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I have a Numpy rec array from which I would like to do some quick queries similar to SQL: SELECT * where array['phase'] == "P". I would like to get a Record Array as output with each row corresponding to a row from the original array that met the query criteria. Any ideas? I am pretty sure I have done this before, but just cannot remember the function.
Thanks
rec.array([ (5295499, 2.8123965, 127.20443, 0.0, 1237680436.06, 908, -19.942589, 134.33951, 0.3888, 'P', 0.19513991),
(5295499, 2.8123965, 127.20443, 0.0, 1237680436.06, 1387, -18.102, 125.639, 0.11, 'P', 1.2515257),
(5447254, 39.025873, 143.31065, 0.0, 1245455521.85, 1512, 33.121667, 130.87833, 0.573, 'LR', 45.099504)],
dtype=[('eventid', '<i4'), ('eventlat', '<f8'), ('eventlon', '<f8'), ('eventdepth', '<f8'), ('eventtime', '<f8'), ('stationid', '<i4'), ('stationlat', '<f8'), ('stationlon', '<f8'), ('stationelv', '<f8'), ('phase', '|S7'), ('timeresidual', '<f8')])
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In NumPy , it is very easy to access any rows of a multidimensional array. All we need to do is Slicing the array according to the given conditions. Whenever we need to perform analysis, slicing plays an important role.
In the NumPy with the help of shape() function, we can find the number of rows and columns. In this function, we pass a matrix and it will return row and column number of the matrix. Return: The number of rows and columns.
We can use [][] operator to select an element from Numpy Array i.e. Example 1: Select the element at row index 1 and column index 2. Or we can pass the comma separated list of indices representing row index & column index too i.e.
select()() function return an array drawn from elements in choicelist, depending on conditions. Parameters : condlist : [list of bool ndarrays] It determine from which array in choicelist the output elements are taken.
Try:
array[array['phase']=='P']
array['phase']=='P' returns a boolean numpy array. When idx is a boolean array, array[idx] returns an array composed of those rows where idx is True.
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