"""IPywidgets GUI."""
# Authors: Mainak Jas <mjas@mgh.harvard.edu>
# Huzi Cheng <hzcheng15@icloud.com>
import base64
import codecs
import io
import logging
import mimetypes
import multiprocessing
import numpy as np
import sys
import json
import urllib.parse
import urllib.request
import zipfile
from collections import defaultdict
from copy import deepcopy
from pathlib import Path
from datetime import datetime
from functools import partial
from IPython.display import IFrame, display
from ipywidgets import (HTML, Accordion, AppLayout, BoundedFloatText,
BoundedIntText, Button, Dropdown, FileUpload, VBox,
HBox, IntText, Layout, Output, RadioButtons, Tab, Text,
Checkbox)
from ipywidgets.embed import embed_minimal_html
import hnn_core
from hnn_core import JoblibBackend, MPIBackend, simulate_dipole
from hnn_core.gui._logging import logger
from hnn_core.gui._viz_manager import _VizManager, _idx2figname
from hnn_core.network import pick_connection
from hnn_core.dipole import _read_dipole_txt
from hnn_core.params_default import (get_L2Pyr_params_default,
get_L5Pyr_params_default)
from hnn_core.hnn_io import dict_to_network, write_network_configuration
from hnn_core.cells_default import _exp_g_at_dist
hnn_core_root = Path(hnn_core.__file__).parent
default_network_configuration = (hnn_core_root / 'param' /
'jones2009_base.json')
cell_parameters_dict = {
"Geometry L2":
[
('Soma length', 'micron', 'soma_L'),
('Soma diameter', 'micron', 'soma_diam'),
('Soma capacitive density', 'F/cm2', 'soma_cm'),
('Soma resistivity', 'ohm-cm', 'soma_Ra'),
('Dendrite capacitive density', 'F/cm2', 'dend_cm'),
('Dendrite resistivity', 'ohm-cm', 'dend_Ra'),
('Apical Dendrite Trunk length', 'micron', 'apicaltrunk_L'),
('Apical Dendrite Trunk diameter', 'micron', 'apicaltrunk_diam'),
('Apical Dendrite 1 length', 'micron', 'apical1_L'),
('Apical Dendrite 1 diameter', 'micron', 'apical1_diam'),
('Apical Dendrite Tuft length', 'micron', 'apicaltuft_L'),
('Apical Dendrite Tuft diameter', 'micron', 'apicaltuft_diam'),
('Oblique Apical Dendrite length', 'micron', 'apicaloblique_L'),
('Oblique Apical Dendrite diameter', 'micron', 'apicaloblique_diam'),
('Basal Dendrite 1 length', 'micron', 'basal1_L'),
('Basal Dendrite 1 diameter', 'micron', 'basal1_diam'),
('Basal Dendrite 2 length', 'micron', 'basal2_L'),
('Basal Dendrite 2 diameter', 'micron', 'basal2_diam'),
('Basal Dendrite 3 length', 'micron', 'basal3_L'),
('Basal Dendrite 3 diameter', 'micron', 'basal3_diam')
],
"Geometry L5":
[
('Soma length', 'micron', 'soma_L'),
('Soma diameter', 'micron', 'soma_diam'),
('Soma capacitive density', 'F/cm2', 'soma_cm'),
('Soma resistivity', 'ohm-cm', 'soma_Ra'),
('Dendrite capacitive density', 'F/cm2', 'dend_cm'),
('Dendrite resistivity', 'ohm-cm', 'dend_Ra'),
('Apical Dendrite Trunk length', 'micron', 'apicaltrunk_L'),
('Apical Dendrite Trunk diameter', 'micron', 'apicaltrunk_diam'),
('Apical Dendrite 1 length', 'micron', 'apical1_L'),
('Apical Dendrite 1 diameter', 'micron', 'apical1_diam'),
('Apical Dendrite 2 length', 'micron', 'apical2_L'),
('Apical Dendrite 2 diameter', 'micron', 'apical2_diam'),
('Apical Dendrite Tuft length', 'micron', 'apicaltuft_L'),
('Apical Dendrite Tuft diameter', 'micron', 'apicaltuft_diam'),
('Oblique Apical Dendrite length', 'micron', 'apicaloblique_L'),
('Oblique Apical Dendrite diameter', 'micron', 'apicaloblique_diam'),
('Basal Dendrite 1 length', 'micron', 'basal1_L'),
('Basal Dendrite 1 diameter', 'micron', 'basal1_diam'),
('Basal Dendrite 2 length', 'micron', 'basal2_L'),
('Basal Dendrite 2 diameter', 'micron', 'basal2_diam'),
('Basal Dendrite 3 length', 'micron', 'basal3_L'),
('Basal Dendrite 3 diameter', 'micron', 'basal3_diam')
],
"Synapses":
[
('AMPA reversal', 'mV', 'ampa_e'),
('AMPA rise time', 'ms', 'ampa_tau1'),
('AMPA decay time', 'ms', 'ampa_tau2'),
('NMDA reversal', 'mV', 'nmda_e'),
('NMDA rise time', 'ms', 'nmda_tau1'),
('NMDA decay time', 'ms', 'nmda_tau2'),
('GABAA reversal', 'mV', 'gabaa_e'),
('GABAA rise time', 'ms', 'gabaa_tau1'),
('GABAA decay time', 'ms', 'gabaa_tau2'),
('GABAB reversal', 'mV', 'gabab_e'),
('GABAB rise time', 'ms', 'gabab_tau1'),
('GABAB decay time', 'ms', 'gabab_tau2')
],
"Biophysics L2":
[
('Soma Kv channel density', 'S/cm2', 'soma_gkbar_hh2'),
('Soma Na channel density', 'S/cm2', 'soma_gnabar_hh2'),
('Soma leak reversal', 'mV', 'soma_el_hh2'),
('Soma leak channel density', 'S/cm2', 'soma_gl_hh2'),
('Soma Km channel density', 'pS/micron2', 'soma_gbar_km'),
('Dendrite Kv channel density', 'S/cm2', 'dend_gkbar_hh2'),
('Dendrite Na channel density', 'S/cm2', 'dend_gnabar_hh2'),
('Dendrite leak reversal', 'mV', 'dend_el_hh2'),
('Dendrite leak channel density', 'S/cm2', 'dend_gl_hh2'),
('Dendrite Km channel density', 'pS/micron2', 'dend_gbar_km')
],
"Biophysics L5":
[
('Soma Kv channel density', 'S/cm2', 'soma_gkbar_hh2'),
('Soma Na channel density', 'S/cm2', 'soma_gnabar_hh2'),
('Soma leak reversal', 'mV', 'soma_el_hh2'),
('Soma leak channel density', 'S/cm2', 'soma_gl_hh2'),
('Soma Ca channel density', 'pS/micron2', 'soma_gbar_ca'),
('Soma Ca decay time', 'ms', 'soma_taur_cad'),
('Soma Kca channel density', 'pS/micron2', 'soma_gbar_kca'),
('Soma Km channel density', 'pS/micron2', 'soma_gbar_km'),
('Soma CaT channel density', 'S/cm2', 'soma_gbar_cat'),
('Soma HCN channel density', 'S/cm2', 'soma_gbar_ar'),
('Dendrite Kv channel density', 'S/cm2', 'dend_gkbar_hh2'),
('Dendrite Na channel density', 'S/cm2', 'dend_gnabar_hh2'),
('Dendrite leak reversal', 'mV', 'dend_el_hh2'),
('Dendrite leak channel density', 'S/cm2', 'dend_gl_hh2'),
('Dendrite Ca channel density', 'pS/micron2', 'dend_gbar_ca'),
('Dendrite Ca decay time', 'ms', 'dend_taur_cad'),
('Dendrite KCa channel density', 'pS/micron2', 'dend_gbar_kca'),
('Dendrite Km channel density', 'pS/micron2', 'dend_gbar_km'),
('Dendrite CaT channel density', 'S/cm2', 'dend_gbar_cat'),
('Dendrite HCN channel density', 'S/cm2', 'dend_gbar_ar')
]
}
class _OutputWidgetHandler(logging.Handler):
def __init__(self, output_widget, *args, **kwargs):
super(_OutputWidgetHandler, self).__init__(*args, **kwargs)
self.out = output_widget
def emit(self, record):
formatted_record = self.format(record)
new_output = {
'name': 'stdout',
'output_type': 'stream',
'text': formatted_record + '\n'
}
self.out.outputs = (new_output, ) + self.out.outputs
[docs]class HNNGUI:
"""HNN GUI class
Parameters
----------
theme_color : str
The theme color of the whole dashboard.
total_height : int
The height of the GUI (in pixel, same for all following parameters).
total_width : int
The width of the GUI.
header_height : int
The height of the header.
button_height : int
The height of buttons.
operation_box_height : int
The operation_box_height of operations box.
drive_widget_width : int
The width of GUI drive box.
left_sidebar_width : int
The width of left sidebad.
log_window_height : int
The height of logging window.
status_height : int
The height of status bar.
dpi : int
The screen dpi.
