I am a manufacturing engineer, very new to Python and Matplotlib. Currently, I am trying to plot a scatter time graph, where for every single record, I have the data (read from a sensor) and upper and lower limits for that data that will stop the tool if data is not between them.
So for a simple set of data like this:
time = [1, 2, 3, 7, 8, 9, 10]*
data = [5, 6, 5, 5, 6, 7, 8]
lower_limit = [4, 4, 5, 5, 5, 5, 5]
upper_limit = [6, 6, 6, 7, 7, 7, 7]
The desired graph would look like this:
A few rules that I am trying to stick to:
So, with all of that in mind, and thousands of records per day, a regular graph, for a 24hr time span, should look like the following: (notice the gap due to possible lack of records in a time span, as well as vertical green lines, for the limits.)
Thanks for your time and help!
This is a version using numpy
s masking and matplotlib
s errorbar
import matplotlib.pyplot as plt
import numpy as np
time = np.array( [0, 1, 2, 3, 7, 8, 9, 10] )
data = np.array([2, 5, 6, 5, 5, 6, 7, 8] )
lower = np.array([4, 4, 4, 5, 5, 5, 5, 5] )
upper = np.array([6, 6, 6, 6, 7, 7, 7, 7] )
nn = len( lower )
delta = upper - lower
### creating masks
inside = ( ( upper - data ) >= 0 ) & ( ( data - lower ) >= 0 )
outside = np.logical_not( inside )
fig = plt.figure()
ax = fig.add_subplot( 1, 1, 1 )
ax.errorbar( time, lower, yerr=( nn*[0], delta), ls='', ecolor="#00C023" )
ax.scatter( time[ inside ], data[ inside ], c='k' )
ax.scatter( time[ outside ], data[ outside ], c='r' )
plt.show()