: .. important :: Don't forget to build the model before using ``predict_percept`` .. GENERATED FROM PYTHON SOURCE LINES 106-119 .. code-block:: Python from pulse2percept.implants import ArgusII from pulse2percept.models import AxonMapModel model = AxonMapModel() model.build() implant = ArgusII() implant.stim = GratingStimulus((25,25), temporal_freq=0.1) percept = model.predict_percept(implant) percept.play() .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 120-136 As you can see in the above code segment, the stimulus passed to the implant does not necessarily have to have the same dimensions as the electrode grid. This is functionality built in to the implant code: The implant will automatically rescale the stimulus to the appropriate size. In the case of Argus II, the stimulus would thus be downscaled to a 6x10 image. Pre-Processing Stimuli ---------------------- Since both :py:class:`~pulse2percept.stimuli.BarStimulus` and :py:class:`~pulse2percept.stimuli.GratingStimulus` inherit form :py:class:`~pulse2percept.stimuli.VideoStimulus`, we can apply any video processing methods provided by ``VideoStimulus``. In the following example, we will invert the stimulus before passing it to the implant: .. GENERATED FROM PYTHON SOURCE LINES 136-145 .. code-block:: Python model = AxonMapModel() model.build() implant = ArgusII() implant.stim = GratingStimulus((25,25), temporal_freq=0.1).invert() percept = model.predict_percept(implant) percept.play() .. raw:: html

.. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 28.376 seconds) .. _sphx_glr_download_examples_stimuli_plot_psychophysics.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_psychophysics.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_psychophysics.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_psychophysics.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_