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from datetime import datetime, timedelta | |
import plotly.graph_objs as go | |
import numpy as np | |
import dash_core_components as dcc | |
import dash_html_components as html | |
import dash | |
def display_eletrode_turns(all_turn_data): | |
""" | |
all_turn_data: list of data for each electrode, [(times,turns), ...] | |
""" | |
data = [ | |
{ | |
"x": np.r_[start, turn_times], | |
"y": np.r_[0, np.cumsum(turns)], | |
"line": {"shape": 'hv'}, | |
"mode": 'lines+markers', | |
"name": 'value', | |
"type": 'scatter', | |
"name": 'elec{}'.format(i) | |
} for i, (turn_times, turns) in enumerate(all_turn_data)] | |
layout = go.Layout( | |
showlegend=False, | |
yaxis = dict( | |
title='depth (mm)' | |
) | |
) | |
fig = go.Figure(data=data, layout=layout) | |
return fig | |
# generate fake data | |
start = datetime(1900, 1, 1) | |
nchans = 10 | |
max_turn = 300 | |
max_time_interval = 30 # days | |
n_turns = 5 | |
all_data = [] | |
for chan in range(nchans): | |
turn_times = start + np.cumsum([timedelta(days=np.random.randint(max_time_interval)) for _ in range(n_turns)]) | |
turns = np.random.randint(max_turn, size=turn_times.shape) | |
all_data.append( | |
(turn_times, | |
turns) | |
) | |
display_eletrode_turns(all_data) |
Author
bendichter
commented
Dec 3, 2020
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