pingu_98/cosmicpi-rpi_V1.5
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Added function to plot nearly arbitrary histograms of events

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Hendrik Borras 2017-10-20 14:23:02 +02:00
parent 36c2af0405
commit f3dda1b644
2 changed files with 83 additions and 35 deletions
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9
frontend/templates/dashboard.html
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@ -1,14 +1,9 @@
{% extends "cosmic_base.html" %}
{% block title %}Dashboard{% endblock %}
{% block head_additions %}
<link rel="stylesheet" href="{{ url_for('static',filename='css/c3.min.css') }}">
<script src="{{ url_for('static',filename='js/c3.min.js') }}"></script>
<script src="{{ url_for('static',filename='js/d3.v3.js') }}"></script>
{% endblock %}
{% block content %}
<h1>Index</h1>
<div id='line_chart_div'></div>
<script type="text/javascript">
c3.generate({{chart_json|safe}})
</script>
<img id="img" src="/histogram.png?start_time=-120&end_time=9000000000&bin_size_seconds=1"/>
{% endblock %}

109
frontend/web_ui.py
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@ -1,56 +1,109 @@
from flask import Flask, flash, redirect, render_template, request
from flask import Flask, flash, redirect, render_template, request, make_response
import matplotlib.pyplot as plt
import io
import base64
import c3pyo as c3
import sqlite3
import numpy as np
import matplotlib.dates as mdates
app = Flask(__name__)
sqlite_location = "../storage/sqlite_db"
def initDB():
conn = sqlite3.connect(sqlite_location)
cursor = conn.cursor()
cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='Events'")
if cursor.fetchone() == None:
cursor.execute('''CREATE TABLE Events
(UTCUnixTime INTEGER, SubSeconds REAL, TempreatureC REAL, Humidity REAL, AccelX REAL,
AccelY REAL, AccelZ REAL, MagX REAL, MagY REAL, MagZ REAL, Pressure REAL, Longitude REAL,
Latitude REAL, DetectorName TEXT, DetectorVersion TEXT);''')
conn.commit()
@app.route("/base/")
def base():
return render_template(
'cosmic_base.html', **locals())
def get_line_chart_json():
# data
x = [1, 2, 3, 4, 5, 6, 7]
y1 = [150, 450, 200, 100, 300, 0, 325]
y2 = [230, 220, 150, 400, 105, 50, 302]
# chart
chart = c3.LineChart()
chart.plot(x, y1, label='Series 1')
chart.plot(x, y2, label='Series 2')
chart.bind_to('line_chart_div')
return chart.json()
@app.route('/test/', methods=['GET', 'POST'])
def test():
chart_json = get_line_chart_json()
return render_template('c3pyo.html', chart_json=chart_json)
@app.route('/', methods=['GET', 'POST'])
@app.route('/dashboard/', methods=['GET', 'POST'])
def dashboard():
chart_json = get_line_chart_json()
return render_template('dashboard.html', chart_json=chart_json)
return render_template('dashboard.html', chart_json=0)
@app.route('/plot/')
@app.route('/histogram.png')
def build_plot():
# get user set parameters
start_time = request.args.get('start_time', type=int)
end_time = request.args.get('end_time', type=int)
bin_size_seconds = request.args.get('bin_size_seconds', type=int)
plot_title = ''
# get some data
data = []
conn = sqlite3.connect(sqlite_location)
cursor = conn.cursor()
# only get the last n seconds if the start time was negative
if start_time < 0:
plot_title += "Histogram of events over the last " + str(-start_time/60) + " minutes\nbin size: "+str(bin_size_seconds)+" [s]"
cursor.execute("SELECT * FROM Events ORDER BY UTCUnixTime DESC, SubSeconds DESC;")
start_time = cursor.fetchone()[0] + start_time
end_time = 9000000000
else:
plot_title += "Histogram of events over a set time\nbin size: " + str(bin_size_seconds) + " [s]"
cursor.execute("SELECT * FROM Events WHERE UTCUnixTime BETWEEN ? AND ? ORDER BY UTCUnixTime DESC, SubSeconds DESC;",
(start_time, end_time))
data = cursor.fetchall()
# massage data
if len(data) == 0:
plt.hist([])
plt.title("No data to display")
else:
event_time_list = [data[i][0] + data[i][1] for i in range(len(data))]
#event_time_list = [data[i][0] for i in range(len(data))]
bin_edges = range(int(event_time_list[len(event_time_list) - 1]), int(event_time_list[0]), bin_size_seconds)
x_axis_limits = (int(event_time_list[len(event_time_list) - 1]), int(event_time_list[0])+1)
# convert our unix timestamps to Matplotlib format
event_time_list = mdates.epoch2num(event_time_list)
bin_edges = mdates.epoch2num(bin_edges)
x_axis_limits = mdates.epoch2num(x_axis_limits)
# make the plot
plt.hist(event_time_list,bins=bin_edges)
plt.title(plot_title)
plt.xlabel("Time [UTC]")
plt.ylabel("Number of Events [1]")
plt.subplots_adjust(bottom=0.2)
plt.xticks(rotation=25)
plt.tick_params(which='both', width=2, direction="out", top=False, right=False)
plt.tick_params(which='major', length=5)
plt.tick_params(which='minor', length=3, color='r')
# do the date formatting
ax = plt.gca()
locator = mdates.AutoDateLocator(minticks=7)
locator.intervald[mdates.SECONDLY] = [1,10,30]
formatter = mdates.AutoDateFormatter(locator)
formatter.scaled[1 / (24. * 60.)] = '%H:%M:%S'
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(formatter)
ax.set_xlim(x_axis_limits)
# return the generated plot
img = io.BytesIO()
y = [1,2,3,4,5]
x = [0,2,1,3,4]
plt.plot(x,y)
plt.savefig(img, format='png')
img.seek(0)
plt.close()
response = make_response(img.getvalue())
response.headers['Content-Type'] = 'image/png'
return response
plot_url = base64.b64encode(img.getvalue()).decode()
return '<img src="data:image/png;base64,{}">'.format(plot_url)
if __name__ == '__main__':
initDB()
app.run()