Quantity

class astropy.units.Quantity[source] [edit on github]

Bases: numpy.ndarray

A Quantity represents a number with some associated unit.

Parameters:

value : number, ndarray, Quantity object, or sequence of Quantity objects.

The numerical value of this quantity in the units given by unit. If a Quantity or sequence of them (or any other valid object with a unit attribute), creates a new Quantity object, converting to unit units as needed.

unit : UnitBase instance, str

An object that represents the unit associated with the input value. Must be an UnitBase object or a string parseable by the units package.

dtype : ~numpy.dtype, optional

The dtype of the resulting Numpy array or scalar that will hold the value. If not provided, it is determined from the input, except that any input that cannot represent float (integer and bool) is converted to float.

copy : bool, optional

If True (default), then the value is copied. Otherwise, a copy will only be made if __array__ returns a copy, if value is a nested sequence, or if a copy is needed to satisfy an explicitly given dtype. (The False option is intended mostly for internal use, to speed up initialization where a copy is known to have been made. Use with care.)

order : {‘C’, ‘F’, ‘A’}, optional

Specify the order of the array. As in array. This parameter is ignored if the input is a Quantity and copy=False.

subok : bool, optional

If False (default), the returned array will be forced to be a Quantity. Otherwise, Quantity subclasses will be passed through.

ndmin : int, optional

Specifies the minimum number of dimensions that the resulting array should have. Ones will be pre-pended to the shape as needed to meet this requirement. This parameter is ignored if the input is a Quantity and copy=False.

Raises:

TypeError

If the value provided is not a Python numeric type.

TypeError

If the unit provided is not either a Unit object or a parseable string unit.

Attributes Summary

cgs Returns a copy of the current Quantity instance with CGS units.
equivalencies A list of equivalencies that will be applied by default during unit conversions.
flat A 1-D iterator over the Quantity array.
info Container for meta information like name, description, format.
isscalar True if the value of this quantity is a scalar, or False if it is an array-like object.
si Returns a copy of the current Quantity instance with SI units.
unit A UnitBase object representing the unit of this quantity.
value The numerical value of this quantity.

Methods Summary

all([axis, out]) Returns True if all elements evaluate to True.
any([axis, out]) Returns True if any of the elements of a evaluate to True.
argmax([axis, out]) Return indices of the maximum values along the given axis.
argmin([axis, out]) Return indices of the minimum values along the given axis of a.
argsort([axis, kind, order]) Returns the indices that would sort this array.
choose(choices[, out, mode]) Use an index array to construct a new array from a set of choices.
clip(a_min, a_max[, out]) Return an array whose values are limited to [a_min, a_max].
cumprod([axis, dtype, out]) Return the cumulative product of the elements along the given axis.
cumsum([axis, dtype, out]) Return the cumulative sum of the elements along the given axis.
decompose([bases]) Generates a new Quantity with the units decomposed.
diff([n, axis])
dot(b[, out]) Dot product of two arrays.
dump(file) Dump a pickle of the array to the specified file.
dumps() Returns the pickle of the array as a string.
ediff1d([to_end, to_begin])
fill(value) Fill the array with a scalar value.
insert(obj, values[, axis]) Insert values along the given axis before the given indices and return a new Quantity object.
item(*args) Copy an element of an array to a standard Python scalar and return it.
itemset(*args) Insert scalar into an array (scalar is cast to array’s dtype, if possible)
max([axis, out]) Return the maximum along a given axis.
mean([axis, dtype, out]) Returns the average of the array elements along given axis.
min([axis, out]) Return the minimum along a given axis.
nansum([axis, out, keepdims])
prod([axis, dtype, out]) Return the product of the array elements over the given axis
ptp([axis, out]) Peak to peak (maximum - minimum) value along a given axis.
put(indices, values[, mode]) Set a.flat[n] = values[n] for all n in indices.
round([decimals, out]) Return a with each element rounded to the given number of decimals.
searchsorted(v[, side, sorter]) Find indices where elements of v should be inserted in a to maintain order.
std([axis, dtype, out, ddof]) Returns the standard deviation of the array elements along given axis.
sum([axis, dtype, out]) Return the sum of the array elements over the given axis.
to(unit[, equivalencies]) Returns a new Quantity object with the specified units.
tofile(fid[, sep, format]) Write array to a file as text or binary (default).
tolist() Return the array as a (possibly nested) list.
tostring([order]) Construct a Python string containing the raw data bytes in the array.
trace([offset, axis1, axis2, dtype, out]) Return the sum along diagonals of the array.
var([axis, dtype, out, ddof]) Returns the variance of the array elements, along given axis.

