[14de349] | 1 | __all__ = ["make_opencl"] |
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| 2 | |
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| 3 | import os.path |
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| 4 | |
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| 5 | import numpy as np |
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| 6 | |
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| 7 | from .jsonutil import relaxed_loads |
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| 8 | |
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| 9 | F64 = np.dtype('float64') |
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| 10 | F32 = np.dtype('float32') |
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| 11 | |
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[ce27e21] | 12 | # Scale and background, which are parameters common to every form factor |
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| 13 | COMMON_PARAMETERS = [ |
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| 14 | [ "scale", "", 1, [0, np.inf], "", "Source intensity" ], |
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| 15 | [ "background", "1/cm", 0, [0, np.inf], "", "Source background" ], |
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| 16 | ] |
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| 17 | |
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| 18 | |
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[14de349] | 19 | # Conversion from units defined in the parameter table for each model |
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| 20 | # to units displayed in the sphinx documentation. |
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| 21 | RST_UNITS = { |
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| 22 | "Ang": "|Ang|", |
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| 23 | "1/Ang^2": "|Ang^-2|", |
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| 24 | "1e-6/Ang^2": "|1e-6Ang^-2|", |
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| 25 | "degrees": "degree", |
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| 26 | "1/cm": "|cm^-1|", |
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| 27 | "": "None", |
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| 28 | } |
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| 29 | |
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| 30 | # Headers for the parameters tables in th sphinx documentation |
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| 31 | PARTABLE_HEADERS = [ |
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| 32 | "Parameter name", |
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| 33 | "Units", |
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| 34 | "Default value", |
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| 35 | ] |
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| 36 | |
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| 37 | PARTABLE_VALUE_WIDTH = 10 |
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| 38 | |
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| 39 | # Header included before every kernel. |
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| 40 | # This makes sure that the appropriate math constants are defined, and |
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| 41 | KERNEL_HEADER = """\ |
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| 42 | // GENERATED CODE --- DO NOT EDIT --- |
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| 43 | // Code is produced by sasmodels.gen from sasmodels/models/MODEL.c |
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| 44 | |
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| 45 | #ifdef __OPENCL_VERSION__ |
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| 46 | # define USE_OPENCL |
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| 47 | #endif |
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| 48 | |
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| 49 | // If opencl is not available, then we are compiling a C function |
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| 50 | // Note: if using a C++ compiler, then define kernel as extern "C" |
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| 51 | #ifndef USE_OPENCL |
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| 52 | # include <math.h> |
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| 53 | # define REAL(x) (x) |
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| 54 | # ifndef real |
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| 55 | # define real double |
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| 56 | # endif |
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| 57 | # define global |
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| 58 | # define local |
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| 59 | # define constant const |
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| 60 | # define kernel |
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| 61 | # define SINCOS(angle,svar,cvar) do {svar=sin(angle);cvar=cos(angle);} while (0) |
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[ce27e21] | 62 | # define powr(a,b) pow(a,b) |
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[14de349] | 63 | #else |
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| 64 | # ifdef USE_SINCOS |
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| 65 | # define SINCOS(angle,svar,cvar) svar=sincos(angle,&cvar) |
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| 66 | # else |
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| 67 | # define SINCOS(angle,svar,cvar) do {svar=sin(angle);cvar=cos(angle);} while (0) |
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| 68 | # endif |
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| 69 | #endif |
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| 70 | |
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| 71 | // Standard mathematical constants, prefixed with M_: |
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| 72 | // E, LOG2E, LOG10E, LN2, LN10, PI, PI_2, PI_4, 1_PI, 2_PI, |
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| 73 | // 2_SQRTPI, SQRT2, SQRT1_2 |
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| 74 | // OpenCL defines M_constant_F for float constants, and nothing if double |
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| 75 | // is not enabled on the card, which is why these constants may be missing |
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| 76 | #ifndef M_PI |
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| 77 | # define M_PI REAL(3.141592653589793) |
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| 78 | #endif |
