something already works
Former-commit-id: 9b1cfe39ae1453d26db40ad36d649b820d091ee4
This commit is contained in:
Marek Nečada
parent
261b6686bd
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161
qpms/qpms_c.pyx
161
qpms/qpms_c.pyx
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@ -1,6 +1,8 @@
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# cythonized functions here
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cimport numpy as np
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# Cythonized parts of QPMS here
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# -----------------------------
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import numpy as np
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cimport numpy as np
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cimport cython
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## Auxillary function for retrieving the "meshgrid-like" indices; inc. nmax
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@ -68,7 +70,158 @@ def get_y_mn_unsigned(int nmax):
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return(ymn_plus, ymn_minus)
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cdef int q_max(int m, int n, int mu, int nu):
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return min(n,nu,(n+nu-abs(m+mu)//2)
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return min(n,nu,(n+nu-abs(m+mu)//2))
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"""
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Now we generate our own universal functions to be used with numpy.
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Good way to see how this is done is to look at scipy/scipy/special/generate_ufuncs.py
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and scipy/scipy/special/generate_ufuncs.py
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In simple words, it works like this:
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- Let's have a single element function. This can be function which returns or a "subroutine".
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- Then we need a loop function; this is a wrapper that gets bunch of pointers from numpy and
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has to properly call the single element function.
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- From those two, we build a python object using PyUFunc_FromFuncAndData.
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* If the ufunc is supposed to work on different kinds of input/output types,
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then a pair of single-element and loop functions is o be provided for
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each combination of types. However, the single-element function can be reused if
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the corresponding loop functions do the proper casting.
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"""
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## as in scipy/special/_ufuncs_cxx.pyx
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##-------------------------------------
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#cdef extern from "numpy/ufuncobject.h":
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# int PyUFunc_getfperr() nogil
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#
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#cdef public int wrap_PyUFunc_getfperr() nogil:
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# """
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# Call PyUFunc_getfperr in a context where PyUFunc_API array is initialized;
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#
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# """
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# return PyUFunc_getfperr()
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#
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#cimport sf_error
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#-------------------------------------
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#cdef translation_coefficient_A(
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ctypedef double complex cdouble
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cdef void loop_D_iiiidddii_As_D_lllldddbl(char **args, np.npy_intp *dims, np.npy_intp *steps, void *data) nogil:
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cdef np.npy_intp i, n = dims[0]
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cdef void *func = (<void**>data)#[0]
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#cdef char *func_name= <char*>(<void**>data)[1] # i am not using this, nor have I saved func_name to data
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cdef char *ip0 = args[0]
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cdef char *ip1 = args[1]
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cdef char *ip2 = args[2]
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cdef char *ip3 = args[3]
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cdef char *ip4 = args[4]
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cdef char *ip5 = args[5]
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cdef char *ip6 = args[6]
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cdef char *ip7 = args[7]
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cdef char *ip8 = args[8]
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cdef char *op0 = args[9]
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cdef cdouble ov0
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for i in range(n): # iterating over dimensions
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ov0 = (<double complex(*)(int, int, int, int, double, double, double, int, int) nogil>func)(
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<int>(<np.npy_long*>ip0)[0],
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<int>(<np.npy_long*>ip1)[0],
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<int>(<np.npy_long*>ip2)[0],
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<int>(<np.npy_long*>ip3)[0],
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<double>(<np.npy_double*>ip4)[0],
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<double>(<np.npy_double*>ip5)[0],
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<double>(<np.npy_double*>ip6)[0],
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<int>(<np.npy_bool*>ip7)[0],
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<int>(<np.npy_long*>ip8)[0],
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)
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(<double *>op0)[0] = <double>ov0
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ip0 += steps[0]
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ip1 += steps[1]
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ip2 += steps[2]
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ip3 += steps[3]
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ip4 += steps[4]
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ip5 += steps[5]
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ip6 += steps[6]
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ip7 += steps[7]
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ip8 += steps[8]
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op0 += steps[9]
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# FIXME ERROR HANDLING!!! requires correct import and different data passed (see scipy's generated ufuncs)
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# sf_error.check_fpe(func_name)
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#cdef extern from "numpy/arrayobject.h":
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# cdef enum NPY_TYPES:
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# NPY_DOUBLE
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# NPY_CDOUBLE # complex double
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# NPY_LONG # int
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# ctypedef int npy_intp
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cdef extern from "translations.h":
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cdouble qpms_trans_single_A_Taylor_ext(int m, int n, int mu, int nu,
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double r, double th, double ph, int r_ge_d, int J) nogil
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cdouble qpms_trans_single_B_Taylor_ext(int m, int n, int mu, int nu,
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double r, double th, double ph, int r_ge_d, int J) nogil
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# Module initialisation
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# ---------------------
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np.import_array() # not sure whether this is really needed
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np.import_ufunc()
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# Arrays passed to PyUFunc_FromFuncAndData()
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# ------------------------------------------
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# BTW, aren't there anonymous arrays in cython?
