spkit.create_signal_1d

spkit.create_signal_1d(n=100, seed=None, circular=False, bipolar=True, sg_winlen=11, sg_polyorder=1, max_dxdt=0.1, iterations=2, max_itr=10, **kwargs)

Generate 1D arbitary signal

Simulating arbitary signal

Parameters:

n: int, default=100

• number of sampels

seed: int, defualt=None,

• random seed, to re-generate same signal

circular: bool, deault=False,

• if True, then starting and ending value of the signal will be roughly same.

• if will signal starts from 0, it will end near to 0.

• useful for geometric operations.

bipolar: bool, default=True

• if True, signal will vary from -1 to +1

• else from 0 to 1

sg_winlen: int,deault=11

• window length, heigher the window size, smoother the signal will be

sg_polyorder: int, >0

• order of polynomial,

• higher the order, more curvy the signal will be

• smaller the order, more smoother and flat-like signal will be

max_dxdt: float, deafult=0.1

• maximum derivative in the signal,

• generated signal will be iteratively smoothen, untill, maximum derivative is <=`max_dxdt`

• or maximum number of iterations max_itr are achived, when (max_dxdt) is not None

max_itr: int, deafult=10

• maximum number of iterations to achive max_dxdt

• if None, then iterations are used, regardless of max_dxdt value.

iterations: int, deafault=2

• if max_itr is None, then iterations many iterations are used to smoothen the signal.

Returns:

x: 1d-array of n samples

See also

create_signal_2d

Notes

#TODO

Examples

#sp.create_signal_1d
import numpy as np
import matplotlib.pyplot as plt
import spkit as sp
seed=11
x1 = sp.create_signal_1d(n=100,sg_winlen=5,seed=seed)
x2 = sp.create_signal_1d(n=100,sg_winlen=11,seed=seed)
x3 = sp.create_signal_1d(n=100,sg_winlen=31,seed=seed)
plt.figure(figsize=(10,4))
plt.subplot(311)
plt.plot(x1,label='winlen=5')
plt.legend(loc='upper right')
plt.grid()
plt.subplot(312)
plt.plot(x2,label='winlen=11')
plt.legend(loc='upper right')
plt.grid()
plt.subplot(313)
plt.plot(x3,label='winlen=31')
plt.legend(loc='upper right')
plt.grid()
plt.subplots_adjust(hspace=0)
plt.show()

############################################
#sp.create_signal_1d
import numpy as np
import matplotlib.pyplot as plt
import spkit as sp
seed=1
x1 = sp.create_signal_1d(n=100,sg_winlen=11,sg_polyorder=1,seed=seed)
x2 = sp.create_signal_1d(n=100,sg_winlen=11,sg_polyorder=5,seed=seed)
x3 = sp.create_signal_1d(n=100,sg_winlen=11,sg_polyorder=7,seed=seed)
plt.figure(figsize=(10,4))
plt.subplot(311)
plt.plot(x1,label='order=1')
plt.legend(loc='upper right')
plt.grid()
plt.subplot(312)
plt.plot(x2,label='order=5')
plt.legend(loc='upper right')
plt.grid()
plt.subplot(313)
plt.plot(x3,label='order=7')
plt.legend(loc='upper right')
plt.grid()
plt.subplots_adjust(hspace=0)
plt.show()

Examples using spkit.create_signal_1d

Release Highlights for spkit 0.0.9.7

Release Highlights for spkit 0.0.9.7