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| 79 | #ifndef M_PI_2 |
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| 80 | # define M_PI_2 REAL(1.570796326794897) |
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| 81 | #endif |
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| 82 | #ifndef M_PI_4 |
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| 83 | # define M_PI_4 REAL(0.7853981633974483) |
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| 84 | #endif |
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| 85 | |
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| 86 | // Non-standard pi/180, used for converting between degrees and radians |
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| 87 | #ifndef M_PI_180 |
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| 88 | # define M_PI_180 REAL(0.017453292519943295) |
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| 89 | #endif |
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| 90 | """ |
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| 91 | |
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| 92 | |
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| 93 | # The I(q) kernel and the I(qx, qy) kernel have one and two q parameters |
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| 94 | # respectively, so the template builder will need to do extra work to |
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| 95 | # declare, initialize and pass the q parameters. |
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[ce27e21] | 96 | KERNEL_1D = { |
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[14de349] | 97 | 'fn': "Iq", |
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| 98 | 'q_par_decl': "global const real *q,", |
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| 99 | 'qinit': "const real qi = q[i];", |
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| 100 | 'qcall': "qi", |
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| 101 | } |
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| 102 | |
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[ce27e21] | 103 | KERNEL_2D = { |
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[14de349] | 104 | 'fn': "Iqxy", |
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| 105 | 'q_par_decl': "global const real *qx,\n global const real *qy,", |
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| 106 | 'qinit': "const real qxi = qx[i];\n const real qyi = qy[i];", |
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| 107 | 'qcall': "qxi, qyi", |
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| 108 | } |
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| 109 | |
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| 110 | # Generic kernel template for opencl/openmp. |
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| 111 | # This defines the opencl kernel that is available to the host. The same |
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| 112 | # structure is used for Iq and Iqxy kernels, so extra flexibility is needed |
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| 113 | # for q parameters. The polydispersity loop is built elsewhere and |
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| 114 | # substituted into this template. |
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| 115 | KERNEL_TEMPLATE = """\ |
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| 116 | kernel void %(name)s( |
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| 117 | %(q_par_decl)s |
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| 118 | global real *result, |
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| 119 | #ifdef USE_OPENCL |
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| 120 | global real *loops_g, |
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| 121 | #else |
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| 122 | const int Nq, |
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| 123 | #endif |
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| 124 | local real *loops, |
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| 125 | const real cutoff, |
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| 126 | %(par_decl)s |
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| 127 | ) |
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| 128 | { |
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| 129 | #ifdef USE_OPENCL |
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| 130 | // copy loops info to local memory |
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| 131 | event_t e = async_work_group_copy(loops, loops_g, (%(pd_length)s)*2, 0); |
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| 132 | wait_group_events(1, &e); |
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| 133 | |
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| 134 | int i = get_global_id(0); |
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| 135 | int Nq = get_global_size(0); |
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| 136 | #endif |
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| 137 | |
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| 138 | #ifdef USE_OPENCL |
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| 139 | if (i < Nq) |
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| 140 | #else |
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| 141 | #pragma omp parallel for |
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| 142 | for (int i=0; i < Nq; i++) |
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| 143 | #endif |
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| 144 | { |
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| 145 | %(qinit)s |
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| 146 | real ret=REAL(0.0), norm=REAL(0.0); |
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| 147 | real vol=REAL(0.0), norm_vol=REAL(0.0); |
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| 148 | %(loops)s |
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| 149 | if (vol*norm_vol != REAL(0.0)) { |
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| 150 | ret *= norm_vol/vol; |
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| 151 | } |
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| 152 | result[i] = scale*ret/norm+background; |
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| 153 | } |
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| 154 | } |
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| 155 | """ |
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| 156 | |
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| 157 | # Polydispersity loop level. |
