Sequence filters
[1]:
# Import auxiliary libraries for demonstration
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
plt.rcParams[ "figure.figsize" ] = [ 5, 4 ]
plt.style.use( "default" )
plt.rcParams[ "figure.dpi" ] = 80
plt.rcParams[ "font.family" ] = "Times New Roman"
plt.rcParams[ "font.size" ] = '14'
Sequence peakValley filter
Function sequencePeakValleyFilter returns the peaks and valleys of a sequence.
Function help
[2]:
from ffpack.utils import sequencePeakValleyFilter
help( sequencePeakValleyFilter )
Help on function sequencePeakValleyFilter in module ffpack.utils.generalUtils:
sequencePeakValleyFilter(data, keepEnds=False)
Remove the intermediate value and only get the peaks and valleys of the data
The peak and valley refer the data points that are EXACTLY above and below
the neighbors, not equal.
Parameters
----------
data: 1darray
Sequence data to get peaks and valleys.
keepEnds: bool, optional
If two ends of the original data should be preserved.
Returns
-------
rst: 1darray
A list contains the peaks and valleys of the data.
Raises
------
ValueError
If the data dimension is not 1.
If the data length is less than 2 with keedEnds == False.
If the data length is less than 3 with keedEnds == True.
Examples
--------
>>> from ffpack.utils import sequencePeakValleyFilter
>>> data = [ -0.5, 1.0, -2.0, 3.0, -1.0, 4.5, -2.5, 3.5, -1.5, 1.0 ]
>>> rst = sequencePeakValleyFilter( data )
Example with default values
[3]:
gspvSequenceData = [ -0.5, 0.0, 1.0, -1.0, -2.0, -1.0, 1.5, 3.0, 2.5, -1.0, 0.5, 1.5, 4.5,
3.5, 1.0, -1.0, -2.5, -1.5, 3.0, 3.5, 1.5, 0.0, -1.5, 0.5, 1.0 ]
gspvResults = sequencePeakValleyFilter( gspvSequenceData, keepEnds=False )
[4]:
print( gspvResults )
[1.0, -2.0, 3.0, -1.0, 4.5, -2.5, 3.5, -1.5]
[5]:
fig, ( ax1, ax2 ) = plt.subplots( 1, 2, figsize=( 10, 4 ) )
ax1.plot( gspvSequenceData, 'o-' )
ax1.tick_params( axis='x', direction="in", length=5 )
ax1.tick_params( axis='y', direction="in", length=5 )
ax1.set_ylabel( "Load units" )
ax1.set_xlabel( "Data points" )
ax1.set_title( "Sequence data" )
ax2.plot( gspvResults, 'o-' )
ax2.tick_params(axis='x', direction="in", length=5)
ax2.tick_params(axis='y', direction="in", length=5)
ax2.set_ylabel( "Load units" )
ax2.set_xlabel( "Data points" )
ax2.set_title( "Sequence after peakValley filter" )
plt.tight_layout()
plt.show()
Example with keep end points
[6]:
from ffpack.utils import sequencePeakValleyFilter
[7]:
gspvSequenceData = [ -0.5, 0.0, 1.0, -1.0, -2.0, -1.0, 1.5, 3.0, 2.5, -1.0, 0.5, 1.5, 4.5,
3.5, 1.0, -1.0, -2.5, -1.5, 3.0, 3.5, 1.5, 0.0, -1.5, 0.5, 1.0 ]
gspvResults = sequencePeakValleyFilter( gspvSequenceData, keepEnds=True )
[8]:
print( gspvResults )
[-0.5, 1.0, -2.0, 3.0, -1.0, 4.5, -2.5, 3.5, -1.5, 1.0]
[9]:
fig, ( ax1, ax2 ) = plt.subplots( 1, 2, figsize=( 10, 4 ) )
ax1.plot( gspvSequenceData, 'o-' )
ax1.tick_params( axis='x', direction="in", length=5 )
ax1.tick_params( axis='y', direction="in", length=5 )
ax1.set_ylabel( "Load units" )
ax1.set_xlabel( "Data points" )
ax1.set_title( "Sequence data" )
ax2.plot( gspvResults, 'o-' )
ax2.tick_params(axis='x', direction="in", length=5)
ax2.tick_params(axis='y', direction="in", length=5)
ax2.set_ylabel( "Load units" )
ax2.set_xlabel( "Data points" )
ax2.set_title( "Sequence after peakValley filter" )
plt.tight_layout()
plt.show()
Sequence hysteresis filter
Function sequenceHysteresisFilter returns the sequence after hysteresis filtering.
Function help
[10]:
from ffpack.utils import sequenceHysteresisFilter
help( sequenceHysteresisFilter )
Help on function sequenceHysteresisFilter in module ffpack.utils.generalUtils:
sequenceHysteresisFilter(data, gateSize)
Filter data within the gateSize.
Any cycle that has an amplitude smaller than the gate is removed from the data.
This is done by scan the data, i.e., point i, to check if the next points,
i.e., i + 1, i + 2, ... are within the gate from point i.
Parameters
----------
data: 1darray
Sequence data to get peaks and valleys.
gateSize: scalar
Gate size to filter the data.
Returns
-------
rst: 1darray
A list contains the filtered data.
Raises
------
ValueError
If the data dimension is not 1.
If the data length is less than 2.
If gateSize is not a scalar or not positive.
Examples
--------
>>> from ffpack.utils import sequenceHysteresisFilter
>>> data = [ 2, 5, 3, 6, 2, 4, 1, 6, 1, 3, 1, 5, 3, 6, 3, 6, 4, 5, 2 ]
>>> gateSize = 3.0
>>> rst = sequenceHysteresisFilter( data, gateSize )
Example with default values
[11]:
hfSequenceData = [ 2, 5, 3, 6, 2, 4, 1, 6, 1, 3, 1, 5, 3, 6, 3, 6, 4, 5, 4 ]
[12]:
gateSize = 3
hfResults = sequenceHysteresisFilter( hfSequenceData, gateSize )
[13]:
print( hfResults )
[2.0, 5.0, 6.0, 2.0, 1.0, 6.0, 1.0, 5.0, 6.0, 3.0, 6.0, 4.0]
[14]:
fig, ( ax1, ax2 ) = plt.subplots( 1, 2, figsize=( 10, 4 ) )
ax1.plot( hfSequenceData, 'o-' )
ax1.tick_params( axis='x', direction="in", length=5 )
ax1.tick_params( axis='y', direction="in", length=5 )
ax1.set_ylabel( "Load units" )
ax1.set_xlabel( "Data points" )
ax1.set_title( "Sequence data" )
ax2.plot( hfResults, 'o-' )
ax2.tick_params(axis='x', direction="in", length=5)
ax2.tick_params(axis='y', direction="in", length=5)
ax2.set_ylabel( "Load units" )
ax2.set_xlabel( "Data points" )
ax2.set_title( "Sequence after hysteresis filter" )
plt.tight_layout()
plt.show()
[15]:
hfSequenceData = [ -0.5, 0.5, 0.2, 0.8, 1.0, -1.0, -2.0, -1.0, 0.8, 0.0, 1.5, 3.0, 2.5,
2.0, 2.5, 1.5, -1.0, 0.5, 1.2, 0.8, 1.5, 2.5, 2.0, 3.5, 3.0, 4.5, 3.5,
4.0, 4.2, 3.3, 2.8, 3.0, 2.5, 3.0, 2.0, 1.0, 0.0, 0.5, -1.0, -2.0,
-1.5, -2.0, -2.5, -1.5, -2.0, 0.0, 1.0, 1.2, 0.5, 2.0, 3.0, 4.0, 3.5,
4.5, 3.5, 2.5, 3.5, 2.5, 3.0, 2.0, 2.5, 1.5, 0.5, 1.0, 0.5, 0.0, -1.0,
-0.5 -1.5, -0.5, -1.0, 0.0, -0.5, 1.0 ]
[16]:
gateSize = 1.5
hfResults = sequenceHysteresisFilter( hfSequenceData, gateSize )
[17]:
print( hfResults )
[-0.5, 1.0, -1.0, 0.8, 1.5, 3.0, 1.5, -1.0, 0.5, 2.5, 3.5, 4.5, 2.8, 2.5, 2.0, 0.0, -1.0, -2.5, 0.0, 2.0, 4.0, 4.5, 2.5, 2.0, 1.5, 0.0, -2.0, -0.5, 0.0, 1.0]
[18]:
fig, ( ax1, ax2 ) = plt.subplots( 1, 2, figsize=( 10, 4 ) )
ax1.plot( hfSequenceData, 'o-' )
ax1.tick_params( axis='x', direction="in", length=5 )
ax1.tick_params( axis='y', direction="in", length=5 )
ax1.set_ylabel( "Load units" )
ax1.set_xlabel( "Data points" )
ax1.set_title( "Sequence data" )
ax2.plot( hfResults, 'o-' )
ax2.tick_params(axis='x', direction="in", length=5)
ax2.tick_params(axis='y', direction="in", length=5)
ax2.set_ylabel( "Load units" )
ax2.set_xlabel( "Data points" )
ax2.set_title( "Sequence after hysteresis filter" )
plt.tight_layout()
plt.show()