Attributes
----------
layout : dict
The styling configuration of GUI.
params : dict
The parameters to use for constructing the network.
simulation_data : dict
Simulation related objects, such as net and dpls.
widget_tstop : Widget
Simulation stop time widget.
widget_dt : Widget
Simulation step size widget.
widget_ntrials : Widget
Widget that controls the number of trials in a single simulation.
widget_backend_selection : Widget
Widget that selects the backend used in simulations.
widget_viz_layout_selection : Widget
Widget that selects the layout of visualization window.
widget_mpi_cmd : Widget
Widget that specify the mpi command to use when the backend is
MPIBackend.
widget_n_jobs : Widget
Widget that specify the cores in multi-trial simulations.
widget_drive_type_selection : Widget
Widget that is used to select the drive to be added to the network.
widget_location_selection : Widget.
Widget that specifies the location of network drives. Could be proximal
or distal.
add_drive_button : Widget
Clickable widget that is used to add a drive to the network.
run_button : Widget
Clickable widget that triggers simulation.
load_button : Widget
Clickable widget that receives uploaded parameter files.
delete_drive_button : Widget
Clickable widget that clear all existing network drives.
plot_outputs_dict : list
A list of visualization panel outputs.
plot_dropdown_types_dict : list
A list of dropdown menus that control the plot types in
plot_outputs_dict.
drive_widgets : list
A list of network drive widgets added by add_drive_button.
drive_boxes : list
A list of network drive layouts.
connectivity_textfields : list
A list of boxes that control the weight and probability of connections
in the network.
"""
def __init__(self, theme_color="#802989",
total_height=800,
total_width=1300,
header_height=50,
button_height=30,
operation_box_height=60,
drive_widget_width=200,
left_sidebar_width=576,
log_window_height=150,
status_height=30,
dpi=96,
network_configuration=default_network_configuration,
):
# set up styling.
self.total_height = total_height
self.total_width = total_width
viz_win_width = self.total_width - left_sidebar_width
main_content_height = self.total_height - status_height
config_box_height = main_content_height - (log_window_height +
operation_box_height)
self.layout = {
"dpi": dpi,
"header_height": f"{header_height}px",
"theme_color": theme_color,
"btn": Layout(height=f"{button_height}px", width='auto'),
"run_btn": Layout(height=f"{button_height}px", width='10%'),
"btn_full_w": Layout(height=f"{button_height}px", width='100%'),
"del_fig_btn": Layout(height=f"{button_height}px", width='auto'),
"log_out": Layout(border='1px solid gray',
height=f"{log_window_height - 10}px",
overflow='auto'),
"viz_config": Layout(width='99%'),
"simulations_list": Layout(width=f'{left_sidebar_width - 50}px'),
"visualization_window": Layout(
width=f"{viz_win_width - 10}px",
height=f"{main_content_height - 10}px",
border='1px solid gray',
overflow='scroll'),
"visualization_output": Layout(
width=f"{viz_win_width - 50}px",
height=f"{main_content_height - 100}px",
border='1px solid gray',
overflow='scroll'),
"left_sidebar": Layout(width=f"{left_sidebar_width}px",
height=f"{main_content_height}px"),
"left_tab": Layout(width=f"{left_sidebar_width}px",
height=f"{config_box_height}px"),
"operation_box": Layout(width=f"{left_sidebar_width}px",
height=f"{operation_box_height}px",
flex_wrap="wrap",
),
"config_box": Layout(width=f"{left_sidebar_width}px",
height=f"{config_box_height - 100}px"),
"drive_widget": Layout(width="auto"),
"drive_textbox": Layout(width='270px', height='auto'),
# simulation status related
"simulation_status_height": f"{status_height}px",
"simulation_status_common": "background:gray;padding-left:10px",
"simulation_status_running": "background:orange;padding-left:10px",
"simulation_status_failed": "background:red;padding-left:10px",
"simulation_status_finished": "background:green;padding-left:10px",
}
self._simulation_status_contents = {
"not_running":
f"""<div style='{self.layout['simulation_status_common']};
color:white;'>Not running</div>""",
"running":
f"""<div style='{self.layout['simulation_status_running']};
color:white;'>Running...</div>""",
"finished":
f"""<div style='{self.layout['simulation_status_finished']};
color:white;'>Simulation finished</div>""",
"failed":
f"""<div style='{self.layout['simulation_status_failed']};
color:white;'>Simulation failed</div>""",
}
# load default parameters
self.params = self.load_parameters(network_configuration)
# In-memory storage of all simulation and visualization related data
self.simulation_data = defaultdict(lambda: dict(net=None, dpls=list()))
# Simulation parameters
self.widget_tstop = BoundedFloatText(
value=170, description='tstop (ms):', min=0, max=1e6, step=1,
disabled=False)
self.widget_dt = BoundedFloatText(
value=0.025, description='dt (ms):', min=0, max=10, step=0.01,
disabled=False)
self.widget_ntrials = IntText(value=1, description='Trials:',
disabled=False)
self.widget_simulation_name = Text(value='default',
placeholder='ID of your simulation',
description='Name:',
disabled=False)
self.widget_backend_selection = Dropdown(options=[('Joblib', 'Joblib'),
('MPI', 'MPI')],
value='Joblib',
description='Backend:')
self.widget_mpi_cmd = Text(value='mpiexec',
placeholder='Fill if applies',
description='MPI cmd:', disabled=False)
self.widget_n_jobs = BoundedIntText(value=1, min=1,
max=multiprocessing.cpu_count(),
description='Cores:',
disabled=False)
self.load_data_button = FileUpload(
accept='.txt,.csv', multiple=False,
style={'button_color': self.layout['theme_color']},
layout=self.layout['btn'],
description='Load data',
button_style='success')
# Create save simulation widget wrapper
self.save_simuation_button = self._init_html_download_button(
title='Save Simulation', mimetype='text/csv')
self.save_config_button = self._init_html_download_button(
title='Save Network', mimetype='application/json')
self.simulation_list_widget = Dropdown(options=[],
value=None,
description='',
layout={'width': '15%'})
# Drive selection
self.widget_drive_type_selection = RadioButtons(
options=['Evoked', 'Poisson', 'Rhythmic', 'Tonic'],
value='Evoked',
description='Drive:',
disabled=False,
layout=self.layout['drive_widget'])
self.widget_location_selection = RadioButtons(
options=['proximal', 'distal'], value='proximal',
description='Location', disabled=False,
layout=self.layout['drive_widget'])
self.add_drive_button = create_expanded_button(
'Add drive', 'primary', layout=self.layout['btn'],
button_color=self.layout['theme_color'])
# Dashboard level buttons
self.run_button = create_expanded_button(
'Run', 'success', layout=self.layout['run_btn'],
button_color=self.layout['theme_color'])
self.load_connectivity_button = FileUpload(
accept='.json', multiple=False,
style={'button_color': self.layout['theme_color']},
description='Load local network connectivity',
layout=self.layout['btn_full_w'], button_style='success')
self.load_drives_button = FileUpload(
accept='.json', multiple=False,
style={'button_color': self.layout['theme_color']},
description='Load external drives', layout=self.layout['btn'],
button_style='success')
self.delete_drive_button = create_expanded_button(
'Delete drives', 'success', layout=self.layout['btn'],
button_color=self.layout['theme_color'])
self.cell_type_radio_buttons = RadioButtons(
options=['L2 Pyramidal', 'L5 Pyramidal'],
description='Cell type:')
self.cell_layer_radio_buttons = RadioButtons(
options=['Geometry', 'Synapses', 'Biophysics'],
description='Cell Properties:')
# Plotting window
# Visualization figure related dicts
self.plot_outputs_dict = dict()
self.plot_dropdown_types_dict = dict()
self.plot_sim_selections_dict = dict()
# Add drive section
self.drive_widgets = list()
self.drive_boxes = list()
# Connectivity list
self.connectivity_widgets = list()
# Cell parameter list
self.cell_pameters_widgets = dict()
self._init_ui_components()
self.add_logging_window_logger()
[docs] def get_cell_parameters_dict(self):
"""Returns the number of elements in the
cell_parameters_dict dictionary.
This is for testing purposes """
return cell_parameters_dict
def _init_html_download_button(self, title, mimetype):
b64 = base64.b64encode("".encode())
payload = b64.decode()
# Initialliting HTML code for download button
self.html_download_button = '''
<a download="{filename}" href="data:{mimetype};base64,{payload}"
download>
<button style="background:{color_theme}; height:{btn_height}"
class=" jupyter-button
mod-warning" {is_disabled} >{title}</button>
</a>
'''
# Create widget wrapper
return (
HTML(self.html_download_button.
format(payload=payload,
filename={""},
is_disabled="disabled",
btn_height=self.layout['run_btn'].height,
color_theme=self.layout['theme_color'],
title=title,
mimetype=mimetype)))
def add_logging_window_logger(self):
handler = _OutputWidgetHandler(self._log_out)
handler.setFormatter(
logging.Formatter('%(asctime)s - [%(levelname)s] %(message)s'))
logger.addHandler(handler)
def _init_ui_components(self):
"""Initialize larger UI components and dynamical output windows.