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| 158 | # This pulls the parameter value and weight from the looping vector in order |
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| 159 | # in preperation for a nested loop. |
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| 160 | LOOP_OPEN="""\ |
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| 161 | for (int %(name)s_i=0; %(name)s_i < N%(name)s; %(name)s_i++) { |
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| 162 | const real %(name)s = loops[2*(%(name)s_i%(offset)s)]; |
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| 163 | const real %(name)s_w = loops[2*(%(name)s_i%(offset)s)+1];""" |
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| 164 | |
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| 165 | # Polydispersity loop body. |
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| 166 | # This computes the weight, and if it is sufficient, calls the scattering |
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| 167 | # function and adds it to the total. If there is a volume normalization, |
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| 168 | # it will also be added here. |
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| 169 | LOOP_BODY="""\ |
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| 170 | const real weight = %(weight_product)s; |
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| 171 | if (weight > cutoff) { |
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| 172 | ret += weight*%(fn)s(%(qcall)s, %(pcall)s); |
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| 173 | norm += weight; |
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| 174 | %(volume_norm)s |
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| 175 | }""" |
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| 176 | |
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| 177 | # Volume normalization. |
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| 178 | # If there are "volume" polydispersity parameters, then these will be used |
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[ce27e21] | 179 | # to call the form_volume function from the user supplied kernel, and accumulate |
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[14de349] | 180 | # a normalized weight. |
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| 181 | VOLUME_NORM="""const real vol_weight = %(weight)s; |
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[ce27e21] | 182 | vol += vol_weight*form_volume(%(pars)s); |
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[14de349] | 183 | norm_vol += vol_weight;""" |
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| 184 | |
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[ce27e21] | 185 | |
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[14de349] | 186 | def indent(s, depth): |
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| 187 | """ |
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| 188 | Indent a string of text with *depth* additional spaces on each line. |
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| 189 | """ |
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| 190 | spaces = " "*depth |
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| 191 | sep = "\n"+spaces |
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| 192 | return spaces + sep.join(s.split("\n")) |
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| 193 | |
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| 194 | |
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[ce27e21] | 195 | def kernel_name(info, is_2D): |
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| 196 | return info['name'] + "_" + ("Iqxy" if is_2D else "Iq") |
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| 197 | |
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| 198 | |
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| 199 | def make_kernel(info, is_2D): |
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[14de349] | 200 | """ |
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| 201 | Build a kernel call from metadata supplied by the user. |
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| 202 | |
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[ce27e21] | 203 | *info* is the json object defined in the kernel file. |
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[14de349] | 204 | |
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| 205 | *form* is either "Iq" or "Iqxy". |
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| 206 | |
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| 207 | This does not create a complete OpenCL kernel source, only the top |
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| 208 | level kernel call with polydispersity and a call to the appropriate |
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| 209 | Iq or Iqxy function. |
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| 210 | """ |
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| 211 | |
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| 212 | # If we are building the Iqxy kernel, we need to propagate qx,qy |
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| 213 | # parameters, otherwise we can |
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[ce27e21] | 214 | dim = "2d" if is_2D else "1d" |
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| 215 | fixed_pars = info['partype']['fixed-'+dim] |
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| 216 | pd_pars = info['partype']['pd-'+dim] |
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| 217 | vol_pars = info['partype']['volume'] |
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| 218 | q_pars = KERNEL_2D if is_2D else KERNEL_1D |
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[14de349] | 219 | |
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[ce27e21] | 220 | # Build polydispersity loops |
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[14de349] | 221 | depth = 4 |
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| 222 | offset = "" |
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| 223 | loop_head = [] |
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| 224 | loop_end = [] |
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[ce27e21] | 225 | for name in pd_pars: |
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[14de349] | 226 | subst = { 'name': name, 'offset': offset } |
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| 227 | loop_head.append(indent(LOOP_OPEN%subst, depth)) |
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| 228 | loop_end.insert(0, (" "*depth) + "}") |
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| 229 | offset += '+N'+name |
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| 230 | depth += 2 |
