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Update README.md

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Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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pywavelet/README.md
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@ -128,7 +128,10 @@ import numpy as np
import matplotlib.pyplot as plt
f_test: float = 50 # Hz
t_test: np.ndarray = np.arange(0, 1000) / 1000
number_of_test_samples: int = 1000
dt: float = 1.0 / 1000 # sec
t_test: np.ndarray = np.arange(0, number_of_test_samples) * dt
test_data: np.ndarray = np.sin(2 * np.pi * f_test * t_test)
plt.plot(t_test, test_data)
@ -137,3 +140,46 @@ plt.ylabel("time series")
```
![figure 4](image4.png)
```python
import numpy as np
import matplotlib.pyplot as plt
import pywt
f_test: float = 50 # Hz
number_of_test_samples: int = 1000
# The wavelet we want to use
mother = pywt.ContinuousWavelet("cmor1.5-1.0")
# Parameters for the wavelet transform
number_of_frequences: int = 25 # frequency bands
frequency_range_min: float = 15 # Hz
frequency_range_max: float = 200 # Hz
dt: float = 1.0 / 1000 # sec
t_test: np.ndarray = np.arange(0, number_of_test_samples) * dt
test_data: np.ndarray = np.sin(2 * np.pi * f_test * t_test)
# Calculate the wavelet scales we requested
s_spacing: np.ndarray = (1.0 / (number_of_frequences - 1)) * np.log2(
frequency_range_max / frequency_range_min
)
scale: np.ndarray = np.power(2, np.arange(0, number_of_frequences) * s_spacing)
frequency_axis_request: np.ndarray = frequency_range_min * np.flip(scale)
wave_scales: np.ndarray = 1.0 / (frequency_axis_request * dt)
complex_spectrum, frequency_axis = pywt.cwt(test_data, wave_scales, mother, dt)
plt.imshow(abs(complex_spectrum) ** 2, cmap="hot", aspect="auto")
plt.colorbar()
plt.yticks(np.arange(0, frequency_axis.shape[0]), frequency_axis)
plt.xticks(np.arange(0, t_test.shape[0]), t_test)
plt.xlabel("Time [sec]")
plt.ylabel("Frequency [Hz]")
plt.show()
```
![figure 5](image5.png)