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signac.rc | ||
signac_project_document.json | ||
workspace/ |
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# Plotly Plots Example | ||
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To run this example, call `python init.py` and then `python dashboard.py run`. |
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#!/usr/bin/env python3 | ||
# Copyright (c) 2019 The Regents of the University of Michigan | ||
# All rights reserved. | ||
# This software is licensed under the BSD 3-Clause License. | ||
from scipy.signal import coherence | ||
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from signac_dashboard import Dashboard | ||
from signac_dashboard.modules import PlotViewer, StatepointList, TextDisplay | ||
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class PlotDashboard(Dashboard): | ||
def job_sorter(self, job): | ||
return job.sp.get("coherence_time", -1) | ||
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def job_title(self, job): | ||
return f"Coherence time: {job.sp.coherence_time}" | ||
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def correlation_text(job): | ||
return "Correlation coefficient: {:.5f}".format(job.doc["correlation"]) | ||
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def plotly_args(job): | ||
# Visualization adapted from: | ||
# https://matplotlib.org/gallery/lines_bars_and_markers/cohere.html | ||
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# It's necessary to cast to list because the list elements of the job | ||
# document are BufferedJSONAttrList, which is not serializable | ||
signals_traces = [ | ||
{ | ||
"x": list(job.doc["t"]), | ||
"y": list(job.doc["s1"]), | ||
"name": "s1", | ||
}, | ||
{ | ||
"x": list(job.doc["t"]), | ||
"y": list(job.doc["s2"]), | ||
"name": "s2", | ||
}, | ||
] | ||
signals_layout = { | ||
"xaxis": { | ||
"title": "time", | ||
"range": [0, 2], | ||
}, | ||
"height": 200, | ||
"margin": dict(t=30, b=40, l=40, r=0), | ||
} | ||
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dt = job.doc["t"][1] - job.doc["t"][0] | ||
coherence_x, coherence_y = coherence( | ||
job.doc["s1"], job.doc["s2"], nfft=256, fs=1.0 / dt | ||
) | ||
coherence_traces = [ | ||
{ | ||
"x": coherence_x.tolist(), | ||
"y": coherence_y.tolist(), | ||
} | ||
] | ||
coherence_layout = { | ||
"title": f"Coherence time = {job.sp.coherence_time}", | ||
"xaxis": {"title": "frequency"}, | ||
"yaxis": {"title": "coherence", "range": [0, 1]}, | ||
"height": 200, | ||
"margin": dict(t=30, b=40, l=40, r=0), | ||
} | ||
return [ | ||
("Signals", signals_traces, signals_layout), | ||
("Coherence", coherence_traces, coherence_layout), | ||
] | ||
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if __name__ == "__main__": | ||
modules = [] | ||
modules.append(StatepointList()) | ||
modules.append(PlotViewer(plotly_args=plotly_args)) | ||
modules.append(TextDisplay(name="Correlation", message=correlation_text)) | ||
PlotDashboard(modules=modules).main() |
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#!/usr/bin/env python3 | ||
# Copyright (c) 2019 The Regents of the University of Michigan | ||
# All rights reserved. | ||
# This software is licensed under the BSD 3-Clause License. | ||
import numpy as np | ||
import signac | ||
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project = signac.init_project("plots") | ||
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def plot_coherence(job): | ||
# Data generation adapted from: | ||
# https://matplotlib.org/gallery/lines_bars_and_markers/cohere.html | ||
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print(f"Generating signals for coherence time {job.sp.coherence_time}, job {job}") | ||
# Fixing random state for reproducibility | ||
np.random.seed(job.sp.seed) | ||
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dt = 0.01 | ||
t = np.arange(0, 30, dt) | ||
nse1 = np.random.randn(len(t)) # white noise 1 | ||
nse2 = np.random.randn(len(t)) # white noise 2 | ||
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# Two signals with a coherent part and a random part | ||
s1 = np.sin(2 * np.pi * job.sp.coherence_time * t) + nse1 | ||
s2 = np.sin(2 * np.pi * job.sp.coherence_time * t) + nse2 | ||
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# Save the signal data | ||
job.doc["t"] = t.tolist() | ||
job.doc["s1"] = s1.tolist() | ||
job.doc["s2"] = s2.tolist() | ||
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# Save correlation coefficient | ||
job.doc["correlation"] = np.corrcoef(s1, s2)[0, 1] | ||
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for i in range(30): | ||
job = project.open_job({"coherence_time": i, "seed": 42}) | ||
job.init() | ||
plot_coherence(job) |