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| 231 | |
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| 232 | # The volume parameters in the inner loop are used to call the volume() |
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| 233 | # function in the kernel, with the parameters defined in vol_pars and the |
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| 234 | # weight product defined in weight. If there are no volume parameters, |
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| 235 | # then there will be no volume normalization. |
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| 236 | if vol_pars: |
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| 237 | subst = { |
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| 238 | 'weight': "*".join(p+"_w" for p in vol_pars), |
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| 239 | 'pars': ", ".join(vol_pars), |
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| 240 | } |
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| 241 | volume_norm = VOLUME_NORM%subst |
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| 242 | else: |
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| 243 | volume_norm = "" |
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| 244 | |
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| 245 | # Define the inner loop function call |
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[ce27e21] | 246 | # The parameters to the f(q,p1,p2...) call should occur in the same |
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| 247 | # order as given in the parameter info structure. This may be different |
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| 248 | # from the parameter order in the call to the kernel since the kernel |
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| 249 | # call places all fixed parameters before all polydisperse parameters. |
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| 250 | fq_pars = [p[0] for p in info['parameters'][len(COMMON_PARAMETERS):] |
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| 251 | if p[0] in set(fixed_pars+pd_pars)] |
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[14de349] | 252 | subst = { |
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| 253 | 'weight_product': "*".join(p+"_w" for p in pd_pars), |
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| 254 | 'volume_norm': volume_norm, |
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[ce27e21] | 255 | 'fn': q_pars['fn'], |
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| 256 | 'qcall': q_pars['qcall'], |
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| 257 | 'pcall': ", ".join(fq_pars), # skip scale and background |
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[14de349] | 258 | } |
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| 259 | loop_body = [indent(LOOP_BODY%subst, depth)] |
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| 260 | loops = "\n".join(loop_head+loop_body+loop_end) |
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| 261 | |
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| 262 | # declarations for non-pd followed by pd pars |
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| 263 | # e.g., |
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| 264 | # const real sld, |
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| 265 | # const int Nradius |
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| 266 | fixed_par_decl = ",\n ".join("const real %s"%p for p in fixed_pars) |
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| 267 | pd_par_decl = ",\n ".join("const int N%s"%p for p in pd_pars) |
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| 268 | if fixed_par_decl and pd_par_decl: |
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| 269 | par_decl = ",\n ".join((fixed_par_decl, pd_par_decl)) |
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| 270 | elif fixed_par_decl: |
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| 271 | par_decl = fixed_par_decl |
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| 272 | else: |
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| 273 | par_decl = pd_par_decl |
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| 274 | |
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| 275 | # Finally, put the pieces together in the kernel. |
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| 276 | subst = { |
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| 277 | # kernel name is, e.g., cylinder_Iq |
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[ce27e21] | 278 | 'name': kernel_name(info, is_2D), |
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[14de349] | 279 | # to declare, e.g., global real q[], |
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[ce27e21] | 280 | 'q_par_decl': q_pars['q_par_decl'], |
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[14de349] | 281 | # to declare, e.g., real sld, int Nradius, int Nlength |
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| 282 | 'par_decl': par_decl, |
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| 283 | # to copy global to local pd pars we need, e.g., Nradius+Nlength |
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| 284 | 'pd_length': "+".join('N'+p for p in pd_pars), |
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| 285 | # the q initializers, e.g., real qi = q[i]; |
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[ce27e21] | 286 | 'qinit': q_pars['qinit'], |
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[14de349] | 287 | # the actual polydispersity loop |
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| 288 | 'loops': loops, |
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| 289 | } |
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| 290 | kernel = KERNEL_TEMPLATE%subst |
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| 291 | return kernel |
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| 292 | |
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[ce27e21] | 293 | def make_partable(info): |
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| 294 | pars = info['parameters'] |
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[14de349] | 295 | column_widths = [ |
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| 296 | max(len(p[0]) for p in pars), |
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| 297 | max(len(RST_UNITS[p[1]]) for p in pars), |
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| 298 | PARTABLE_VALUE_WIDTH, |
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| 299 | ] |
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| 300 | column_widths = [max(w, len(h)) |