It's not encouraged for users to modify or access attributes in this
part.
"""
# dynamic larger components
self._drives_out = Output() # tab to add new drives
self._connectivity_out = Output() # tab to tune connectivity.
self._cell_params_out = Output()
self._log_out = Output()
self.viz_manager = _VizManager(self.data, self.layout)
# detailed configuration of backends
self._backend_config_out = Output()
# static parts
# Running status
self._simulation_status_bar = HTML(
value=self._simulation_status_contents['not_running'])
self._log_window = HBox([self._log_out], layout=self.layout['log_out'])
self._operation_buttons = HBox(
[self.run_button, self.load_data_button,
self.save_config_button,
self.save_simuation_button,
self.simulation_list_widget],
layout=self.layout['operation_box'])
# title
self._header = HTML(value=f"""<div
style='background:{self.layout['theme_color']};
text-align:center;color:white;'>
HUMAN NEOCORTICAL NEUROSOLVER</div>""")
@property
def analysis_config(self):
"""Provides everything viz window needs except for the data."""
return {
"viz_style": self.layout['visualization_output'],
# widgets
"plot_outputs": self.plot_outputs_dict,
"plot_dropdowns": self.plot_dropdown_types_dict,
"plot_sim_selections": self.plot_sim_selections_dict,
"current_sim_name": self.widget_simulation_name.value,
}
@property
def data(self):
"""Provides easy access to simulation-related data."""
return {"simulation_data": self.simulation_data}
[docs] @staticmethod
def load_parameters(params_fname):
"""Read parameters from file."""
with open(params_fname, 'r') as file:
parameters = json.load(file)
return parameters
def _link_callbacks(self):
"""Link callbacks to UI components."""
def _handle_backend_change(backend_type):
return handle_backend_change(backend_type.new,
self._backend_config_out,
self.widget_mpi_cmd,
self.widget_n_jobs)
def _add_drive_button_clicked(b):
return add_drive_widget(self.widget_drive_type_selection.value,
self.drive_boxes, self.drive_widgets,
self._drives_out, self.widget_tstop,
self.widget_location_selection.value,
layout=self.layout['drive_textbox'])
def _delete_drives_clicked(b):
self._drives_out.clear_output()
# black magic: the following does not work
# global drive_widgets; drive_widgets = list()
while len(self.drive_widgets) > 0:
self.drive_widgets.pop()
self.drive_boxes.pop()
def _on_upload_connectivity(change):
new_params = on_upload_params_change(
change, self.widget_tstop, self.widget_dt,
self._log_out, self.drive_boxes, self.drive_widgets,
self._drives_out, self._connectivity_out,
self.connectivity_widgets, self._cell_params_out,
self.cell_pameters_widgets, self.cell_layer_radio_buttons,
self.cell_type_radio_buttons, self.layout['drive_textbox'],
"connectivity")
self.params = new_params
def _on_upload_drives(change):
_ = on_upload_params_change(
change, self.widget_tstop, self.widget_dt,
self._log_out, self.drive_boxes, self.drive_widgets,
self._drives_out, self._connectivity_out,
self.connectivity_widgets, self._cell_params_out,
self.cell_pameters_widgets, self.cell_layer_radio_buttons,
self.cell_type_radio_buttons, self.layout['drive_textbox'],
"drives")
def _on_upload_data(change):
return on_upload_data_change(change, self.data, self.viz_manager,
self._log_out)
def _run_button_clicked(b):
return run_button_clicked(
self.widget_simulation_name, self._log_out, self.drive_widgets,
self.data, self.widget_dt, self.widget_tstop,
self.widget_ntrials, self.widget_backend_selection,
self.widget_mpi_cmd, self.widget_n_jobs, self.params,
self._simulation_status_bar, self._simulation_status_contents,
self.connectivity_widgets, self.viz_manager,
self.simulation_list_widget, self.cell_pameters_widgets)
def _simulation_list_change(value):
# Simulation Data
_simulation_data, file_extension = (
_serialize_simulation(self._log_out,
self.data,
self.simulation_list_widget))
result_file = f"{value.new}{file_extension}"
if file_extension == ".csv":
b64 = base64.b64encode(_simulation_data.encode())
else:
b64 = base64.b64encode(_simulation_data)
payload = b64.decode()
self.save_simuation_button.value = (
self.html_download_button.format(
payload=payload, filename=result_file,
is_disabled="", btn_height=self.layout['run_btn'].height,
color_theme=self.layout['theme_color'],
title='Save Simulation', mimetype='text/csv'))
# Network Configuration
network_config = _serialize_config(self._log_out,
self.data,
self.simulation_list_widget)
b64_net = base64.b64encode(network_config.encode())
self.save_config_button.value = (
self.html_download_button.format(
payload=b64_net.decode(),
filename=f"{value.new}.json",
is_disabled="",
btn_height=self.layout['run_btn'].height,
color_theme=self.layout['theme_color'],
title='Save Network', mimetype='application/json'))
def _driver_type_change(value):
self.widget_location_selection.disabled = (
True if value.new == "Tonic" else False)
def _cell_type_radio_change(value):
_update_cell_params_vbox(self._cell_params_out,
self.cell_pameters_widgets,
value.new,
self.cell_layer_radio_buttons.value)
def _cell_layer_radio_change(value):
_update_cell_params_vbox(self._cell_params_out,
self.cell_pameters_widgets,
self.cell_type_radio_buttons.value,
value.new)
self.widget_backend_selection.observe(_handle_backend_change, 'value')
self.add_drive_button.on_click(_add_drive_button_clicked)
self.delete_drive_button.on_click(_delete_drives_clicked)
self.load_connectivity_button.observe(_on_upload_connectivity,
names='value')
self.load_drives_button.observe(_on_upload_drives, names='value')
self.run_button.on_click(_run_button_clicked)
self.load_data_button.observe(_on_upload_data, names='value')
self.simulation_list_widget.observe(_simulation_list_change, 'value')
self.widget_drive_type_selection.observe(_driver_type_change, 'value')
self.cell_type_radio_buttons.observe(_cell_type_radio_change,
'value')
self.cell_layer_radio_buttons.observe(_cell_layer_radio_change,
'value')
[docs] def compose(self, return_layout=True):
"""Compose widgets.
Parameters
----------
return_layout : bool
If the method returns the layout object which can be rendered by
IPython.display.display() method.
"""
simulation_box = VBox([
VBox([
self.widget_simulation_name, self.widget_tstop, self.widget_dt,
self.widget_ntrials, self.widget_backend_selection,
self._backend_config_out]),
], layout=self.layout['config_box'])
connectivity_configuration = Tab()
connectivity_box = VBox([
HBox([self.load_connectivity_button, ]),
self._connectivity_out,
])
cell_parameters = VBox([
HBox([self.cell_type_radio_buttons,
self.cell_layer_radio_buttons]),
self._cell_params_out
])
connectivity_configuration.children = [connectivity_box,
cell_parameters]
connectivity_configuration.titles = ['Connectivity',
'Cell parameters']
drive_selections = VBox([
self.add_drive_button, self.widget_drive_type_selection,
self.widget_location_selection],
layout=Layout(flex="1"))
drives_options = VBox([
HBox([
VBox([self.load_drives_button, self.delete_drive_button],
layout=Layout(flex="1")),
drive_selections,
]), self._drives_out
])
config_panel, figs_output = self.viz_manager.compose()
# Tabs for left pane
left_tab = Tab()
left_tab.children = [
simulation_box, connectivity_configuration, drives_options,
config_panel,
]
titles = ('Simulation', 'Network', 'External drives',
'Visualization')
for idx, title in enumerate(titles):
left_tab.set_title(idx, title)
self.app_layout = AppLayout(
header=self._header,
left_sidebar=VBox([
VBox([left_tab], layout=self.layout['left_tab']),
self._operation_buttons,
self._log_window,
], layout=self.layout['left_sidebar']),
right_sidebar=figs_output,
footer=self._simulation_status_bar,
pane_widths=[
self.layout['left_sidebar'].width, '0px',
self.layout['visualization_window'].width
],
pane_heights=[
self.layout['header_height'],
self.layout['visualization_window'].height,
self.layout['simulation_status_height']
],
)
self._link_callbacks()
# initialize drive and connectivity ipywidgets
load_drive_and_connectivity(self.params, self._log_out,
self._drives_out, self.drive_widgets,
self.drive_boxes, self._connectivity_out,
self.connectivity_widgets,
self._cell_params_out,
self.cell_pameters_widgets,
self.cell_layer_radio_buttons,
self.cell_type_radio_buttons,
self.widget_tstop, self.layout)
if not return_layout:
return
else:
return self.app_layout
def show(self):
display(self.app_layout)
[docs] def capture(self, width=None, height=None, extra_margin=100, render=True):
"""Take a screenshot of the current GUI.
Parameters
----------
width : int | None
The width of iframe window use to show the snapshot.
height : int | None
The height of iframe window use to show the snapshot.
extra_margin: int
Extra margin in pixel for the GUI.
render : bool
Will return an IFrame object if False
Returns
-------
snapshot : An iframe snapshot object that can be rendered in notebooks.
