SciPy

numpy.recarray

class numpy.recarray[source]

Construct an ndarray that allows field access using attributes.

Arrays may have a data-types containing fields, analogous to columns in a spread sheet. An example is [(x, int), (y, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['x'] and arr['y']. Record arrays allow the fields to be accessed as members of the array, using arr.x and arr.y.

Parameters:

shape : tuple

Shape of output array.

dtype : data-type, optional

The desired data-type. By default, the data-type is determined from formats, names, titles, aligned and byteorder.

formats : list of data-types, optional

A list containing the data-types for the different columns, e.g. ['i4', 'f8', 'i4']. formats does not support the new convention of using types directly, i.e. (int, float, int). Note that formats must be a list, not a tuple. Given that formats is somewhat limited, we recommend specifying dtype instead.

names : tuple of str, optional

The name of each column, e.g. ('x', 'y', 'z').

buf : buffer, optional

By default, a new array is created of the given shape and data-type. If buf is specified and is an object exposing the buffer interface, the array will use the memory from the existing buffer. In this case, the offset and strides keywords are available.

Returns:

rec : recarray

Empty array of the given shape and type.

Other Parameters:
 

titles : tuple of str, optional

Aliases for column names. For example, if names were ('x', 'y', 'z') and titles is ('x_coordinate', 'y_coordinate', 'z_coordinate'), then arr['x'] is equivalent to both arr.x and arr.x_coordinate.

byteorder : {‘<’, ‘>’, ‘=’}, optional

Byte-order for all fields.

aligned : bool, optional

Align the fields in memory as the C-compiler would.

strides : tuple of ints, optional

Buffer (buf) is interpreted according to these strides (strides define how many bytes each array element, row, column, etc. occupy in memory).

offset : int, optional

Start reading buffer (buf) from this offset onwards.

order : {‘C’, ‘F’}, optional

Row-major or column-major order.

See also

rec.fromrecords
Construct a record array from data.
record
fundamental data-type for recarray.
format_parser
determine a data-type from formats, names, titles.

Notes

This constructor can be compared to empty: it creates a new record array but does not fill it with data. To create a record array from data, use one of the following methods:

  1. Create a standard ndarray and convert it to a record array, using arr.view(np.recarray)
  2. Use the buf keyword.
  3. Use np.rec.fromrecords.

Examples

Create an array with two fields, x and y:

>>> x = np.array([(1.0, 2), (3.0, 4)], dtype=[('x', float), ('y', int)])
>>> x
array([(1.0, 2), (3.0, 4)],
      dtype=[('x', '<f8'), ('y', '<i4')])
>>> x['x']
array([ 1.,  3.])

View the array as a record array:

>>> x = x.view(np.recarray)
>>> x.x
array([ 1.,  3.])
>>> x.y
array([2, 4])

Create a new, empty record array:

>>> np.recarray((2,),
... dtype=[('x', int), ('y', float), ('z', int)]) 
rec.array([(-1073741821, 1.2249118382103472e-301, 24547520),
       (3471280, 1.2134086255804012e-316, 0)],
      dtype=[('x', '<i4'), ('y', '<f8'), ('z', '<i4')])

Attributes

T Same as self.transpose(), except that self is returned if self.ndim < 2.
base Base object if memory is from some other object.
ctypes An object to simplify the interaction of the array with the ctypes module.
data Python buffer object pointing to the start of the array’s data.
dtype Data-type of the array’s elements.
flags Information about the memory layout of the array.
flat A 1-D iterator over the array.
imag The imaginary part of the array.
itemsize Length of one array element in bytes.
nbytes Total bytes consumed by the elements of the array.
ndim Number of array dimensions.
real The real part of the array.
shape Tuple of array dimensions.
size Number of elements in the array.
strides Tuple of bytes to step in each dimension when traversing an array.

Methods

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.
argpartition(kth[, axis, kind, order]) Returns the indices that would partition this array.
argsort([axis, kind, order]) Returns the indices that would sort this array.
astype(dtype[, order, casting, subok, copy]) Copy of the array, cast to a specified type.
byteswap(inplace) Swap the bytes of the array elements
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].
compress(condition[, axis, out]) Return selected slices of this array along given axis.
conj() Complex-conjugate all elements.
conjugate() Return the complex conjugate, element-wise.
copy([order]) Return a copy of the array.
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.
diagonal([offset, axis1, axis2]) Return specified diagonals.
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.
field(attr[, val])
fill(value) Fill the array with a scalar value.
flatten([order]) Return a copy of the array collapsed into one dimension.
getfield(dtype[, offset]) Returns a field of the given array as a certain type.
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.
newbyteorder([new_order]) Return the array with the same data viewed with a different byte order.
nonzero() Return the indices of the elements that are non-zero.
partition(kth[, axis, kind, order]) Rearranges the elements in the array in such a way that value of the element in kth position is in the position it would be in a sorted array.
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.
ravel([order]) Return a flattened array.
repeat(repeats[, axis]) Repeat elements of an array.
reshape(shape[, order]) Returns an array containing the same data with a new shape.
resize(new_shape[, refcheck]) Change shape and size of array in-place.
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.
setfield(val, dtype[, offset]) Put a value into a specified place in a field defined by a data-type.
setflags([write, align, uic]) Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively.
sort([axis, kind, order]) Sort an array, in-place.
squeeze([axis]) Remove single-dimensional entries from the shape of a.
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.
swapaxes(axis1, axis2) Return a view of the array with axis1 and axis2 interchanged.
take(indices[, axis, out, mode]) Return an array formed from the elements of a at the given indices.
tobytes([order]) Construct Python bytes containing the raw data bytes in the array.
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 Python bytes containing the raw data bytes in the array.
trace([offset, axis1, axis2, dtype, out]) Return the sum along diagonals of the array.
transpose(*axes) Returns a view of the array with axes transposed.
var([axis, dtype, out, ddof]) Returns the variance of the array elements, along given axis.
view([dtype, type])