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| 301 | for w,h in zip(column_widths, PARTABLE_HEADERS)] |
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| 302 | |
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| 303 | sep = " ".join("="*w for w in column_widths) |
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| 304 | lines = [ |
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| 305 | sep, |
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| 306 | " ".join("%-*s"%(w,h) for w,h in zip(column_widths, PARTABLE_HEADERS)), |
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| 307 | sep, |
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| 308 | ] |
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| 309 | for p in pars: |
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| 310 | lines.append(" ".join([ |
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| 311 | "%-*s"%(column_widths[0],p[0]), |
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| 312 | "%-*s"%(column_widths[1],RST_UNITS[p[1]]), |
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| 313 | "%*g"%(column_widths[2],p[2]), |
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| 314 | ])) |
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| 315 | lines.append(sep) |
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| 316 | return "\n".join(lines) |
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| 317 | |
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[ce27e21] | 318 | def make_doc(kernelfile, info, doc): |
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| 319 | doc = doc%{'parameters': make_partable(info)} |
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[14de349] | 320 | return doc |
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| 321 | |
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[ce27e21] | 322 | def make_model(kernelfile, info, source): |
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| 323 | kernel_Iq = make_kernel(info, is_2D=False) |
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| 324 | kernel_Iqxy = make_kernel(info, is_2D=True) |
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[14de349] | 325 | path = os.path.dirname(kernelfile) |
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[ce27e21] | 326 | extra = [open("%s/%s"%(path,f)).read() for f in info['include']] |
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[14de349] | 327 | kernel = "\n\n".join([KERNEL_HEADER]+extra+[source, kernel_Iq, kernel_Iqxy]) |
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| 328 | return kernel |
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| 329 | |
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| 330 | def parse_file(kernelfile): |
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| 331 | source = open(kernelfile).read() |
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| 332 | |
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| 333 | # select parameters out of the source file |
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| 334 | parts = source.split("PARAMETERS") |
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| 335 | if len(parts) != 3: |
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| 336 | raise ValueError("PARAMETERS block missing from %r"%kernelfile) |
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[ce27e21] | 337 | info_source = parts[1].strip() |
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[14de349] | 338 | try: |
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[ce27e21] | 339 | info = relaxed_loads(info_source) |
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[14de349] | 340 | except: |
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| 341 | print "in json text:" |
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| 342 | print "\n".join("%2d: %s"%(i+1,s) |
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[ce27e21] | 343 | for i,s in enumerate(info_source.split('\n'))) |
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[14de349] | 344 | raise |
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| 345 | #raise ValueError("PARAMETERS block could not be parsed from %r"%kernelfile) |
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| 346 | |
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| 347 | # select documentation out of the source file |
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| 348 | parts = source.split("DOCUMENTATION") |
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| 349 | if len(parts) == 3: |
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[ce27e21] | 350 | doc = make_doc(kernelfile, info, parts[1].strip()) |
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[14de349] | 351 | elif len(parts) == 1: |
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| 352 | raise ValueError("DOCUMENTATION block is missing from %r"%kernelfile) |
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| 353 | else: |
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| 354 | raise ValueError("DOCUMENTATION block incorrect from %r"%kernelfile) |
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| 355 | |
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[ce27e21] | 356 | return source, info, doc |
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[14de349] | 357 | |
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[ce27e21] | 358 | def categorize_parameters(pars): |
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[14de349] | 359 | """ |
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[ce27e21] | 360 | Build parameter categories out of the the parameter definitions. |
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| 361 | |
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| 362 | Returns a dictionary of categories. |
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| 363 | |
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| 364 | The function call sequence consists of q inputs and the return vector, |
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| 365 | followed by the loop value/weight vector, followed by the values for |
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| 366 | the non-polydisperse parameters, followed by the lengths of the |
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| 367 | polydispersity loops. To construct the call for 1D models, the |
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| 368 | categories *fixed-1d* and *pd-1d* list the names of the parameters |
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| 369 | of the non-polydisperse and the polydisperse parameters respectively. |
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| 370 | Similarly, *fixed-2d* and *pd-2d* provide parameter names for 2D models. |