"""
file = io.StringIO()
embed_minimal_html(file, views=[self.app_layout], title='')
if not width:
width = self.total_width + extra_margin
if not height:
height = self.total_height + extra_margin
content = urllib.parse.quote(file.getvalue().encode('utf8'))
data_url = f"data:text/html,{content}"
screenshot = IFrame(data_url, width=width, height=height)
if render:
display(screenshot)
else:
return screenshot
[docs] def run_notebook_cells(self):
"""Run all but the last cells sequentially in a Jupyter notebook.
To properly use this function:
1. Put this into the penultimate cell.
2. init the HNNGUI in a single cell.
3. Hit 'run all' button to run the whole notebook and it will
selectively run twice.
"""
js_string = """
function sleep(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
function getRunningStatus(idx){
const htmlContent = Jupyter.notebook.get_cell(idx).element[0];
return htmlContent.childNodes[0].childNodes[0].textContent;
}
function cellContainsInitOrMarkdown(idx){
const cell = Jupyter.notebook.get_cell(idx);
if(cell.cell_type!=='code'){
return true;
}
else{
const textVal = cell.element[0].childNodes[0].textContent;
return textVal.includes('HNNGUI()') || textVal.includes(
'HNNGUI');
}
}
function cellContainsRunCells(idx){
const textVal = Jupyter.notebook.get_cell(
idx).element[0].childNodes[0].textContent;
return textVal.includes('run_notebook_cells()');
}
async function runNotebook() {
console.log("run notebook cell by cell");
const cellHtmlContents = Jupyter.notebook.element[0].children[0];
const nCells = cellHtmlContents.childElementCount;
console.log(`In total we have ${nCells} cells`);
for(let i=1; i<nCells-1; i++){
if(cellContainsRunCells(i)){
break
}
else if(cellContainsInitOrMarkdown(i)){
console.log(`Skip init or markdown cell ${i}...`);
continue
}
else{
console.log(`About to execute cell ${i}..`);
Jupyter.notebook.execute_cells([i]);
while (getRunningStatus(i).includes("*")){
console.log("Still running, wait for another 2 secs");
await sleep(2000);
}
await sleep(1000);
}
}
console.log('Done');
}
runNotebook();
"""
return js_string
# below are a series of methods that are used to manipulate the GUI
def _simulate_upload_data(self, file_url):
uploaded_value = _prepare_upload_file(file_url)
self.load_data_button.set_trait('value', uploaded_value)
def _simulate_upload_connectivity(self, file_url):
uploaded_value = _prepare_upload_file(file_url)
self.load_connectivity_button.set_trait('value', uploaded_value)
def _simulate_upload_drives(self, file_url):
uploaded_value = _prepare_upload_file(file_url)
self.load_drives_button.set_trait('value', uploaded_value)
def _simulate_left_tab_click(self, tab_title):
# Get left tab group object
left_tab = self.app_layout.left_sidebar.children[0].children[0]
# Check that the title is in the tab group
if tab_title in left_tab.titles:
# Simulate the user clicking on the tab
left_tab.selected_index = left_tab.titles.index(tab_title)
else:
raise ValueError("Tab title does not exist.")
def _simulate_make_figure(self,):
self._simulate_left_tab_click("Visualization")
self.viz_manager.make_fig_button.click()
def _simulate_viz_action(self, action_name, *args, **kwargs):
"""A shortcut to call simulated actions in _VizManager.
Parameters
----------
action_name : str
The action to take. For example, to call `_simulate_add_fig` in
_VizManager, you can run `_simulate_viz_action("add_fig")`
args : list
Optional positional parameters passed to the called method.
kwargs: dict
Optional keyword parameters passed to the called method.
"""
self._simulate_left_tab_click("Visualization")
action = getattr(self.viz_manager, f"_simulate_{action_name}")
action(*args, **kwargs)
def _prepare_upload_file_from_local(path):
path = Path(path)
with open(path, 'rb') as file:
content = memoryview(file.read())
last_modified = datetime.fromtimestamp(path.stat().st_mtime)
upload_structure = [{
'name': path.name,
'type': mimetypes.guess_type(path)[0],
'size': path.stat().st_size,
'content': content,
'last_modified': last_modified
}]
return upload_structure
def _prepare_upload_file_from_url(file_url):
file_name = file_url.split("/")[-1]
data = urllib.request.urlopen(file_url)
content = bytearray()
for line in data:
content.extend(line)
upload_structure = [{
'name': file_name,
'type': mimetypes.guess_type(file_url)[0],
'size': len(content),
'content': memoryview(content),
'last_modified': datetime.now()
}]
return upload_structure
def _prepare_upload_file(path):
""" Simulates output of the FileUpload widget for testing.
Unit tests for the GUI simulate user upload of files. File source can
either be local or from a URL. This function returns the data structure
of the ipywidget FileUpload widget, a list of dictionaries with file
attributes.
"""
try:
uploaded_value = _prepare_upload_file_from_local(path)
except (FileNotFoundError, OSError):
uploaded_value = _prepare_upload_file_from_url(path)
return uploaded_value
def _update_nested_dict(original, new, skip_none=True):
""" Updates dictionary values from another dictionary
Will update nested dictionaries in the structure. New items from the
update dictionary are added and omitted items are retained from the
original dictionary. By default, will not pass None values from the update
dictionary.
Parameters
----------
original : dict
Dictionary to update
new : dict
Dictionary with new values for updating
skip_none : bool, default True
None values in the new dictionary are not passed to the updated
dictionary by when True. If False None values will be passed to the
updated dictionary.
Returns dict
-------
"""
updated = original.copy()
for key, value in new.items():
if (isinstance(value, dict) and
key in updated and
isinstance(updated[key], dict)):
updated[key] = _update_nested_dict(updated[key], value, skip_none)
elif (value is not None) or (not skip_none):
updated[key] = value
else:
pass
return updated
def create_expanded_button(description, button_style, layout, disabled=False,
button_color="#8A2BE2"):
return Button(description=description, button_style=button_style,
layout=layout, style={'button_color': button_color},
disabled=disabled)
def _get_connectivity_widgets(conn_data):
"""Create connectivity box widgets from specified weight and probability"""
style = {'description_width': '150px'}
style = {}
sliders = list()
for receptor_name in conn_data.keys():
w_text_input = BoundedFloatText(
value=conn_data[receptor_name]['weight'], disabled=False,
continuous_update=False, min=0, max=1e6, step=0.01,
description="weight", style=style)
conn_widget = VBox([
HTML(value=f"""<p>
Receptor: {conn_data[receptor_name]['receptor']}</p>"""),
w_text_input, HTML(value="<hr style='margin-bottom:5px'/>")
])
conn_widget._belongsto = {
"receptor": conn_data[receptor_name]['receptor'],
"location": conn_data[receptor_name]['location'],
"src_gids": conn_data[receptor_name]['src_gids'],
"target_gids": conn_data[receptor_name]['target_gids'],
}
sliders.append(conn_widget)
return sliders
def _get_drive_weight_widgets(layout, style, location, data=None):
default_data = {
'weights_ampa': {
'L5_pyramidal': 0.,
'L2_pyramidal': 0.,
'L5_basket': 0.,
'L2_basket': 0.
},
'weights_nmda': {
'L5_pyramidal': 0.,
'L2_pyramidal': 0.,
'L5_basket': 0.,
'L2_basket': 0.
