SciPy

This is documentation for an old release of NumPy (version 1.10.0). Read this page in the documentation of the latest stable release (version > 1.17).

numpy.chararray.flags

chararray.flags

Information about the memory layout of the array.

Notes

The flags object can be accessed dictionary-like (as in a.flags['WRITEABLE']), or by using lowercased attribute names (as in a.flags.writeable). Short flag names are only supported in dictionary access.

Only the UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be changed by the user, via direct assignment to the attribute or dictionary entry, or by calling ndarray.setflags.

The array flags cannot be set arbitrarily:

  • UPDATEIFCOPY can only be set False.
  • ALIGNED can only be set True if the data is truly aligned.
  • WRITEABLE can only be set True if the array owns its own memory or the ultimate owner of the memory exposes a writeable buffer interface or is a string.

Arrays can be both C-style and Fortran-style contiguous simultaneously. This is clear for 1-dimensional arrays, but can also be true for higher dimensional arrays.

Even for contiguous arrays a stride for a given dimension arr.strides[dim] may be arbitrary if arr.shape[dim] == 1 or the array has no elements. It does not generally hold that self.strides[-1] == self.itemsize for C-style contiguous arrays or self.strides[0] == self.itemsize for Fortran-style contiguous arrays is true.

Attributes

C_CONTIGUOUS (C) The data is in a single, C-style contiguous segment.
F_CONTIGUOUS (F) The data is in a single, Fortran-style contiguous segment.
OWNDATA (O) The array owns the memory it uses or borrows it from another object.
WRITEABLE (W) The data area can be written to. Setting this to False locks the data, making it read-only. A view (slice, etc.) inherits WRITEABLE from its base array at creation time, but a view of a writeable array may be subsequently locked while the base array remains writeable. (The opposite is not true, in that a view of a locked array may not be made writeable. However, currently, locking a base object does not lock any views that already reference it, so under that circumstance it is possible to alter the contents of a locked array via a previously created writeable view onto it.) Attempting to change a non-writeable array raises a RuntimeError exception.
ALIGNED (A) The data and all elements are aligned appropriately for the hardware.
UPDATEIFCOPY (U) This array is a copy of some other array. When this array is deallocated, the base array will be updated with the contents of this array.
FNC F_CONTIGUOUS and not C_CONTIGUOUS.
FORC F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).
BEHAVED (B) ALIGNED and WRITEABLE.
CARRAY (CA) BEHAVED and C_CONTIGUOUS.
FARRAY (FA) BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.

Previous topic

numpy.chararray.dtype

Next topic

numpy.chararray.flat