Interactive data normalization and continuum finder¶
The ContinuumInteractive class provides a GUI, which helps to interactively normalize data, e.g., for continuum normalization.
Example of usage¶
from PyAstronomy import pyaGui as pg
import numpy as np
import matplotlib.pylab as plt
# Create some artificial data/spectrum
x = np.arange(1000)
y = np.random.random(1000) + 1000.0 + np.sin(x/80.)
y += np.random.random(len(x))
# Construct an instance of the interactive normalization GUI
cf = pg.ContinuumInteractive(x, y)
# The 'plot' command can be used to draw something on the canvas
# on which normalization points are selected. Uncomment the following
# line to see an example.
#
# cf.plot([4,400,600], [1001,1000,999], 'k--')
# The 'plotNorm' command can be used to draw something on the
# canvas showing the normalized spectrum (if display is enabled).
# Uncomment the following line to see an example.
#
# cf.plotNorm([0.,1000.], [1.001,0.999], 'g:')
# Opens the GUI and starts the interactive session.
c = cf.findContinuum()
# The outcome is a dictionary with the following keys:
#
# - points: A list of two-float tuples holding the
# x,y location of the selected points.
# - continuum : Array holding the continuum estimate
# at the given x-values.
# - splineKind : A string specifying the selected
# spline option.
# - normalizedData : An array holding the normalized
# data.
plt.title("Normalized data")
plt.plot(x, c["normalizedData"], 'b.--')
plt.show()