},
'delays': {
'L5_pyramidal': 0.1,
'L2_pyramidal': 0.1,
'L5_basket': 0.1,
'L2_basket': 0.1
},
}
if isinstance(data, dict):
default_data = _update_nested_dict(default_data, data)
kwargs = dict(layout=layout, style=style)
cell_types = ['L5_pyramidal', 'L2_pyramidal', 'L5_basket', 'L2_basket']
if location == "distal":
cell_types.remove('L5_basket')
weights_ampa, weights_nmda, delays = dict(), dict(), dict()
for cell_type in cell_types:
weights_ampa[f'{cell_type}'] = BoundedFloatText(
value=default_data['weights_ampa'][cell_type],
description=f'{cell_type}:', min=0, max=1e6, step=0.01, **kwargs)
weights_nmda[f'{cell_type}'] = BoundedFloatText(
value=default_data['weights_nmda'][cell_type],
description=f'{cell_type}:', min=0, max=1e6, step=0.01, **kwargs)
delays[f'{cell_type}'] = BoundedFloatText(
value=default_data['delays'][cell_type],
description=f'{cell_type}:', min=0, max=1e6, step=0.1, **kwargs)
widgets_dict = {
'weights_ampa': weights_ampa,
'weights_nmda': weights_nmda,
'delays': delays
}
widgets_list = ([HTML(value="<b>AMPA weights</b>")] +
list(weights_ampa.values()) +
[HTML(value="<b>NMDA weights</b>")] +
list(weights_nmda.values()) +
[HTML(value="<b>Synaptic delays</b>")] +
list(delays.values()))
return widgets_list, widgets_dict
def _cell_spec_change(change, widget):
if change['new']:
widget.disabled = True
else:
widget.disabled = False
def _get_rhythmic_widget(name, tstop_widget, layout, style, location,
data={}, weights_ampa=None,
weights_nmda=None, delays=None,
n_drive_cells=None, cell_specific=None
):
default_data = {
'tstart': 0.,
'tstart_std': 0.,
'tstop': tstop_widget.value,
'burst_rate': 7.5,
'burst_std': 0,
'numspikes': 1,
'n_drive_cells': 1,
'cell_specific': False,
'seedcore': 14,
}
data.update({'n_drive_cells': n_drive_cells,
'cell_specific': cell_specific})
default_data = _update_nested_dict(default_data, data)
kwargs = dict(layout=layout, style=style)
tstart = BoundedFloatText(
value=default_data['tstart'], description='Start time (ms)',
min=0, max=1e6, **kwargs)
tstart_std = BoundedFloatText(
value=default_data['tstart_std'], description='Start time dev (ms)',
min=0, max=1e6, **kwargs)
tstop = BoundedFloatText(
value=default_data['tstop'],
description='Stop time (ms)',
max=tstop_widget.value,
**kwargs,
)
burst_rate = BoundedFloatText(
value=default_data['burst_rate'], description='Burst rate (Hz)',
min=0, max=1e6, **kwargs)
burst_std = BoundedFloatText(
value=default_data['burst_std'], description='Burst std dev (Hz)',
min=0, max=1e6, **kwargs)
numspikes = BoundedIntText(
value=default_data['numspikes'], description='No. Spikes:', min=0,
max=int(1e6), **kwargs)
n_drive_cells = IntText(value=default_data['n_drive_cells'],
description='No. Drive Cells:',
disabled=default_data['cell_specific'],
**kwargs)
cell_specific = Checkbox(value=default_data['cell_specific'],
description='Cell-Specific',
**kwargs)
seedcore = IntText(value=default_data['seedcore'],
description='Seed',
**kwargs)
widgets_list, widgets_dict = _get_drive_weight_widgets(
layout,
style,
location,
data={
'weights_ampa': weights_ampa,
'weights_nmda': weights_nmda,
'delays': delays,
},
)
# Disable n_drive_cells widget based on cell_specific checkbox
cell_specific.observe(partial(_cell_spec_change, widget=n_drive_cells),
names='value')
drive_box = VBox([tstart, tstart_std, tstop,
burst_rate, burst_std, numspikes,
n_drive_cells, cell_specific,
seedcore] + widgets_list)
drive = dict(type='Rhythmic',
name=name,
tstart=tstart,
tstart_std=tstart_std,
burst_rate=burst_rate,
burst_std=burst_std,
numspikes=numspikes,
seedcore=seedcore,
location=location,
tstop=tstop,
n_drive_cells=n_drive_cells,
is_cell_specific=cell_specific,
)
drive.update(widgets_dict)
return drive, drive_box
def _get_poisson_widget(name, tstop_widget, layout, style, location, data={},
weights_ampa=None, weights_nmda=None,
delays=None, n_drive_cells=None,
cell_specific=None):
default_data = {
'tstart': 0.0,
'tstop': tstop_widget.value,
'n_drive_cells': 1,
'cell_specific': True,
'seedcore': 14,
'rate_constant': {
'L2_pyramidal': 40.,
'L5_pyramidal': 40.,
'L2_basket': 40.,
'L5_basket': 40.,
}
}
data.update({'n_drive_cells': n_drive_cells,
'cell_specific': cell_specific})
default_data = _update_nested_dict(default_data, data)
tstart = BoundedFloatText(
value=default_data['tstart'], description='Start time (ms)',
min=0, max=1e6, layout=layout, style=style)
tstop = BoundedFloatText(
value=default_data['tstop'],
max=tstop_widget.value,
description='Stop time (ms)',
layout=layout,
style=style,
)
n_drive_cells = IntText(value=default_data['n_drive_cells'],
description='No. Drive Cells:',
disabled=default_data['cell_specific'],
layout=layout,
style=style
)
cell_specific = Checkbox(value=default_data['cell_specific'],
description='Cell-Specific',
layout=layout,
style=style
)
seedcore = IntText(value=default_data['seedcore'],
description='Seed',
layout=layout,
style=style)
cell_types = ['L5_pyramidal', 'L2_pyramidal', 'L5_basket', 'L2_basket']
rate_constant = dict()
for cell_type in cell_types:
rate_constant[f'{cell_type}'] = BoundedFloatText(
value=default_data['rate_constant'][cell_type],
description=f'{cell_type}:', min=0, max=1e6, step=0.01,
layout=layout, style=style)
widgets_list, widgets_dict = _get_drive_weight_widgets(
layout,
style,
location,
data={
'weights_ampa': weights_ampa,
'weights_nmda': weights_nmda,
'delays': delays,
},
)
widgets_dict.update({'rate_constant': rate_constant})
widgets_list.extend([HTML(value="<b>Rate constants</b>")] +
list(widgets_dict['rate_constant'].values()))
# Disable n_drive_cells widget based on cell_specific checkbox
cell_specific.observe(partial(_cell_spec_change, widget=n_drive_cells),
names='value')
drive_box = VBox([tstart, tstop, n_drive_cells,
cell_specific, seedcore] + widgets_list)
drive = dict(
type='Poisson',
name=name,
tstart=tstart,
tstop=tstop,
rate_constant=rate_constant,
seedcore=seedcore,
location=location, # notice this is a widget but a str!
n_drive_cells=n_drive_cells,
is_cell_specific=cell_specific,
)
drive.update(widgets_dict)
return drive, drive_box
def _get_evoked_widget(name, layout, style, location, data={},
weights_ampa=None, weights_nmda=None,
delays=None, n_drive_cells=None, cell_specific=None):
default_data = {
'mu': 0,
'sigma': 1,
'numspikes': 1,
'n_drive_cells': 1,
'cell_specific': True,
'seedcore': 14,
}
data.update({'n_drive_cells': n_drive_cells,
'cell_specific': cell_specific})
default_data = _update_nested_dict(default_data, data)
kwargs = dict(layout=layout, style=style)
mu = BoundedFloatText(
value=default_data['mu'], description='Mean time:', min=0, max=1e6,
step=0.01, **kwargs)
sigma = BoundedFloatText(
value=default_data['sigma'], description='Std dev time:', min=0,
max=1e6, step=0.01, **kwargs)
numspikes = IntText(value=default_data['numspikes'],
description='No. Spikes:',
**kwargs)
n_drive_cells = IntText(value=default_data['n_drive_cells'],
description='No. Drive Cells:',
disabled=default_data['cell_specific'],
**kwargs)
cell_specific = Checkbox(value=default_data['cell_specific'],
description='Cell-Specific',
**kwargs)
seedcore = IntText(value=default_data['seedcore'],
description='Seed: ',
**kwargs)
widgets_list, widgets_dict = _get_drive_weight_widgets(
layout,
style,
location,
data={
'weights_ampa': weights_ampa,
'weights_nmda': weights_nmda,
'delays': delays,
},
)
# Disable n_drive_cells widget based on cell_specific checkbox
cell_specific.observe(partial(_cell_spec_change, widget=n_drive_cells),
names='value')
drive_box = VBox([mu, sigma, numspikes, n_drive_cells,
cell_specific, seedcore,] +
widgets_list)
drive = dict(type='Evoked',
name=name,
mu=mu,
sigma=sigma,
numspikes=numspikes,
seedcore=seedcore,
location=location,
sync_within_trial=False,
n_drive_cells=n_drive_cells,
is_cell_specific=cell_specific)
drive.update(widgets_dict)
return drive, drive_box
def _get_tonic_widget(name, tstop_widget, layout, style, data=None):
cell_types = ['L2_basket', 'L2_pyramidal', 'L5_basket', 'L5_pyramidal']
default_values = {
'amplitude': 0,
't0': 0,
'tstop': tstop_widget.value
}
t0 = default_values['t0']
tstop = default_values['tstop']
default_data = {cell_type: default_values for cell_type in cell_types}
kwargs = dict(layout=layout, style=style)
if isinstance(data, dict):
default_data = _update_nested_dict(default_data, data)
amplitudes = dict()
for cell_type in cell_types:
amplitude = default_data[cell_type]['amplitude']
amplitudes[cell_type] = BoundedFloatText(
value=amplitude, description=cell_type,
min=0, max=1e6, step=0.01, **kwargs)
# Reset the global t0 and stop with values from the 'data' keyword.
# It should be same across all the cell-types.
if amplitude > 0:
t0 = default_data[cell_type]['t0']
tstop = default_data[cell_type]['tstop']
start_times = BoundedFloatText(
value=t0, description="Start time",
min=0, max=1e6, step=1.0, **kwargs)
stop_times = BoundedFloatText(
value=tstop, description="Stop time",
min=-1, max=1e6, step=1.0, **kwargs)
widgets_dict = {
'amplitude': amplitudes,
't0': start_times,
'tstop': stop_times
}
widgets_list = ([HTML(value="<b>Times (ms):</b>")] +
[start_times, stop_times] +
[HTML(value="<b>Amplitude (nA):</b>")] +
list(amplitudes.values()))
drive_box = VBox(widgets_list)
drive = dict(type='Tonic',
name=name,
amplitude=amplitudes,
t0=start_times,
tstop=stop_times,)
drive.update(widgets_dict)
return drive, drive_box
def add_drive_widget(drive_type, drive_boxes, drive_widgets, drives_out,
tstop_widget, location, layout,
prespecified_drive_name=None,
prespecified_drive_data=None,
prespecified_weights_ampa=None,
prespecified_weights_nmda=None,
prespecified_delays=None,
prespecified_n_drive_cells=None,
prespecified_cell_specific=None,
render=True,
expand_last_drive=True,
event_seed=14,):
"""Add a widget for a new drive."""