Attributes Documentation

cgs

Returns a copy of the current Quantity instance with CGS units. The value of the resulting object will be scaled.

equivalencies

A list of equivalencies that will be applied by default during unit conversions.

flat

A 1-D iterator over the Quantity array.

This returns a QuantityIterator instance, which behaves the same as the flatiter instance returned by flat, and is similar to, but not a subclass of, Python’s built-in iterator object.

info

Container for meta information like name, description, format. This is required when the object is used as a mixin column within a table, but can be used as a general way to store meta information.

isscalar

True if the value of this quantity is a scalar, or False if it is an array-like object.

Note

This is subtly different from numpy.isscalar in that numpy.isscalar returns False for a zero-dimensional array (e.g. np.array(1)), while this is True for quantities, since quantities cannot represent true numpy scalars.

si

Returns a copy of the current Quantity instance with SI units. The value of the resulting object will be scaled.

unit

A UnitBase object representing the unit of this quantity.

value

The numerical value of this quantity.

Methods Documentation

all(axis=None, out=None)[source] [edit on github]

Returns True if all elements evaluate to True.

Refer to numpy.all for full documentation.

See also

numpy.all
equivalent function
any(axis=None, out=None)[source] [edit on github]

Returns True if any of the elements of a evaluate to True.

Refer to numpy.any for full documentation.

See also

numpy.any
equivalent function
argmax(axis=None, out=None)[source] [edit on github]

Return indices of the maximum values along the given axis.

Refer to numpy.argmax for full documentation.

See also

numpy.argmax
equivalent function
argmin(axis=None, out=None)[source] [edit on github]

Return indices of the minimum values along the given axis of a.

Refer to numpy.argmin for detailed documentation.

See also

numpy.argmin
equivalent function
argsort(axis=-1, kind='quicksort', order=None)[source] [edit on github]

Returns the indices that would sort this array.

Refer to numpy.argsort for full documentation.

See also

numpy.argsort
equivalent function
choose(choices, out=None, mode='raise')[source] [edit on github]

Use an index array to construct a new array from a set of choices.

Refer to numpy.choose for full documentation.

See also

numpy.choose
equivalent function
clip(a_min, a_max, out=None)[source] [edit on github]

Return an array whose values are limited to [a_min, a_max].

Refer to numpy.clip for full documentation.

See also

numpy.clip
equivalent function
cumprod(axis=None, dtype=None, out=None)[source] [edit on github]

Return the cumulative product of the elements along the given axis.

Refer to numpy.cumprod for full documentation.

See also

numpy.cumprod
equivalent function
cumsum(axis=None, dtype=None, out=None)[source] [edit on github]

Return the cumulative sum of the elements along the given axis.

Refer to numpy.cumsum for full documentation.

See also

numpy.cumsum
equivalent function
decompose(bases=[])[source] [edit on github]

Generates a new Quantity with the units decomposed. Decomposed units have only irreducible units in them (see astropy.units.UnitBase.decompose).

Parameters:

bases : sequence of UnitBase, optional

The bases to decompose into. When not provided, decomposes down to any irreducible units. When provided, the decomposed result will only contain the given units. This will raises a UnitsError if it’s not possible to do so.

Returns:

newq : Quantity

A new object equal to this quantity with units decomposed.

diff(n=1, axis=-1)[source] [edit on github]
dot(b, out=None)[source] [edit on github]

Dot product of two arrays.

Refer to numpy.dot for full documentation.

See also

numpy.dot
equivalent function

Examples

>>> a = np.eye(2)
>>> b = np.ones((2, 2)) * 2
>>> a.dot(b)
array([[ 2.,  2.],
       [ 2.,  2.]])

This array method can be conveniently chained:

>>> a.dot(b).dot(b)
array([[ 8.,  8.],
       [ 8.,  8.]])
dump(file)[source] [edit on github]

Dump a pickle of the array to the specified file. The array can be read back with pickle.load or numpy.load.

Parameters:

file : str

A string naming the dump file.

dumps()[source] [edit on github]

Returns the pickle of the array as a string. pickle.loads or numpy.loads will convert the string back to an array.

Parameters:None
ediff1d(to_end=None, to_begin=None)[source] [edit on github]
fill(value)[source] [edit on github]

Fill the array with a scalar value.

Parameters:

value : scalar

All elements of a will be assigned this value.

