def fromarrays(
arraylist, dates=None, dtype=None, shape=None, formats=None, names=None, titles=None, aligned=False, byteorder=None
):
"""Creates a mrecarray from a (flat) list of masked arrays.
:Parameters:
- `arraylist` : Sequence
A list of (masked) arrays. Each element of the sequence is first converted
to a masked array if needed. If a 2D array is passed as argument, it is
processed line by line
- `dtype` : numeric.dtype
Data type descriptor.
- `shape` : Integer *[None]*
Number of records. If None, `shape` is defined from the shape of the first
array in the list.
- `formats` :
(Description to write)
- `names` :
(description to write)
- `titles`:
(Description to write)
- `aligned`: Boolen *[False]*
(Description to write, not used anyway)
- `byteorder`: Boolen *[None]*
(Description to write, not used anyway)
"""
arraylist = [MA.asarray(x) for x in arraylist]
# Define/check the shape.....................
if shape is None or shape == 0:
shape = arraylist[0].shape
if isinstance(shape, int):
shape = (shape,)
# Define formats from scratch ...............
if formats is None and dtype is None:
formats = _getformats(arraylist)
# Define the dtype ..........................
if dtype is not None:
descr = numeric.dtype(dtype)
_names = descr.names
else:
parsed = format_parser(formats, names, titles, aligned, byteorder)
_names = parsed._names
descr = parsed._descr
# Determine shape from data-type.............
if len(descr) != len(arraylist):
msg = "Mismatch between the number of fields (%i) and the number of " "arrays (%i)"
raise ValueError, msg % (len(descr), len(arraylist))
d0 = descr[0].shape
nn = len(d0)
if nn > 0:
shape = shape[:-nn]
# Make sure the shape is the correct one ....
for k, obj in enumerate(arraylist):
nn = len(descr[k].shape)
testshape = obj.shape[: len(obj.shape) - nn]
if testshape != shape:
raise ValueError, "Array-shape mismatch in array %d" % k
# Reconstruct the descriptor, by creating a _data and _mask version
return MultiTimeSeries(arraylist, dtype=descr)
