Say I have a numpy structured array (a.k.a. record array):
record_types = np.dtype([
('date',object), #00 - Timestamp
('lats',float), #01 - Latitude
('lons',float), #02 - Longitude
('vals',float), #03 - Value
])
data = np.zeros(10, dtype=record_types)
If I try to call the shape attribute, I get (10,)
How can I do something like the following:
y, x = data.shape
To get y = 10 and x = 4
Thanks!
This is one of the confusing things about structured arrays.
You basically have a (n-1)D array where each item is a C-like struct.
This type of structure allows for all kinds of useful things (easy file IO with binary formats, for example), but it's quite confusing for a lot of other use cases. For what you're doing, you'd likely be better served by using pandas than directly using a structured array.
That having been said, here's how you'd get what you're asking:
def structured_shape(x):
if len(x.dtype) > 0
return list(x.shape) + [len(x.dtype)]
else:
return x.shape
pandas, but this is another great reason. Thank you!