# Check only adds 1 tonic input widget
if drive_type == "Tonic" and not _is_valid_add_tonic_input(drive_widgets):
return
style = {'description_width': '125px'}
drives_out.clear_output()
if not prespecified_drive_data:
prespecified_drive_data = {}
prespecified_drive_data.update({"seedcore": max(event_seed, 2)})
with drives_out:
if not prespecified_drive_name:
name = drive_type + str(len(drive_boxes))
else:
name = prespecified_drive_name
if drive_type in ('Rhythmic', 'Bursty'):
drive, drive_box = _get_rhythmic_widget(
name,
tstop_widget,
layout,
style,
location,
data=prespecified_drive_data,
weights_ampa=prespecified_weights_ampa,
weights_nmda=prespecified_weights_nmda,
delays=prespecified_delays,
n_drive_cells=prespecified_n_drive_cells,
cell_specific=prespecified_cell_specific,
)
elif drive_type == 'Poisson':
drive, drive_box = _get_poisson_widget(
name,
tstop_widget,
layout,
style,
location,
data=prespecified_drive_data,
weights_ampa=prespecified_weights_ampa,
weights_nmda=prespecified_weights_nmda,
delays=prespecified_delays,
n_drive_cells=prespecified_n_drive_cells,
cell_specific=prespecified_cell_specific,
)
elif drive_type in ('Evoked', 'Gaussian'):
drive, drive_box = _get_evoked_widget(
name,
layout,
style,
location,
data=prespecified_drive_data,
weights_ampa=prespecified_weights_ampa,
weights_nmda=prespecified_weights_nmda,
delays=prespecified_delays,
n_drive_cells=prespecified_n_drive_cells,
cell_specific=prespecified_cell_specific,
)
elif drive_type == 'Tonic':
drive, drive_box = _get_tonic_widget(
name,
tstop_widget,
layout,
style,
data=prespecified_drive_data
)
if drive_type in [
'Evoked', 'Poisson', 'Rhythmic', 'Bursty', 'Gaussian', 'Tonic'
]:
drive_boxes.append(drive_box)
drive_widgets.append(drive)
if render:
accordion = Accordion(
children=drive_boxes,
selected_index=len(drive_boxes) -
1 if expand_last_drive else None,
)
for idx, drive in enumerate(drive_widgets):
tab_name = drive['name']
if drive['type'] != 'Tonic':
tab_name += f" ({drive['location']})"
accordion.set_title(idx, tab_name)
display(accordion)
def add_connectivity_tab(params, connectivity_out, connectivity_textfields,
cell_params_out, cell_pameters_vboxes,
cell_layer_radio_button, cell_type_radio_button,
layout):
"""Add all possible connectivity boxes to connectivity tab."""
net = dict_to_network(params)
# build network connectivity tab
add_network_connectivity_tab(net, connectivity_out,
connectivity_textfields)
# build cell parameters tab
add_cell_parameters_tab(cell_params_out, cell_pameters_vboxes,
cell_layer_radio_button, cell_type_radio_button,
layout)
return net
def add_network_connectivity_tab(net, connectivity_out,
connectivity_textfields):
cell_types = [ct for ct in net.cell_types.keys()]
receptors = ('ampa', 'nmda', 'gabaa', 'gabab')
locations = ('proximal', 'distal', 'soma')
# clear existing connectivity
connectivity_out.clear_output()
while len(connectivity_textfields) > 0:
connectivity_textfields.pop()
connectivity_names = list()
for src_gids in cell_types:
for target_gids in cell_types:
for location in locations:
# the connectivity list should be built on this level
receptor_related_conn = {}
for receptor in receptors:
conn_indices = pick_connection(net=net,
src_gids=src_gids,
target_gids=target_gids,
loc=location,
receptor=receptor)
if len(conn_indices) > 0:
assert len(conn_indices) == 1
conn_idx = conn_indices[0]
current_w = net.connectivity[
conn_idx]['nc_dict']['A_weight']
current_p = net.connectivity[
conn_idx]['probability']
# valid connection
receptor_related_conn[receptor] = {
"weight": current_w,
"probability": current_p,
# info used to identify connection
"receptor": receptor,
"location": location,
"src_gids": src_gids,
"target_gids": target_gids,
}
if len(receptor_related_conn) > 0:
connectivity_names.append(
f"{src_gids}→{target_gids} ({location})")
connectivity_textfields.append(
_get_connectivity_widgets(receptor_related_conn))
connectivity_boxes = [VBox(slider) for slider in connectivity_textfields]
cell_connectivity = Accordion(children=connectivity_boxes)
for idx, connectivity_name in enumerate(connectivity_names):
cell_connectivity.set_title(idx, connectivity_name)
with connectivity_out:
display(cell_connectivity)
return net
def add_cell_parameters_tab(cell_params_out, cell_pameters_vboxes,
cell_layer_radio_button, cell_type_radio_button,
layout):
L2_default_values = get_L2Pyr_params_default()
L5_default_values = get_L5Pyr_params_default()
cell_types = [("L2", L2_default_values), ("L5", L5_default_values)]
style = {'description_width': '255px'}
kwargs = dict(layout=layout, style=style)
for cell_type in cell_types:
layer_parameters = list()
for layer in cell_parameters_dict.keys():
if ('Biophysic' in layer or 'Geometry' in layer) and \
cell_type[0] not in layer:
continue
for parameter in cell_parameters_dict[layer]:
param_name, param_units, params_key = (parameter[0],
parameter[1],
parameter[2])
default_value = get_cell_param_default_value(
f'{cell_type[0]}Pyr_{params_key}', cell_type[1])
description = f"{param_name} ({param_units})"
min_value = -1000.0 if param_units not in 'ms' else 0
text_field = BoundedFloatText(value=default_value,
min=min_value,
max=1000.0,
step=0.1,
description=description,
disabled=False,
**kwargs)
text_field.layout.width = "350px"
layer_parameters.append(text_field)
cell_pameters_key = f'{cell_type[0]} Pyramidal_{layer}'
cell_pameters_vboxes[cell_pameters_key] = VBox(layer_parameters)
layer_parameters.clear()
# clear existing connectivity
cell_params_out.clear_output()
# Add cell parameters
_update_cell_params_vbox(cell_params_out,
cell_pameters_vboxes,
cell_type_radio_button.value,
cell_layer_radio_button.value)
def get_cell_param_default_value(cell_type_key, param_dict):
return param_dict[cell_type_key]
def add_drive_tab(params, log_out, drives_out, drive_widgets, drive_boxes,
tstop, layout):
net = dict_to_network(params)
drive_specs = net.external_drives
tonic_specs = net.external_biases
# clear before adding drives
drives_out.clear_output()
while len(drive_widgets) > 0:
drive_widgets.pop()
drive_boxes.pop()
drive_names = list(drive_specs.keys())
# Add tonic biases
if tonic_specs:
drive_names.extend(list(tonic_specs.keys()))
for idx, drive_name in enumerate(drive_names): # order matters
if 'tonic' in drive_name:
specs = dict(type='tonic', location=None)
kwargs = dict(prespecified_drive_data=tonic_specs[drive_name])
else:
specs = drive_specs[drive_name]
kwargs = dict(prespecified_drive_data=specs['dynamics'],
prespecified_weights_ampa=specs['weights_ampa'],
prespecified_weights_nmda=specs['weights_nmda'],
prespecified_delays=specs['synaptic_delays'],
prespecified_n_drive_cells=specs['n_drive_cells'],
prespecified_cell_specific=specs['cell_specific'],
event_seed=specs['event_seed'],
)
should_render = idx == (len(drive_names) - 1)
add_drive_widget(
specs['type'].capitalize(),
drive_boxes,
drive_widgets,
drives_out,
tstop,
specs['location'],
layout=layout,
prespecified_drive_name=drive_name,
render=should_render,
expand_last_drive=False,
**kwargs
)
def load_drive_and_connectivity(params, log_out, drives_out,
drive_widgets, drive_boxes, connectivity_out,
connectivity_textfields, cell_params_out,
cell_pameters_vboxes, cell_layer_radio_button,
cell_type_radio_button, tstop, layout):
"""Add drive and connectivity ipywidgets from params."""
with log_out:
# Add connectivity
add_connectivity_tab(params, connectivity_out, connectivity_textfields,
cell_params_out, cell_pameters_vboxes,
cell_layer_radio_button, cell_type_radio_button,
layout)
# Add drives
add_drive_tab(params, log_out, drives_out, drive_widgets, drive_boxes,
tstop, layout)
def on_upload_data_change(change, data, viz_manager, log_out):
if len(change['owner'].value) == 0:
return
data_dict = change['new'][0]
dict_name = data_dict['name'].rsplit('.', 1)
data_fname = dict_name[0]
file_extension = f".{dict_name[1]}"
if data_fname in data['simulation_data'].keys():
logger.error(f"Found existing data: {data_fname}.")
return
ext_content = data_dict['content']
ext_content = codecs.decode(ext_content, encoding="utf-8")
with log_out:
data['simulation_data'][data_fname] = {'net': None, 'dpls': [
_read_dipole_txt(io.StringIO(ext_content), file_extension)
]}
logger.info(f'External data {data_fname} loaded.')
