# This is a "structarray in cython with numpy recarrays" testfile
import numpy as np
cimport numpy as np

# My structarray has nodes with fields x and y
# This also works without packed, but I have seen packed used in other places where people asked similar questions
# I assume that for two doubles that is equivalent but is necessary for in8s in between
cdef packed struct node:
    double x
    double y
# I suppose that would be the equivalent numpy dtype?
# Note: During compilation it warns me about double to float downcasts, but I do not see where
nodetype = [('x' , np.float64),('y', np.float64)]

def fun():
    # Make 10 element recarray
    # (Just looked it up. A point where 1-based indexing would save a look in the docs)
    mynode1 = np.recarray(10,dtype=nodetype)

    # Recarray with cdef struct
    mynode1 = np.recarray(10,dtype=nodetype)

    # Fill it with non-garbage somewhere
    mynode1[2].x=1.0
    mynode1[2].y=2.0

    # Brave: give recarray element to a c function assuming its equivalent to the struct
    ny = cfuny(mynode1[2])
    assert ny==2.0 # works!

    # Test memoryview, assuming type node
    cdef node [:] nview = mynode1
    ny = cfunyv(nview,2)
    assert ny==2.0 # works!

    # This sets the numpy recarray value with a c function the gts a memoryview
    cfunyv_set(nview,5,9.0)
    assert mynode1[5].y==9.0 # alsow works!

    return 0

# return node element y from c struct node
cdef double cfuny(node n):
    return n.y

# give element i from memoryview of recarray to c function expecting a c struct
cdef double cfunyv(node [:] n, int i):
    return cfuny(n[i])

# write into recarray with a function expecting a memoryview with type node
cdef int cfunyv_set(node [:] n,int i,double val):
    n[i].y = val
    return 0