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cdef np.PyUFuncGenericFunction loop_func[1]
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cdef char input_output_types[10]
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cdef void *elementwise_funcs_A[1]
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cdef void *elementwise_funcs_B[1]
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loop_func[0] = loop_D_iiiidddii_As_D_lllldddbl
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input_output_types[0] = np.NPY_LONG
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input_output_types[1] = np.NPY_LONG
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input_output_types[2] = np.NPY_LONG
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input_output_types[3] = np.NPY_LONG
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input_output_types[4] = np.NPY_DOUBLE
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input_output_types[5] = np.NPY_DOUBLE
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input_output_types[6] = np.NPY_DOUBLE
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input_output_types[7] = np.NPY_BOOL
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input_output_types[8] = np.NPY_LONG
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input_output_types[9] = np.NPY_CDOUBLE
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elementwise_funcs_A[0] = <void*> qpms_trans_single_A_Taylor_ext
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elementwise_funcs_B[0] = <void*> qpms_trans_single_B_Taylor_ext
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trans_A_Taylor = np.PyUFunc_FromFuncAndData(
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loop_func, # func
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elementwise_funcs_A, #data
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input_output_types, # types
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1, # ntypes: number of supported input types
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9, # nin: number of input args
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1, # nout: number of output args
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0, # identity element, unused
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"trans_A_Taylor", # name
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"""
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TODO computes the E-E or M-M translation coefficient in Taylor's normalisation
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""", # doc
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0 # unused, for backward compatibility of numpy c api
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)
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trans_B_Taylor = np.PyUFunc_FromFuncAndData(
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loop_func,
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elementwise_funcs_B,
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input_output_types,
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1, # number of supported input types
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9, # number of input args
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1, # number of output args
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0, # identity element, unused
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"trans_B_Taylor",
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"""
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TODO computes the E-E or M-M translation coefficient in Taylor's normalisation
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""",
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0 # unused
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)
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@ -160,5 +160,14 @@ complex double qpms_trans_single_B_Taylor(int m, int n, int mu, int nu, sph_t kd
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return (presum / prenormratio) * sum;
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}
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complex double qpms_trans_single_A_Taylor_ext(int m, int n, int mu, int nu,
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double kdlj_r, double kdlj_theta, double kdlj_phi, int r_ge_d, int J) {
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sph_t kdlj = {kdlj_r, kdlj_theta, kdlj_phi};
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return qpms_trans_single_A_Taylor(m,n,mu,nu,kdlj,r_ge_d,J);
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}
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complex double qpms_trans_single_B_Taylor_ext(int m, int n, int mu, int nu,
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double kdlj_r, double kdlj_theta, double kdlj_phi, int r_ge_d, int J) {
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sph_t kdlj = {kdlj_r, kdlj_theta, kdlj_phi};
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return qpms_trans_single_B_Taylor(m,n,mu,nu,kdlj,r_ge_d,J);
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}
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@ -23,4 +23,10 @@ complex double qpms_trans_single_A_Taylor(int m, int n, int mu, int nu, sph_t kd
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complex double qpms_trans_single_B_Taylor(int m, int n, int mu, int nu, sph_t kdlj,
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bool r_ge_d, qpms_bessel_t J);
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complex double qpms_trans_single_A_Taylor_ext(int m, int n, int mu, int nu, double kdlj_r,
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double kdlj_th, double kdlj_phi, int r_ge_d, int J);
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complex double qpms_trans_single_B_Taylor_ext(int m, int n, int mu, int nu, double kdlj_r,
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double kdlj_th, double kdlj_phi, int r_ge_d, int J);
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#endif // QPMS_TRANSLATIONS_H
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18
setup.py
18
setup.py
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@ -8,11 +8,25 @@ from distutils.extension import Extension
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# m = sys.modules['setuptools.extension']
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# m.Extension.__dict__ = m._Extension.__dict__
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# TODO CHECK THIS OUT http://stackoverflow.com/questions/4056657/what-is-the-easiest-way-to-make-an-optional-c-extension-for-a-python-package
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# also this: https://docs.python.org/2/extending/building.html
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import os
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print("You might want to add additional library path to LD_LIBRARY_PATH (especially if you are not using"
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" GNU GSL in your system library path) and if import fails. ")
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print(os.environ['LD_LIBRARY_PATH'].split(':'))
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qpms_c = Extension('qpms_c',
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sources = ['qpms/qpms_c.pyx'])
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sources = ['qpms/qpms_c.pyx','qpms/gaunt.c',#'qpms/gaunt.h','qpms/vectors.h','qpms/translations.h',
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# FIXME http://stackoverflow.com/questions/4259170/python-setup-script-extensions-how-do-you-include-a-h-file
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'qpms/translations.c'],
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extra_compile_args=['-std=c99','-ggdb','-O3'],
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libraries=['gsl', 'blas'],
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runtime_library_dirs=os.environ['LD_LIBRARY_PATH'].split(':')
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)
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setup(name='qpms',
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version = "0.1.9",
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version = "0.2.0",
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packages=['qpms'],
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# setup_requires=['setuptools_cython'],
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install_requires=['cython>=0.21','quaternion','spherical_functions','py_gmm'],
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