_template_name = "[Blank] single figure"
viz_manager.reset_fig_config_tabs(template_name=_template_name)
viz_manager.add_figure()
fig_name = _idx2figname(viz_manager.data['fig_idx']['idx'] - 1)
ax_plots = [("ax0", "current dipole")]
# these lines plot the data per axis
for ax_name, plot_type in ax_plots:
viz_manager._simulate_edit_figure(
fig_name, ax_name, data_fname, plot_type, {}, "plot")
change['owner'].value = []
def on_upload_params_change(change, tstop, dt, log_out, drive_boxes,
drive_widgets, drives_out, connectivity_out,
connectivity_textfields, cell_params_out,
cell_pameters_vboxes, cell_layer_radio_button,
cell_type_radio_button, layout, load_type):
if len(change['owner'].value) == 0:
return
param_dict = change['new'][0]
file_contents = codecs.decode(param_dict['content'], encoding="utf-8")
with log_out:
params = json.loads(file_contents)
# update simulation settings and params
if 'tstop' in params.keys():
tstop.value = params['tstop']
if 'dt' in params.keys():
dt.value = params['dt']
# init network, add drives & connectivity
if load_type == 'connectivity':
add_connectivity_tab(params, connectivity_out,
connectivity_textfields, cell_params_out,
cell_pameters_vboxes, cell_layer_radio_button,
cell_type_radio_button, layout)
elif load_type == 'drives':
with log_out:
add_drive_tab(params, log_out, drives_out, drive_widgets,
drive_boxes, tstop, layout)
else:
raise ValueError
print(f"Loaded {load_type} from {param_dict['name']}")
# Resets file counter to 0
change['owner'].set_trait('value', ([]))
return params
def _drive_widget_to_dict(drive, name):
"""Creates a dict of input widget values
Input widgets for drive parameters are structured in a nested
dictionary. This function recreates the nested dictionary replacing
the input widget with its stored value.
Parameters
----------
drive : dict
The drive dictionary containing nested dictionaries for parameters with
multiple input widgets.
name : str
key of the nested dictionary
Returns : dict
-------
"""
return {
k: v.value
for k, v in drive[name].items()
}
def _init_network_from_widgets(params, dt, tstop, single_simulation_data,
drive_widgets, connectivity_textfields,
cell_params_vboxes,
add_drive=True):
"""Construct network and add drives."""
print("init network")
single_simulation_data['net'] = dict_to_network(params,
read_drives=False,
read_external_biases=False
)
# adjust connectivity according to the connectivity_tab
for connectivity_slider in connectivity_textfields:
for vbox_key in connectivity_slider:
conn_indices = pick_connection(
net=single_simulation_data['net'],
src_gids=vbox_key._belongsto['src_gids'],
target_gids=vbox_key._belongsto['target_gids'],
loc=vbox_key._belongsto['location'],
receptor=vbox_key._belongsto['receptor'])
if len(conn_indices) > 0:
assert len(conn_indices) == 1
conn_idx = conn_indices[0]
single_simulation_data['net'].connectivity[conn_idx][
'nc_dict']['A_weight'] = vbox_key.children[1].value
# Update cell params
update_functions = {
'L2 Geometry': _update_L2_geometry_cell_params,
'L5 Geometry': _update_L5_geometry_cell_params,
'Synapses': _update_synapse_cell_params,
'L2 Pyramidal_Biophysics': _update_L2_biophysics_cell_params,
'L5 Pyramidal_Biophysics': _update_L5_biophysics_cell_params
}
# Update cell params
for vbox_key, cell_param_list in cell_params_vboxes.items():
for key, update_function in update_functions.items():
if key in vbox_key:
cell_type = vbox_key.split()[0]
update_function(single_simulation_data['net'], cell_type,
cell_param_list.children)
break # update needed only once per vbox_key
for cell_type in single_simulation_data['net'].cell_types.keys():
single_simulation_data['net'].cell_types[cell_type]._update_end_pts()
single_simulation_data['net'].cell_types[
cell_type]._compute_section_mechs()
if add_drive is False:
return
# add drives to network
for drive in drive_widgets:
if drive['type'] in ('Tonic'):
weights_amplitudes = _drive_widget_to_dict(drive, 'amplitude')
single_simulation_data['net'].add_tonic_bias(
amplitude=weights_amplitudes,
t0=drive["t0"].value,
tstop=drive["tstop"].value)
else:
sync_inputs_kwargs = dict(
n_drive_cells=('n_cells' if drive['is_cell_specific'].value
else drive['n_drive_cells'].value),
cell_specific=drive['is_cell_specific'].value,
)
weights_ampa = _drive_widget_to_dict(drive, 'weights_ampa')
weights_nmda = _drive_widget_to_dict(drive, 'weights_nmda')
synaptic_delays = _drive_widget_to_dict(drive, 'delays')
print(
f"drive type is {drive['type']}, location={drive['location']}")
if drive['type'] == 'Poisson':
rate_constant = _drive_widget_to_dict(drive, 'rate_constant')
single_simulation_data['net'].add_poisson_drive(
name=drive['name'],
tstart=drive['tstart'].value,
tstop=drive['tstop'].value,
rate_constant=rate_constant,
location=drive['location'],
weights_ampa=weights_ampa,
weights_nmda=weights_nmda,
synaptic_delays=synaptic_delays,
space_constant=100.0,
event_seed=drive['seedcore'].value,
**sync_inputs_kwargs)
elif drive['type'] in ('Evoked', 'Gaussian'):
single_simulation_data['net'].add_evoked_drive(
name=drive['name'],
mu=drive['mu'].value,
sigma=drive['sigma'].value,
numspikes=drive['numspikes'].value,
location=drive['location'],
weights_ampa=weights_ampa,
weights_nmda=weights_nmda,
synaptic_delays=synaptic_delays,
space_constant=3.0,
event_seed=drive['seedcore'].value,
**sync_inputs_kwargs)
elif drive['type'] in ('Rhythmic', 'Bursty'):
single_simulation_data['net'].add_bursty_drive(
name=drive['name'],
tstart=drive['tstart'].value,
tstart_std=drive['tstart_std'].value,
tstop=drive['tstop'].value,
location=drive['location'],
burst_rate=drive['burst_rate'].value,
burst_std=drive['burst_std'].value,
numspikes=drive['numspikes'].value,
weights_ampa=weights_ampa,
weights_nmda=weights_nmda,
synaptic_delays=synaptic_delays,
event_seed=drive['seedcore'].value,
**sync_inputs_kwargs)
def run_button_clicked(widget_simulation_name, log_out, drive_widgets,
all_data, dt, tstop, ntrials, backend_selection,
mpi_cmd, n_jobs, params, simulation_status_bar,
simulation_status_contents, connectivity_textfields,
viz_manager, simulations_list_widget,
cell_pameters_widgets):
"""Run the simulation and plot outputs."""
simulation_data = all_data["simulation_data"]
with log_out:
# clear empty trash simulations
for _name in tuple(simulation_data.keys()):
if len(simulation_data[_name]['dpls']) == 0:
del simulation_data[_name]
_sim_name = widget_simulation_name.value
if simulation_data[_sim_name]['net'] is not None:
print("Simulation with the same name exists!")
simulation_status_bar.value = simulation_status_contents[
'failed']
return
_init_network_from_widgets(params, dt, tstop,
simulation_data[_sim_name], drive_widgets,
connectivity_textfields,
cell_pameters_widgets)
print("start simulation")
if backend_selection.value == "MPI":
backend = MPIBackend(
n_procs=multiprocessing.cpu_count() - 1, mpi_cmd=mpi_cmd.value)
else:
backend = JoblibBackend(n_jobs=n_jobs.value)
print(f"Using Joblib with {n_jobs.value} core(s).")
