Posted: 7/4/2020
I was wondering if anyone knows how to plot a sine wave with let's say amplitude of 0.1 as a start and then continuing on as usual. Until at one point, the amplitude change to 1.0. Like a sudden surge of change in amplitude. It's like I was an oscillatory system that was stable, and becoming unstable at one point. The plot that I am expecting is as follow:
Regards, Anis
Updated progress: 18/4/2020
import numpy as np
import matplotlib.pyplot as plotter
from scipy import signal
# How many time points are needed i,e., Sampling Frequency
samplingFrequency = 1500
# At what intervals time points are sampled
samplingInterval = 1 / samplingFrequency;
# Begin time period of the signals
beginTime = 0;
# End time period of the signals
endTime = 0.3;
# Frequency of the signals
signal1Frequency = 50;
#Time points
time = np.arange(beginTime, endTime, samplingInterval);
phase = 180
pi = np.pi
phi = phase*pi/180
# Create two waves- sine and square
amplitude1 = np.sin(2*np.pi*signal1Frequency*time)
amplitude2 = signal.square(2 * np.pi * 50 * time+ phi )
figure, axis = plotter.subplots(1, 1)
plotter.subplots_adjust(hspace=1)
if (time >0.2):
amplitude = 3*amplitude1
plotter.plot(time, amplitude)
plotter.title('test')
plotter.show()
Above is the code that I am currently working on. It keeps on popping an error to due to ambiguity. Requesting me to use a.all() and a.any() function to solve it. When I did do so, I am not getting the surge point that I am expecting. So any ideas on it? I am using time as x axis instead of indexing. And I am using numoy sine instead of math library. This is because when I tried FFT for code proposed below, I am not getting a 50 Hz, it was more of 30 or 10 Hz, and that is understandable given that the frequency was not set and it depends on the periodic cycle created by the sinusoid itself.
Regards, Anis
I have converted the code to period time:
import matplotlib.pyplot as plt
import math
# ------------------------------------------------------------------------
# uses the list amplitude_changes to get the amplitude for time t
def get_amplitude(t):
for amplitude_change in amplitude_changes:
if t >= amplitude_change['t']:
amplitude = amplitude_change['amplitude']
return amplitude
# --------------------------------------------------------------------------
def y_func(time, period_time, amplitude):
return amplitude * math.sin((time / period_time) * 2 * math.pi)
# --------------------------------------------------------------------------
t_values = []
amplitude_values = []
signal1Frequency = 50
period_time = 1 / signal1Frequency
sampling_frequency = 1500
delta_t = 1 / sampling_frequency
amplitude_changes = [
{'t': 0, 'amplitude': 1},
{'t': period_time * 0.9, 'amplitude': 1.5},
{'t': period_time * 0.95, 'amplitude': 1},
{'t': period_time * 1.2, 'amplitude': 0.8},
{'t': period_time * 1.25, 'amplitude': 1},
]
max_t = period_time * 3 # plot 3 periods
t = 0
while t <= max_t:
t_values.append(t)
amplitude = get_amplitude(t)
amplitude_values.append(y_func(t, period_time, amplitude))
t += delta_t
plt.plot(t_values, amplitude_values)
plt.title(f'f = {signal1Frequency} Hz (T = {period_time}) - Sampling frequency = {sampling_frequency} Hz')
plt.show()
Result