Examples

>>> a = np.array([1, 2])
>>> a.fill(0)
>>> a
array([0, 0])
>>> a = np.empty(2)
>>> a.fill(1)
>>> a
array([ 1.,  1.])
insert(obj, values, axis=None)[source] [edit on github]

Insert values along the given axis before the given indices and return a new Quantity object.

This is a thin wrapper around the numpy.insert function.

Parameters:

obj : int, slice or sequence of ints

Object that defines the index or indices before which values is inserted.

values : array-like

Values to insert. If the type of values is different from that of quantity, values is converted to the matching type. values should be shaped so that it can be broadcast appropriately The unit of values must be consistent with this quantity.

axis : int, optional

Axis along which to insert values. If axis is None then the quantity array is flattened before insertion.

Returns:

out : Quantity

A copy of quantity with values inserted. Note that the insertion does not occur in-place: a new quantity array is returned.

Examples

>>> import astropy.units as u
>>> q = [1, 2] * u.m
>>> q.insert(0, 50 * u.cm)
<Quantity [ 0.5,  1.,  2.] m>
>>> q = [[1, 2], [3, 4]] * u.m
>>> q.insert(1, [10, 20] * u.m, axis=0)
<Quantity [[  1.,  2.],
           [ 10., 20.],
           [  3.,  4.]] m>
>>> q.insert(1, 10 * u.m, axis=1)
<Quantity [[  1., 10.,  2.],
           [  3., 10.,  4.]] m>
item(*args)[source] [edit on github]

Copy an element of an array to a standard Python scalar and return it.

Parameters:

*args : Arguments (variable number and type)

  • none: in this case, the method only works for arrays with one element (a.size == 1), which element is copied into a standard Python scalar object and returned.
  • int_type: this argument is interpreted as a flat index into the array, specifying which element to copy and return.
  • tuple of int_types: functions as does a single int_type argument, except that the argument is interpreted as an nd-index into the array.
Returns:

z : Standard Python scalar object

A copy of the specified element of the array as a suitable Python scalar

Notes

When the data type of a is longdouble or clongdouble, item() returns a scalar array object because there is no available Python scalar that would not lose information. Void arrays return a buffer object for item(), unless fields are defined, in which case a tuple is returned.

item is very similar to a[args], except, instead of an array scalar, a standard Python scalar is returned. This can be useful for speeding up access to elements of the array and doing arithmetic on elements of the array using Python’s optimized math.

Examples

>>> x = np.random.randint(9, size=(3, 3))
>>> x
array([[3, 1, 7],
       [2, 8, 3],
       [8, 5, 3]])
>>> x.item(3)
2
>>> x.item(7)
5
>>> x.item((0, 1))
1
>>> x.item((2, 2))
3
itemset(*args)[source] [edit on github]

Insert scalar into an array (scalar is cast to array’s dtype, if possible)

There must be at least 1 argument, and define the last argument as item. Then, a.itemset(*args) is equivalent to but faster than a[args] = item. The item should be a scalar value and args must select a single item in the array a.

Parameters:

*args : Arguments

If one argument: a scalar, only used in case a is of size 1. If two arguments: the last argument is the value to be set and must be a scalar, the first argument specifies a single array element location. It is either an int or a tuple.

Notes

Compared to indexing syntax, itemset provides some speed increase for placing a scalar into a particular location in an ndarray, if you must do this. However, generally this is discouraged: among other problems, it complicates the appearance of the code. Also, when using itemset (and item) inside a loop, be sure to assign the methods to a local variable to avoid the attribute look-up at each loop iteration.

Examples

>>> x = np.random.randint(9, size=(3, 3))
>>> x
array([[3, 1, 7],
       [2, 8, 3],
       [8, 5, 3]])
>>> x.itemset(4, 0)
>>> x.itemset((2, 2), 9)
>>> x
array([[3, 1, 7],
       [2, 0, 3],
       [8, 5, 9]])
max(axis=None, out=None)[source] [edit on github]

Return the maximum along a given axis.

Refer to numpy.amax for full documentation.

See also

numpy.amax
equivalent function
mean(axis=None, dtype=None, out=None)[source] [edit on github]

Returns the average of the array elements along given axis.

Refer to numpy.mean for full documentation.

See also

numpy.mean
equivalent function
min(axis=None, out=None)[source] [edit on github]

Return the minimum along a given axis.

Refer to numpy.amin for full documentation.