with backend:
simulation_status_bar.value = simulation_status_contents['running']
simulation_data[_sim_name]['dpls'] = simulate_dipole(
simulation_data[_sim_name]['net'],
tstop=tstop.value,
dt=dt.value,
n_trials=ntrials.value)
simulation_status_bar.value = simulation_status_contents[
'finished']
sim_names = [sim_name for sim_name in simulation_data
if simulation_data[sim_name]['net'] is not None]
simulations_list_widget.options = sim_names
simulations_list_widget.value = sim_names[0]
viz_manager.reset_fig_config_tabs()
viz_manager.add_figure()
fig_name = _idx2figname(viz_manager.data['fig_idx']['idx'] - 1)
ax_plots = [("ax0", "input histogram"), ("ax1", "current dipole")]
for ax_name, plot_type in ax_plots:
viz_manager._simulate_edit_figure(fig_name, ax_name, _sim_name,
plot_type, {}, "plot")
def _update_cell_params_vbox(cell_type_out, cell_parameters_list,
cell_type, cell_layer):
cell_parameters_key = f"{cell_type}_{cell_layer}"
if "Biophysics" or 'Geometry' in cell_layer:
cell_parameters_key += f" {cell_type.split(' ')[0]}"
if cell_parameters_key in cell_parameters_list:
cell_type_out.clear_output()
with cell_type_out:
display(cell_parameters_list[cell_parameters_key])
def _update_L2_geometry_cell_params(net, cell_param_key, param_list):
cell_params = param_list
cell_type = f'{cell_param_key.split("_")[0]}_pyramidal'
sections = net.cell_types[cell_type].sections
# Soma
sections['soma']._L = cell_params[0].value
sections['soma']._diam = cell_params[1].value
sections['soma']._cm = cell_params[2].value
sections['soma']._Ra = cell_params[3].value
# Dendrite common parameters
dendrite_cm = cell_params[4].value
dendrite_Ra = cell_params[5].value
dendrite_sections = [name for name in sections.keys()
if name != 'soma'
]
param_indices = [
(6, 7), (8, 9), (10, 11), (12, 13), (14, 15), (16, 17), (18, 19)]
# Dendrite
for section, indices in zip(dendrite_sections, param_indices):
sections[section]._L = cell_params[indices[0]].value
sections[section]._diam = cell_params[indices[1]].value
sections[section]._cm = dendrite_cm
sections[section]._Ra = dendrite_Ra
def _update_L5_geometry_cell_params(net, cell_param_key, param_list):
cell_params = param_list
cell_type = f'{cell_param_key.split("_")[0]}_pyramidal'
sections = net.cell_types[cell_type].sections
# Soma
sections['soma']._L = cell_params[0].value
sections['soma']._diam = cell_params[1].value
sections['soma']._cm = cell_params[2].value
sections['soma']._Ra = cell_params[3].value
# Dendrite common parameters
dendrite_cm = cell_params[4].value
dendrite_Ra = cell_params[5].value
dendrite_sections = [name for name in sections.keys()
if name != 'soma'
]
param_indices = [
(6, 7), (8, 9), (10, 11), (12, 13), (14, 15),
(16, 17), (18, 19), (20, 21)]
# Dentrite
for section, indices in zip(dendrite_sections, param_indices):
sections[section]._L = cell_params[indices[0]].value
sections[section]._diam = cell_params[indices[1]].value
sections[section]._cm = dendrite_cm
sections[section]._Ra = dendrite_Ra
def _update_synapse_cell_params(net, cell_param_key, param_list):
cell_params = param_list
cell_type = f'{cell_param_key.split("_")[0]}_pyramidal'
network_synapses = net.cell_types[cell_type].synapses
synapse_sections = ['ampa', 'nmda', 'gabaa', 'gabab']
param_indices = [
(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11)]
# Update Dendrite
for section, indices in zip(synapse_sections, param_indices):
network_synapses[section]['e'] = cell_params[indices[0]].value
network_synapses[section]['tau1'] = cell_params[indices[1]].value
network_synapses[section]['tau2'] = cell_params[indices[2]].value
def _update_L2_biophysics_cell_params(net, cell_param_key, param_list):
cell_type = f'{cell_param_key.split("_")[0]}_pyramidal'
sections = net.cell_types[cell_type].sections
# Soma
mechs_params = {
'hh2': {
'gkbar_hh2': param_list[0].value,
'gnabar_hh2': param_list[1].value,
'el_hh2': param_list[2].value,
'gl_hh2': param_list[3].value},
'km': {
'gbar_km': param_list[4].value}
}
sections['soma'].mechs.update(mechs_params)
# dendrites
mechs_params['hh2'] = {
'gkbar_hh2': param_list[5].value,
'gnabar_hh2': param_list[6].value,
'el_hh2': param_list[7].value,
'gl_hh2': param_list[8].value}
mechs_params['km'] = {
'gbar_km': param_list[9].value}
update_common_dendrite_sections(sections, mechs_params)
def _update_L5_biophysics_cell_params(net, cell_param_key, param_list):
cell_type = f'{cell_param_key.split("_")[0]}_pyramidal'
sections = net.cell_types[cell_type].sections
# Soma
mechs_params = {
'hh2':
{
'gkbar_hh2': param_list[0].value,
'gnabar_hh2': param_list[1].value,
'el_hh2': param_list[2].value,
'gl_hh2': param_list[3].value
},
'ca':
{
'gbar_ca': param_list[4].value
},
'cad':
{
'taur_cad': param_list[5].value
},
'kca':
{
'gbar_kca': param_list[6].value
},
'km':
{
'gbar_km': param_list[7].value
},
'cat':
{
'gbar_cat': param_list[8].value
},
'ar':
{
'gbar_ar': param_list[9].value
}
}
sections['soma'].mechs.update(mechs_params)
# dendrites
mechs_params['hh2'] = {
'gkbar_hh2': param_list[10].value,
'gnabar_hh2': param_list[11].value,
'el_hh2': param_list[12].value,
'gl_hh2': param_list[13].value}
mechs_params['ca'] = {'gbar_ca': param_list[14].value}
mechs_params['cad'] = {'taur_cad': param_list[15].value}
mechs_params['kca'] = {'gbar_kca': param_list[16].value}
mechs_params['km'] = {'gbar_km': param_list[17].value}
mechs_params['cat'] = {'gbar_cat': param_list[18].value}
mechs_params['ar'] = {'gbar_ar': partial(
_exp_g_at_dist, zero_val=param_list[19].value,
exp_term=3e-3, offset=0.0)}
update_common_dendrite_sections(sections, mechs_params)
def update_common_dendrite_sections(sections, mechs_params):
dendrite_sections = [
name for name in sections.keys() if name != 'soma'
]
for section in dendrite_sections:
sections[section].mechs.update(deepcopy(mechs_params))
def _serialize_simulation(log_out, sim_data, simulation_list_widget):
# Only download if there is at least one simulation
sim_name = simulation_list_widget.value
with log_out:
return serialize_simulation(sim_data, sim_name)
def serialize_simulation(simulations_data, simulation_name):
"""Serializes simulation data to CSV.
Creates a single CSV file or a ZIP file containing multiple CSVs,
depending on the number of trials in the simulation.
"""
simulation_data = simulations_data["simulation_data"]
csv_trials_output = []
# CSV file headers
headers = 'times,agg,L2,L5'
fmt = '%f, %f, %f, %f'
for dpl_trial in simulation_data[simulation_name]['dpls']:
# Combine all data columns at once
signals_matrix = np.column_stack((
dpl_trial.times,
dpl_trial.data['agg'],
dpl_trial.data['L2'],
dpl_trial.data['L5']
))
# Using StringIO to collect CSV data
with io.StringIO() as output:
np.savetxt(output, signals_matrix, delimiter=',',
header=headers, fmt=fmt)
csv_trials_output.append(output.getvalue())
if len(csv_trials_output) == 1:
# Return a single csv file
return csv_trials_output[0], ".csv"
else:
# Create zip file
return _create_zip(csv_trials_output, simulation_name), ".zip"
def _serialize_config(log_out, sim_data, simulation_list_widget):
# Only download if there is at least one simulation
sim_name = simulation_list_widget.value
with log_out:
return serialize_config(sim_data, sim_name)
def serialize_config(simulations_data, simulation_name):
"""Serializes Network configuration data to json."""
# Get network from data dictionary
net = simulations_data["simulation_data"][simulation_name]['net']
# Write to buffer
with io.StringIO() as output:
write_network_configuration(net, output)
return output.getvalue()
def _create_zip(csv_data_list, simulation_name):
# Zip all files and keep it in memory
with io.BytesIO() as zip_buffer:
with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zf:
for index, csv_data in enumerate(csv_data_list):
zf.writestr(f'{simulation_name}_{index + 1}.csv', csv_data)
zip_buffer.seek(0)
return zip_buffer.read()
def handle_backend_change(backend_type, backend_config, mpi_cmd, n_jobs):
"""Switch backends between MPI and Joblib."""
backend_config.clear_output()
with backend_config:
if backend_type == "MPI":
display(mpi_cmd)
elif backend_type == "Joblib":
display(n_jobs)
def _is_valid_add_tonic_input(drive_widgets):
for drive in drive_widgets:
if drive['type'] == 'Tonic':
return False
return True
def launch():
"""Launch voila with hnn_widget.ipynb.
You can pass voila commandline parameters as usual.
"""
from voila.app import main
notebook_path = Path(__file__).parent / 'hnn_widget.ipynb'
main([str(notebook_path.resolve()), *sys.argv[1:]])