Generate a fascicle with all contexts

This example shows how to easily generate and save a fascicle with the following contexts:

• Intracellular context: A current attached to all axons at \(x=0\).

• Recording context : An analytical recorder is added with three recording points located at \(x\in\{\frac{L}{4}, \frac{L}{2}, \frac{3L}{4}\}\), \(y=0\), \(z=100\).

• Extracellular context: A LIFE electrode is added to the centre of the fascicle \(x=\frac{L}{2}\), \(y=0\), \(z=0\).

This example can be used as a model to generate all sorts of fascicles with a customised context. For instance, it is used to generate the simulation context for many other examples in this documentation.

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import nrv

import matplotlib.pyplot as plt
import os


# Fascicle declaration
# --------------------

# The first step before generating a fascicle is to create a population of
# axons using the ``create_axon_population`` function.

# Then the fascicle can be generated and filled with the population.

# *Note that the population can be saved in a* ``.pop`` *or a* ``.ppop`` *file. This allows
# different fascicles to be generated with the same proportions of axons
# but with different locations.*

if __name__ == '__main__':
    n_ax = 60
    L = 10000                       # length, in um
    d_f = 45

    fascicle_1 = nrv.fascicle(diameter=d_f, ID=1)
    fascicle_1.define_length(L)
    fascicle_1.fill(n_ax=n_ax, percent_unmyel=0.7, M_stat="Ochoa_M", U_stat="Ochoa_U", delta=5, delta_trace=0.1, with_node_shift=True)


    # Once the fascicle geometry is generated all the contexts can be added:

    # **- The intracellular context**

    position = 0.
    t_start = 1
    duration = 0.5
    amplitude = 4
    fascicle_1.insert_I_Clamp(position, t_start, duration, amplitude)


    testrec = nrv.recorder("endoneurium_bhadra")
    testrec.set_recording_point(L/4, 0, 100)
    testrec.set_recording_point(L/2, 0, 100)
    testrec.set_recording_point(3*L/4, 0, 100)
    fascicle_1.attach_extracellular_recorder(testrec)


    # **\- The extracellular context**

    # *Note that the extracellular can have an impact one the final axon population. For instance all axons overlapping with a LIFE electrode are automatically removed.*

    LIFE_stim = nrv.FEM_stimulation()
    # Simulation box size
    Outer_D = 5
    LIFE_stim.reshape_outerBox(Outer_D)
    # Nerve and fascicle geometry
    Nerve_D = d_f * 1.5
    LIFE_stim.reshape_nerve(Nerve_D, L)
    LIFE_stim.reshape_fascicle(geometry=fascicle_1.geom)
    # electrode and stimulus definition
    D_1 = 25
    length_1 = 1000
    y_c_1 = 0
    z_c_1 = 0
    x_1_offset = (L-length_1)/2
    elec_1 = nrv.LIFE_electrode("LIFE_1", D_1, length_1, x_1_offset, y_c_1, z_c_1)
    # stimulus def
    start = 1
    I_cathod = 40
    I_anod = I_cathod/5
    T_cathod = 60e-3
    T_inter = 40e-3
    stim1 = nrv.stimulus()
    stim1.biphasic_pulse(start, I_cathod, T_cathod, I_anod, T_inter)
    LIFE_stim.add_electrode(elec_1, stim1)
    fascicle_1.attach_extracellular_stimulation(LIFE_stim)

    # Save/Load Fascicle
    # ------------------

    # As the ``fascicle``-class inherits from ``NRVClass``, the save and load methods can be used to generate a python dictionary or save the properties of the fascicle (see `usersguide`).

    # As for all ``simulable``-class instances, contexts are not saved and loaded by default. One need specifies which context to save and load using boolean arguments ``extracel_context``,``intracel_context``, ``rec_context``.


    # ;
    # - *Because fascicles can take a long time to generate, the `fascicle` class is one of the few classes in NRV for which save saves automatically (without specifying `save=True` in the argument). If note is specified, the fascicle will be saved in the current directory in `fascicle.json`*.
    # - *The footprint of the electrodes on the axon can be generated before saving using `compute_electrodes_footprints`. This can increase the file size but also significantly reduce the computation time of the loaded fascicle simulation*.
    # </div>

    # .. Warning::
    # - *Some fascicle parameters (length, diameter, ...) cannot be modified if footprints are calculated*.

    fas_dict = fascicle_1.save(save=False,extracel_context=True,intracel_context=True, rec_context=True)
    #fascicle_2 = nrv.fascicle()
    fascicle_2 = nrv.load_any(fas_dict,extracel_context=True,intracel_context=True, rec_context=True)

    fig, ax = plt.subplots(1, 2, figsize=(14,6))
    fascicle_1.plot(ax[0], num=True)
    ax[0].set_title("Fascicle saved")
    fascicle_2.plot(ax[1], num=True)
    ax[1].set_title("Fascicle loaded")

    plt.show()