Use of normalisation function

In this example we normalise a spectrum to different values: area, maximum, or min-max.

Signal creation

Below we create a fake Gaussian signal for the example.

# we load the necessary libraries
%matplotlib inline
import numpy as np
import scipy
import rampy

# the following code is for the rendering of plotly graphs in Rampy docs, you don't need it
# Set renderer for Jupyter notebooks
import plotly.io as pio
pio.renderers.default = 'notebook'

# and we create the signal
nb_points  =100
x = np.sort(np.random.uniform(0,100,nb_points)) # increasing point
y = 120.0*scipy.stats.norm.pdf(x,loc=50,scale=5)

fig = rampy.plot_spectrum(x, y, title = "our spectrum", xaxis_title="X", yaxis_title="Y")
fig.show()

We can consider that the area of the Gaussian peak should be equal to 1, as it is the value of the intergral of a Gaussian distribution.

To normalise the spectra, we can do:

y_norm_ = rampy.normalise(y, x=x, method="area")

fig = rampy.plot_spectrum(x, y_norm_, title = "Area normalisation", xaxis_title="X", yaxis_title="Y")
fig.show()

We could also just want the signal to be comprised between 0 and 1, so we normalise to the maximum:

y_norm_ = rampy.normalise(y,method="intensity")

fig = rampy.plot_spectrum(x, y_norm_, title = "Intensity normalisation", xaxis_title="X", yaxis_title="Y")
fig.show()

Now, if our signal intensity was shifted from 0 by a constant, the “intensity” method will not work well. For instance, I can add 0.1 to y and plot it.

y2 = y + 1

fig = rampy.plot_spectrum(x, y2, title = "Shifted signal", xaxis_title="X", yaxis_title="Y")
fig.show()

In this case, the “intensity” method will not work well:

y_norm_ = rampy.normalise(y2,method="intensity")

fig = rampy.plot_spectrum(x, y_norm_, title = "Shifted signal normalised", xaxis_title="X", yaxis_title="Y")
fig.show()

The signal remains shifted from 0. For safety, we can do a min-max normalisation, which will put the minimum to 0 and maximum to 1:

y_norm_ = rampy.normalise(y2,method="minmax")

fig = rampy.plot_spectrum(x, y_norm_, title = "Min-max normalisation", xaxis_title="X", yaxis_title="Y")
fig.show()