QuantityArray

Subclasses a Numpy ndarray and adds a unit attribute. It can be used just like any Numpy array.

Extra attributes

To create a QuantityArray use

>>> from PhysicalQuantities.quantityarray import QuantityArray
>>> qa = QuantityArray( <value>, <unit>)

Where <value> is an Numpy ndarray, and <unit>’ is a `PhysiclUnit object or a string representing a unit like m or km/h.

You can scale and remove units using attributes. If you have a variable qa of type QuantityArray with unit m, you can rescale in km using qa.km. If you use qa.km_ you will get a ndarray view and the unit is stripped from the array.

Alternatively, more complicated units can be rescaled using the .to() function. So qa.to(‘km’) will scale the given units to km.

Examples

>>> from PhysicalQuantities import QA
>>> import numpy as np
>>> a = np.random.randn(10)
>>> b = QA(a, 'm/s')
>>> b
PhysicalQuantityArray([ 1.36836913  0.70860175  0.00633686 -0.54290276  0.82087296  0.49118831
  0.7917231   0.13107132  0.35147733  1.14482806], unit=m/s)
>> b.view(np.ndarray)
array([ 1.36836913  0.70860175  0.00633686 -0.54290276  0.82087296  0.49118831
  0.7917231   0.13107132  0.35147733  1.14482806])

>>> b.to('mm/h')
PhysicalQuantityArray([ 4926128.85358709  2550966.29803592    22812.69863759 -1954449.92312585
  2955142.65295286  1768277.90323167  2850203.14531766   471856.75616011
  1265318.38302892  4121381.00263216], unit=mm/h)
>>> c = QA(a, 'km')
>>> c.m
PhysicalQuantityArray([1368.369126    708.60174945    6.33686073 -542.90275642  820.87295915
  491.18830645  791.72309592  131.07132116  351.47732862 1144.82805629], unit=m)
>>> c.m_
array([1368.369126  ,  708.60174945,    6.33686073, -542.90275642,
        820.87295915,  491.18830645,  791.72309592,  131.07132116,
        351.47732862, 1144.82805629])

Reference

Implement a Numpy array with physical units

class PhysicalQuantities.quantityarray.PhysicalQuantityArray(input_array, unit=None)

__array_finalize__(obj, /)

Present so subclasses can call super. Does nothing.

__dir__()

Default dir() implementation.

static __new__(cls, input_array, unit=None)

__repr__() → str

Return repr(self).

property base: PhysicalQuantityArray

Base object if memory is from some other object.

Examples

The base of an array that owns its memory is None:

>>> x = np.array([1,2,3,4])
>>> x.base is None
True

Slicing creates a view, whose memory is shared with x:

>>> y = x[2:]
>>> y.base is x
True

to(*units) → PhysicalQuantityArray

Convert to a different unit

Parameters

unitsstr

Units to convert to

Returns

PhysicalQuantityArray

Array with converted units