See also

numpy.amin
equivalent function
nansum(axis=None, out=None, keepdims=False)[source] [edit on github]
prod(axis=None, dtype=None, out=None)[source] [edit on github]

Return the product of the array elements over the given axis

Refer to numpy.prod for full documentation.

See also

numpy.prod
equivalent function
ptp(axis=None, out=None)[source] [edit on github]

Peak to peak (maximum - minimum) value along a given axis.

Refer to numpy.ptp for full documentation.

See also

numpy.ptp
equivalent function
put(indices, values, mode='raise')[source] [edit on github]

Set a.flat[n] = values[n] for all n in indices.

Refer to numpy.put for full documentation.

See also

numpy.put
equivalent function
round(decimals=0, out=None)[source] [edit on github]

Return a with each element rounded to the given number of decimals.

Refer to numpy.around for full documentation.

See also

numpy.around
equivalent function
searchsorted(v, side='left', sorter=None)[source] [edit on github]

Find indices where elements of v should be inserted in a to maintain order.

For full documentation, see numpy.searchsorted

See also

numpy.searchsorted
equivalent function
std(axis=None, dtype=None, out=None, ddof=0)[source] [edit on github]

Returns the standard deviation of the array elements along given axis.

Refer to numpy.std for full documentation.

See also

numpy.std
equivalent function
sum(axis=None, dtype=None, out=None)[source] [edit on github]

Return the sum of the array elements over the given axis.

Refer to numpy.sum for full documentation.

See also

numpy.sum
equivalent function
to(unit, equivalencies=[])[source] [edit on github]

Returns a new Quantity object with the specified units.

Parameters:

unit : UnitBase instance, str

An object that represents the unit to convert to. Must be an UnitBase object or a string parseable by the units package.

equivalencies : list of equivalence pairs, optional

A list of equivalence pairs to try if the units are not directly convertible. See Equivalencies. If not provided or [], class default equivalencies will be used (none for Quantity, but may be set for subclasses) If None, no equivalencies will be applied at all, not even any set globally or within a context.

tofile(fid, sep="", format="%s")[source] [edit on github]

Write array to a file as text or binary (default).

Data is always written in ‘C’ order, independent of the order of a. The data produced by this method can be recovered using the function fromfile().

Parameters:

fid : file or str

An open file object, or a string containing a filename.

sep : str

Separator between array items for text output. If “” (empty), a binary file is written, equivalent to file.write(a.tostring()).

format : str

Format string for text file output. Each entry in the array is formatted to text by first converting it to the closest Python type, and then using “format” % item.

Notes

This is a convenience function for quick storage of array data. Information on endianness and precision is lost, so this method is not a good choice for files intended to archive data or transport data between machines with different endianness. Some of these problems can be overcome by outputting the data as text files, at the expense of speed and file size.

tolist()[source] [edit on github]

Return the array as a (possibly nested) list.

Return a copy of the array data as a (nested) Python list. Data items are converted to the nearest compatible Python type.

Parameters:

none

Returns:

y : list

The possibly nested list of array elements.

Notes

The array may be recreated, a = np.array(a.tolist()).

Examples

>>> a = np.array([1, 2])
>>> a.tolist()
[1, 2]
>>> a = np.array([[1, 2], [3, 4]])
>>> list(a)
[array([1, 2]), array([3, 4])]
>>> a.tolist()
[[1, 2], [3, 4]]
tostring(order='C')[source] [edit on github]

Construct a Python string containing the raw data bytes in the array.

Constructs a Python string showing a copy of the raw contents of data memory. The string can be produced in either ‘C’ or ‘Fortran’, or ‘Any’ order (the default is ‘C’-order). ‘Any’ order means C-order unless the F_CONTIGUOUS flag in the array is set, in which case it means ‘Fortran’ order.

Parameters:

order : {‘C’, ‘F’, None}, optional

Order of the data for multidimensional arrays: C, Fortran, or the same as for the original array.

Returns:

s : str

A Python string exhibiting a copy of a‘s raw data.

Examples

>>> x = np.array([[0, 1], [2, 3]])
>>> x.tostring()
'\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00'
>>> x.tostring('C') == x.tostring()
True
>>> x.tostring('F')
'\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x03\x00\x00\x00'
trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)[source] [edit on github]

Return the sum along diagonals of the array.

Refer to numpy.trace for full documentation.

See also

numpy.trace
equivalent function
var(axis=None, dtype=None, out=None, ddof=0)[source] [edit on github]

Returns the variance of the array elements, along given axis.

Refer to numpy.var for full documentation.

See also

numpy.var
equivalent function