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"# Use of normalisation function\n",
"\n",
"In this example we normalise a spectrum to different values: area, maximum, or min-max.\n",
"\n",
"## Signal creation\n",
"\n",
"Below we create a fake Gaussian signal for the example."
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"source": [
"# we load the necessary libraries\n",
"%matplotlib inline\n",
"import numpy as np\n",
"import scipy\n",
"import rampy\n",
"\n",
"# the following code is for the rendering of plotly graphs in Rampy docs, you don't need it\n",
"# Set renderer for Jupyter notebooks\n",
"import plotly.io as pio\n",
"pio.renderers.default = 'notebook'\n",
"\n",
"# and we create the signal\n",
"nb_points =100\n",
"x = np.sort(np.random.uniform(0,100,nb_points)) # increasing point\n",
"y = 120.0*scipy.stats.norm.pdf(x,loc=50,scale=5)\n",
"\n",
"fig = rampy.plot_spectrum(x, y, title = \"our spectrum\", xaxis_title=\"X\", yaxis_title=\"Y\")\n",
"fig.show()"
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"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.\n",
"\n",
"To normalise the spectra, we can do:"
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