API

The Dataset() class

New in version 2016.11

This class allows simple data handling.

class allantools.Dataset(data=None, rate=1.0, data_type='phase', taus=None)

Dataset class for Allantools

Example:

import numpy as np
# Load random data
a = allantools.Dataset(data=np.random.rand(1000))
# compute mdev
a.compute("mdev")
print(a.out["stat"])

compute() returns the result of the computation and also stores it in the object’s out member.

__init__(data=None, rate=1.0, data_type='phase', taus=None)

Initialize object with input data

Parameters

data: np.array: Input data. Provide either phase or frequency (fractional, adimensional)
rate: float: The sampling rate for data, in Hz. Defaults to 1.0
data_type: {‘phase’, ‘freq’}: Data type, i.e. phase or frequency. Defaults to “phase”.
taus: np.array: Array of tau values, in seconds, for which to compute statistic. Optionally set taus=[“all”|”octave”|”decade”] for automatic calculation of taus list

Returns

Dataset(): A Dataset() instance

compute(function)

Evaluate the passed function with the supplied data.

Stores result in self.out.

Parameters

function: str: Name of the allantools function to evaluate

Returns

result: dict: The results of the calculation.

inp: input data Dict,

out: output data Dict, to be populated by compute()

set_input(data, rate=1.0, data_type='phase', taus=None)

Optionnal method if you chose not to set inputs on init

Parameters

data: np.array: Input data. Provide either phase or frequency (fractional, adimensional)
rate: float: The sampling rate for data, in Hz. Defaults to 1.0
data_type: {‘phase’, ‘freq’}: Data type, i.e. phase or frequency. Defaults to “phase”.
taus: np.array: Array of tau values, in seconds, for which to compute statistic. Optionally set taus=[“all”|”octave”|”decade”] for automatic

write_results(filename, digits=5, header_params={})

Output result to text

Save calculation results to disk. Will overwrite any existing file.

Parameters

filename: str: Path to the output file
digits: int: Number of significant digits in output
header_params: dict: Arbitrary dict of params to be included in header

Returns

None

The Plot() class

New in version 2016.11

This class allows simple data plotting.

class allantools.Plot(no_display=False)

A class for plotting data once computed by Allantools

Example:

import allantools
import numpy as np
a = allantools.Dataset(data=np.random.rand(1000))
a.compute("mdev")
b = allantools.Plot()
b.plot(a)
b.show()

Uses matplotlib. self.fig and self.ax stores the return values of matplotlib.pyplot.subplots(). plot() sets various defaults, but you can change them by using standard matplotlib method on self.fig and self.ax

__init__(no_display=False): set no_display to True when we don’t have an X-window (e.g. for tests)

plot(atDataset, errorbars=False, grid=False, **kwargs)

Use matplotlib methods for plotting

Additional keywords arguments are passed to matplotlib.pyplot.plot().

Parameters

atDatasetallantools.Dataset(): a dataset with computed data
errorbarsboolean: Plot errorbars. Defaults to False
gridboolean: Plot grid. Defaults to False

save(f): Save figure to file

show()

Calls matplotlib.pyplot.show()

Keeping this separated from plot() allows to tweak display before rendering