The array version of the AB coeff calculation still has bugs.
rewriting to C Former-commit-id: c6582a03a8b73b46156416eb0faa3f866e2638ce
This commit is contained in:
Marek Nečada
parent
2d88a1ef0d
commit
40809ce90a
107
qpms/qpms_c.pyx
107
qpms/qpms_c.pyx
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@ -554,7 +554,7 @@ cdef class trans_calculator:
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# TODO CHECK (and try to cast) INPUT ARRAY TYPES (now is done)
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# BIG FIXME: make skalars valid arguments, now r, theta, phi, r_ge_d have to be ndarrays
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cdef:
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int daxis, saxis, smallaxis, bigaxis, reslen, longest_axis, i, j, d, ax, errval
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int daxis, saxis, smallaxis, bigaxis, resnd, longest_axis, i, j, d, ax, errval
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np.npy_intp sstride, dstride, longi, longstride
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int *local_indices
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int *innerloop_shape
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@ -565,36 +565,54 @@ cdef class trans_calculator:
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char *a_p
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char *b_p
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# Process the array shapes
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baseshape = np.broadcast.shape(r,theta,phi,r_ge_d)
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baseshape = np.broadcast(r,theta,phi,r_ge_d).shape # nope, does not work as needed
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'''
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cdef int r_orignd = r.ndim if hasattr(r, "ndim") else 0
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cdef int theta_orignd = theta.ndim if hasattr(theta, "ndim") else 0
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cdef int phi_orignd = phi.ndim if hasattr(phi, "ndim") else 0
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cdef int r_ge_d_orignd = r_ge_d.ndim if hasattr(r_ge_d, "__len__") else 0
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cdef int basend = max(r_orignd, theta_orignd, phi_orignd, r_ge_d_orignd)
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baseshape = list()
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for d in range(basend):
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baseshape.append(max(
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r.shape[d+r_orignd-basend] if d+r_orignd-basend >= 0 else 1,
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theta.shape[d+theta_orignd-basend] if d+theta_orignd-basend >= 0 else 1,
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phi.shape[d+phi_orignd-basend] if d+phi_orignd-basend >= 0 else 1,
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r_ge_d.shape[d+r_ge_d_orignd-basend] if d+r_ge_d_orignd-basend >= 0 else 1,
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))
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baseshape = tuple(baseshape)
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'''
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if not expand:
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reslen = len(baseshape)
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if reslen < 2:
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resnd = len(baseshape)
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if resnd < 2:
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raise ValueError('Translation matrix arrays must have at least 2 dimensions!')
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daxis = (reslen-2) if destaxis is None else destaxis
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saxis = (reslen-1) if srcaxis is None else srcaxis
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daxis = (resnd-2) if destaxis is None else destaxis
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saxis = (resnd-1) if srcaxis is None else srcaxis
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if daxis < 0:
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daxis = reslen + daxis
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daxis = resnd + daxis
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if saxis < 0:
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saxis = reslen + saxis
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if daxis < 0 or saxis < 0 or daxis >= reslen or saxis >= reslen or daxis == saxis:
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saxis = resnd + saxis
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if daxis < 0 or saxis < 0 or daxis >= resnd or saxis >= resnd or daxis == saxis:
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raise ValueError('invalid axes provided (destaxis = %d, srcaxis = %d, # of axes: %d'
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% (daxis, saxis, reslen))
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% (daxis, saxis, resnd))
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if baseshape[daxis] != 1 or baseshape[saxis] != 1:
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raise ValueError('dimension mismatch (input argument dimensions have to be 1 both at'
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'destaxis (==%d) and srcaxis (==%d) but are %d and %d' %
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(daxis, saxis, baseshape[daxis], baseshape[saxis]))
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resultshape = list(baseshape)
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else:
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reslen = len(baseshape)+2
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if destaxis is None:
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daxis = -2
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if srcaxis is None:
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saxis = -1
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resnd = len(baseshape)+2
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daxis = (resnd-2) if destaxis is None else destaxis
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saxis = (resnd-1) if srcaxis is None else srcaxis
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print(daxis)
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print(saxis)
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if daxis < 0:
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daxis = reslen + daxis
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daxis = resnd + daxis
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print(daxis)
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if saxis < 0:
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saxis = reslen + saxis
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if daxis < 0 or saxis < 0 or daxis >= reslen or saxis >= reslen or daxis == saxis:
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saxis = resnd + saxis
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print(saxis)
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if daxis < 0 or saxis < 0 or daxis >= resnd or saxis >= resnd or daxis == saxis:
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raise ValueError('invalid axes provided') # TODO better error formulation
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resultshape = list(baseshape)
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if daxis > saxis:
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@ -602,23 +620,26 @@ cdef class trans_calculator:
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bigaxis = daxis
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else:
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smallaxis = daxis
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bixagis = saxis
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bigaxis = saxis
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resultshape.insert(smallaxis,1)
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resultshape.insert(bigaxis,1)
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r = np.expand_dims(np.expand_dims(r.astype(np.float_, copy=False), smallaxis), bigaxis)
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theta = np.expand_dims(np.expand_dims(theta.astype(np.float_, copy=False), smallaxis), bigaxis)
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phi = np.expand_dims(np.expand_dims(phi.astype(np.float_, copy=False), smallaxis), bigaxis)
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r_ge_d = np.expand_dims(np.expand_dims(r_ge_d(np.bool_, copy=False), smallaxis), bigaxis)
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r_ge_d = np.expand_dims(np.expand_dims(r_ge_d.astype(np.bool_, copy=False), smallaxis), bigaxis)
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print(baseshape)
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print(len(baseshape), resnd,smallaxis, bigaxis)
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print(r.shape, theta.shape,phi.shape,r_ge_d.shape)
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longestaxis = 0
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longest_axis = 0
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# FIxME: the whole thing with longest_axis will fail if none is longer than 1
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for i in range(reslen):
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for i in range(resnd):
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if resultshape[i] > resultshape[longest_axis]:
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longestaxis = i
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innerloop_shape = <int *> malloc(reslen * sizeof(int))
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longest_axis = i
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innerloop_shape = <int *> malloc(resnd * sizeof(int))
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if innerloop_shape == NULL:
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abort()
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for i in range(reslen):
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for i in range(resnd):
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innerloop_shape[i] = resultshape[i]
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innerloop_shape[longest_axis] = 1 # longest axis will be iterated in the outer (parallelized) loop. Therefore, longest axis, together with saxis and daxis, will not be iterated in the inner loop
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resultshape[daxis] = self.c[0].nelem
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@ -634,20 +655,20 @@ cdef class trans_calculator:
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longstride = a.strides[longest_axis]
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# TODO write this in C (as a function) and parallelize there
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with nogil: #, parallel(): # FIXME rewrite this part in C
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local_indices = <int *> calloc(reslen, sizeof(int))
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local_indices = <int *> calloc(resnd, sizeof(int))
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if local_indices == NULL: abort()
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for longi in range(a.shape[longest_axis]): # outer loop (to be parallelized)
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# this might be done also in the inverse order, but this is more 'c-contiguous' way of incrementing the indices
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ax = reslen - 1
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ax = resnd - 1
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while ax >= 0:
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# calculate the correct index/pointer for each array used. This can be further optimized from O(reslen * total size of the result array) to O(total size of the result array), but fick that now
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# calculate the correct index/pointer for each array used. This can be further optimized from O(resnd * total size of the result array) to O(total size of the result array), but fick that now
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r_p = r_c.data + r_c.strides[longest_axis] * longi
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theta_p = theta_c.data + theta_c.strides[longest_axis] * longi
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phi_p = phi_c.data + phi_c.strides[longest_axis] * longi
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r_ge_d_p = r_ge_d_c.data + r_ge_d_c.strides[longest_axis] * longi
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a_p = a.data + a.strides[longest_axis] * longi
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b_p = b.data + b.strides[longest_axis] * longi
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for i in range(reslen):
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for i in range(resnd):
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if i == longest_axis: continue
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r_p += r_c.strides[i] * local_indices[i]
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theta_p += theta_c.strides[i] * local_indices[i]
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@ -664,14 +685,14 @@ cdef class trans_calculator:
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(<double*>r_p)[0], (<double*>theta_p)[0], (<double*>phi_p)[0], <int>((<np.npy_bool*>r_ge_d_p)[0]), J)
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if errval: abort()
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# increment the last index 'digit' (ax is now reslen-1; we don't have do-while loop in python)
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# increment the last index 'digit' (ax is now resnd-1; we don't have do-while loop in python)
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local_indices[ax] += 1
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while (local_indices[ax] == innerloop_shape[ax] and ax >= 0): # overflow to the next digit but stop when we reach below the last one
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local_indices[ax] = 0
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ax -= 1
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local_indices[ax] += 1
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if ax >= 0: # did not overflow, get back to the lowest index
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ax = reslen - 1
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ax = resnd - 1
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@ -684,27 +705,5 @@ cdef class trans_calculator:
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continue
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free(local_indices)
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free(innerloop_shape)
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return a, b
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# TODO make possible to access the attributes (to show normalization etc)
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