Creating a graph as shown in the attached picture

Question

Does anyone know what is the name of this graph ? I do not have any dataset and I do not know anything how it was created at the first place.

1- Can any please tell how this kind of graph can be created in python ? I do not have any dataset so It would be great if you can tell me what kind of dataset we need for this graph.

2- To me it seems like a time series linechart so can anyone provide a code to generate a similar graph as shown in the attached picture.

I have tried to do it with some timeseries dataset samples but the results were not closed to the graph shown in the picture.

Answer 1

Try something like this:

    import numpy as np
    import matplotlib.pyplot as plt

    def f(x):
        return np.sin(20*x) * np.sin(x) + x/3

    x = np.linspace(-2*np.pi, 2*np.pi, 1000)

    y = f(x)

    plt.figure(figsize=(8, 6))
    plt.plot(x, y, label='y = sin(20x) * sin(x) + x/3', color='b')
    plt.xlabel('x')
    plt.ylabel('y')
    plt.grid(True)
    plt.show()

The output is:

The function could be something like: f(x) = sin(A*x)*sin(B*x) + x*C, where A, B and C are some constants.

As for the name of this graph, you can probably associate it with the term Amplitude modulation, where a sine wave is modulated by another sine wave.

Answer 2

this seems like a sine function that is modulated by another sine function (half sine in this example) and then added a linear offset. You can easily generate this as:

import numpy as np
import matplotlib.pyplot as plt

rads = np.arange(360)*np.pi/180
base_frequency = 10 #angular frequency
base_sine_curve = np.sin(base_frequency*rads)
modulation_curve = np.sin(rads/2) # half a sine wave
linear_offset = np.arange(360)/180 #increase y value by 0.5 after 360 degrees
xs = np.arange(360)
fig, (ax1,ax2,ax3) = plt.subplots(1,3,figsize=(16,5))
ax1.plot(xs,base_sine_curve,label='base frequency')
ax1.legend(loc='upper center', bbox_to_anchor=(0.5, 1.1))
ax2.plot(xs,modulation_curve,label='modulation frequency')
ax2.plot(xs,base_sine_curve*modulation_curve)
ax2.legend(loc='upper center', bbox_to_anchor=(0.5, 1.1))
ax3.plot(xs,linear_offset,label='linear offset')
ax3.plot(xs,(base_sine_curve*modulation_curve)+linear_offset)
ax3.legend(loc='upper center', bbox_to_anchor=(0.5, 1.1))
plt.show()

edit: here is the output of the program: You can obviously repeat this to get repeated modulated sine waves, but I think the example should do what you want it to