<reponame>narenberg/pulse2percept<filename>pulse2percept/viz/tests/test_argus.py
from pulse2percept.viz import (plot_argus_phosphenes,
                               plot_argus_simulated_phosphenes)
from pulse2percept.implants import ArgusI, ArgusII, AlphaAMS
from pulse2percept.models import AxonMapModel, ScoreboardModel
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import numpy.testing as npt
import pytest
import matplotlib
matplotlib.use('Agg')


def test_plot_argus_phosphenes():
    df = pd.DataFrame([
        {'subject': 'S1', 'electrode': 'A1', 'image': np.random.rand(10, 10),
         'xrange': (-10, 10), 'yrange': (-10, 10)},
        {'subject': 'S1', 'electrode': 'B2', 'image': np.random.rand(10, 10),
         'xrange': (-10, 10), 'yrange': (-10, 10)},
    ])
    _, ax = plt.subplots()
    plot_argus_phosphenes(df, ArgusI(), ax=ax)
    plot_argus_phosphenes(df, ArgusII(), ax=ax)

    # Add axon map:
    _, ax = plt.subplots()
    plot_argus_phosphenes(df, ArgusI(), ax=ax, axon_map=AxonMapModel())

    # Data must be a DataFrame:
    with pytest.raises(TypeError):
        plot_argus_phosphenes(np.ones(10), ArgusI())
    # DataFrame must have the required columns:
    with pytest.raises(ValueError):
        plot_argus_phosphenes(pd.DataFrame(), ArgusI())
    # Subjects must all be the same:
    with pytest.raises(ValueError):
        dff = pd.DataFrame([{'subject': 'S1'}, {'subject': 'S2'}])
        plot_argus_phosphenes(dff, ArgusI())
    # Works only for Argus:
    with pytest.raises(TypeError):
        plot_argus_phosphenes(df, AlphaAMS())
    # Works only for axon maps:
    with pytest.raises(TypeError):
        plot_argus_phosphenes(df, ArgusI(), ax=ax, axon_map=ScoreboardModel())

    # Manual subject selection
    plot_argus_phosphenes(df[df.electrode == 'B2'], ArgusI(), ax=ax)


@pytest.mark.parametrize('implant', (ArgusI(), ArgusII()))
def test_plot_argus_simulated_phosphenes(implant):
    implant.stim = {'A1': [1, 0, 0], 'B2': [0, 1, 0], 'C3': [0, 0, 1]}
    percepts = ScoreboardModel().build().predict_percept(implant)

    plot_argus_simulated_phosphenes(percepts, implant)

    # Add axon map:
    _, ax = plt.subplots()
    plot_argus_simulated_phosphenes(percepts, implant, ax=ax,
                                    axon_map=AxonMapModel())

from pulse2percept.viz import (plot_argus_phosphenes,
                               plot_argus_simulated_phosphenes)
from pulse2percept.implants import ArgusI, ArgusII, AlphaAMS
from pulse2percept.models import AxonMapModel, ScoreboardModel
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import numpy.testing as npt
import pytest
import matplotlib
matplotlib.use('Agg')


def test_plot_argus_phosphenes():
    df = pd.DataFrame([
        {'subject': 'S1', 'electrode': 'A1', 'image': np.random.rand(10, 10),
         'xrange': (-10, 10), 'yrange': (-10, 10)},
        {'subject': 'S1', 'electrode': 'B2', 'image': np.random.rand(10, 10),
         'xrange': (-10, 10), 'yrange': (-10, 10)},
    ])
    _, ax = plt.subplots()
    plot_argus_phosphenes(df, ArgusI(), ax=ax)
    plot_argus_phosphenes(df, ArgusII(), ax=ax)

    # Add axon map:
    _, ax = plt.subplots()
    plot_argus_phosphenes(df, ArgusI(), ax=ax, axon_map=AxonMapModel())

    # Data must be a DataFrame:
    with pytest.raises(TypeError):
        plot_argus_phosphenes(np.ones(10), ArgusI())
    # DataFrame must have the required columns:
    with pytest.raises(ValueError):
        plot_argus_phosphenes(pd.DataFrame(), ArgusI())
    # Subjects must all be the same:
    with pytest.raises(ValueError):
        dff = pd.DataFrame([{'subject': 'S1'}, {'subject': 'S2'}])
        plot_argus_phosphenes(dff, ArgusI())
    # Works only for Argus:
    with pytest.raises(TypeError):
        plot_argus_phosphenes(df, AlphaAMS())
    # Works only for axon maps:
    with pytest.raises(TypeError):
        plot_argus_phosphenes(df, ArgusI(), ax=ax, axon_map=ScoreboardModel())

    # Manual subject selection
    plot_argus_phosphenes(df[df.electrode == 'B2'], ArgusI(), ax=ax)


@pytest.mark.parametrize('implant', (ArgusI(), ArgusII()))
def test_plot_argus_simulated_phosphenes(implant):
    implant.stim = {'A1': [1, 0, 0], 'B2': [0, 1, 0], 'C3': [0, 0, 1]}
    percepts = ScoreboardModel().build().predict_percept(implant)

    plot_argus_simulated_phosphenes(percepts, implant)

    # Add axon map:
    _, ax = plt.subplots()
    plot_argus_simulated_phosphenes(percepts, implant, ax=ax,
                                    axon_map=AxonMapModel())
# Add axon map: # Data must be a DataFrame: # DataFrame must have the required columns: # Subjects must all be the same: # Works only for Argus: # Works only for axon maps: # Manual subject selection # Add axon map: