Mathematical Functions

Negation

You can negate each signal sample with the '-' operator or by calling the method neg().

A new Trace instance labeled with the performed transformation 'neg' is returned.

>>> # negate samples with operator
>>> -Trace('Signal', [-1, 0, 1])
Trace(label='Signal:neg', samples=[1, 0, -1])
>>> # negate samples with method call
>>> Trace('Signal', [-1, 0, 1]).neg()
Trace(label='Signal:neg', samples=[1, 0, -1])

(Source code, html)

Absolute

You can compute the absolute value for each signal sample with the built-in function abs() or by calling the method abs().

A new Trace instance labeled with the performed transformation 'abs' is returned.

>>> abs(Trace('Signal', [-1, 0, 1]))
Trace(label='Signal:abs', samples=[1, 0, 1])
>>> Trace('Signal', [-1, 0, 1]).abs()
Trace(label='Signal:abs', samples=[1, 0, 1])

(Source code, html)

Rounding

You can round each signal sample with the built-in function round() or by calling the method round().

A new Trace instance labeled with the performed transformation 'round' is returned.

>>> round(Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]))
Trace(label='Signal:round', samples=[-2, 0, 0, 0, 2])
>>> Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]).round()
Trace(label='Signal:round', samples=[-2, 0, 0, 0, 2])

(Source code, html)

Truncation

You can truncate each signal sample with the function trunc() from the math module or by calling the method trunc().

A new Trace instance labeled with the performed transformation 'trunc' is returned.

>>> import math
>>> math.trunc(Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]))
Trace(label='Signal:trunc', samples=[-1, 0, 0, 0, 1])
>>> Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]).trunc()
Trace(label='Signal:trunc', samples=[-1, 0, 0, 0, 1])

(Source code, html)

Round to the Floor

You can round each signal sample to its floor integer with the function floor() from the math module or by calling the method floor().

A new Trace instance labeled with the performed transformation 'floor' is returned.

>>> import math
>>> math.floor(Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]))
Trace(label='Signal:floor', samples=[-2, -1, 0, 0, 1])
>>> Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]).floor()
Trace(label='Signal:floor', samples=[-2, -1, 0, 0, 1])

(Source code, html)

Round to the Ceil

You can round each signal sample to its ceil integer with the function ceil() from the math module or by calling the method ceil().

A new Trace instance labeled with the performed transformation 'ceil' is returned.

>>> import math
>>> math.ceil(Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]))
Trace(label='Signal:ceil', samples=[-1, 0, 0, 1, 2])
>>> Trace('Signal', [-1.5, -0.5, 0, 0.5, 1.5]).ceil()
Trace(label='Signal:ceil', samples=[-1, 0, 0, 1, 2])

(Source code, html)

Signum

You can compute the signum value for each signal sample by calling the method sign().

A new Trace instance labeled with the performed transformation 'sign' is returned.

>>> Trace('Signal', [-1.5, -0.5, 0 , 0.5, 1.5]).sign()
Trace(label='Signal:sign', samples=[-1.0, -1.0, 0, 1.0, 1.0])

(Source code, html)

Zeros

You can check each signal sample is zero or not by calling the method zero().

A new Trace instance labeled with the performed transformation 'zero' is returned.

>>> Trace('Signal', [-0.5, -0.0, 0, +0.0, 0.5]).zero()
Trace(label='Signal:zero', samples=[0, 1, 1, 1, 0])

(Source code, html)

Positives

You can check each signal sample is positive or not by calling the method positive().

A new Trace instance labeled with the performed transformation 'positive' is returned.

>>> Trace('Signal', [-0.5, -0.0, 0, +0.0, 0.5]).positive()
Trace(label='Signal:positive', samples=[0, 0, 0, 0, 1])

(Source code, html)

Negatives

You can check each signal sample is negative or not by calling the method negative().

A new Trace instance labeled with the performed transformation 'negative' is returned.

>>> Trace('Signal', [-0.5, -0.0, 0, +0.0, 0.5]).negative()
Trace(label='Signal:negative', samples=[1, 0, 0, 0, 0])

(Source code, html)

Min

You can get the minimum of each signal sample and the corresponding element in other Trace’s or Iterables, or an int or float numbers by calling the method min().

A new Trace instance labeled with the performed transformation 'min' is returned.

>>> # minimum of samples
>>> Trace('Signal1', [1, -2, 3]).min(Trace('Signal2', [-1, 2, -3]))
Trace(label='Signal1:min', samples=[-1, -2, -3])

>>> # minimum of samples and iterables
>>> Trace('Signal', [1, -2, 3]).min([-1, 2, -3])
Trace(label='Signal:min', samples=[-1, -2, -3])

>>> # minimum of samples and numbers
>>> Trace('Signal', [1, 2, 3]).min(2)
Trace(label='Signal:min', samples=[1, 2, 2])

Note

An iterable should have at least the same length as the signal samples, otherwise only a subset of the signal samples is returned!

(Source code, html)

Max

You can get the maximum of each signal sample and the corresponding element in other Trace’s or Iterables, or an int or float numbers by calling the method max().

A new Trace instance labeled with the performed transformation 'max' is returned.

>>> # maximum of samples
>>> Trace('Signal1', [1, -2, 3]).max(Trace('Signal2', [-1, 2, -3]))
Trace(label='Signal1:max', samples=[1, 2, 3])

>>> # maximum of samples and iterables
>>> Trace('Signal', [1, -2, 3]).max([-1, 2, -3])
Trace(label='Signal:max', samples=[1, 2, 3])

>>> # maximum of samples and numbers
>>> Trace('Signal', [1, 2, 3]).max(2)
Trace(label='Signal:max', samples=[2, 2, 3])

Note

An iterable should have at least the same length as the signal samples, otherwise only a subset of the signal samples is returned!

(Source code, html)

Average

You can get the average of each signal sample and the corresponding element in other Trace’s or Iterables, or an int or float numbers by calling the method average().

A new Trace instance labeled with the performed transformation 'avg' is returned.

>>> # average of samples
>>> Trace('Signal1', [1, -2, 3]).average(Trace('Signal2', [-1, 2, -3]))
Trace(label='Signal1:avg', samples=[0.0, 0.0, 0.0])

>>> # average of samples and iterables
>>> Trace('Signal', [1, -2, 3]).average([-1, 2, -3])
Trace(label='Signal:avg', samples=[0.0, 0.0, 0.0])

>>> # average of samples and numbers
>>> Trace('Signal', [1, -2, 3]).average(2)
Trace(label='Signal:avg', samples=[1.5, 0.0, 2.5])

Note

An iterable should have at least the same length as the signal samples, otherwise only a subset of the signal samples is returned!

(Source code, html)

Interpolate

You can piecewise linear interpolate the signal samples between consecutive data points by calling the method interpolate().

A new Trace instance labeled with the performed transformation 'interpolate' is returned.

>>> # interpolate linear the samples within the sorted data points
>>> Trace('Signal', [-1.5, -1.0, -0.5, 0 , 0.5, 1.0, 1.5]).interpolate(
...       x=[1, -0.5, -1, 0.5], y=[ -1, 0, 1, 0])
Trace(label='Signal:interpolate',
      samples=[1.0, 1.0, 0.0, 0.0, 0.0, -1.0, -1.0])

Note

The data points are sorted internally by their x-coordinates to be in ascending order.

(Source code, html)