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| 371 | The *pd-rel* category is a set of those parameters which give |
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| 372 | polydispersitiy as a portion of the value (so a 10% length dispersity |
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| 373 | would use a polydispersity value of 0.1) rather than absolute |
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| 374 | dispersity such as an angle plus or minus 15 degrees. |
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| 375 | |
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| 376 | The *volume* category lists the volume parameters in order for calls |
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| 377 | to volume within the kernel (used for volume normalization) and for |
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| 378 | calls to ER and VR for effective radius and volume ratio respectively. |
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| 379 | |
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| 380 | The *orientation* and *magnetic* categories list the orientation and |
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| 381 | magnetic parameters. These are used by the sasview interface. The |
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| 382 | blank category is for parameters such as scale which don't have any |
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| 383 | other marking. |
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[14de349] | 384 | """ |
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[ce27e21] | 385 | partype = { |
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| 386 | 'volume': [], 'orientation': [], 'magnetic': [], '': [], |
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| 387 | 'fixed-1d': [], 'fixed-2d': [], 'pd-1d': [], 'pd-2d': [], |
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| 388 | 'pd-rel': set(), |
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[14de349] | 389 | } |
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| 390 | |
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[ce27e21] | 391 | for p in pars: |
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| 392 | name,ptype = p[0],p[4] |
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| 393 | if ptype == 'volume': |
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| 394 | partype['pd-1d'].append(name) |
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| 395 | partype['pd-2d'].append(name) |
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| 396 | partype['pd-rel'].add(name) |
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| 397 | elif ptype == 'magnetic': |
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| 398 | partype['fixed-2d'].append(name) |
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| 399 | elif ptype == 'orientation': |
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| 400 | partype['pd-2d'].append(name) |
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| 401 | elif ptype == '': |
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| 402 | partype['fixed-1d'].append(name) |
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| 403 | partype['fixed-2d'].append(name) |
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| 404 | else: |
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| 405 | raise ValueError("unknown parameter type %r"%ptype) |
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| 406 | partype[ptype].append(name) |
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[14de349] | 407 | |
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[ce27e21] | 408 | return partype |
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[14de349] | 409 | |
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[ce27e21] | 410 | def make(kernelfile): |
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[14de349] | 411 | """ |
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[ce27e21] | 412 | Build an OpenCL function from the source in *kernelfile*. |
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[14de349] | 413 | |
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[ce27e21] | 414 | The kernel file needs to define metadata about the parameters. This |
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| 415 | will be a JSON definition containing |
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[14de349] | 416 | """ |
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[ce27e21] | 417 | #print kernelfile |
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| 418 | source, info, doc = parse_file(kernelfile) |
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| 419 | info['filename'] = kernelfile |
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| 420 | info['parameters'] = COMMON_PARAMETERS + info['parameters'] |
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| 421 | info['partype'] = categorize_parameters(info['parameters']) |
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| 422 | info['limits'] = dict((p[0],p[3]) for p in info['parameters']) |
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| 423 | doc = make_doc(kernelfile, info, doc) |
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| 424 | model = make_model(kernelfile, info, source) |
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| 425 | return model, info, doc |
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[14de349] | 426 | |
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| 427 | |
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| 428 | def demo_time(): |
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| 429 | import datetime |
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| 430 | tic = datetime.datetime.now() |
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| 431 | toc = lambda: (datetime.datetime.now()-tic).total_seconds() |
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| 432 | path = os.path.dirname("__file__") |
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| 433 | doc, c = make_model(os.path.join(path, "models", "cylinder.c")) |
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| 434 | print "time:",toc() |
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| 435 | |
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| 436 | def demo(): |
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| 437 | from os.path import join as joinpath, dirname |
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[ce27e21] | 438 | c, info, doc = make_model(joinpath(dirname(__file__), "models", "cylinder.c")) |
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[14de349] | 439 | #print doc |
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| 440 | #print c |
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| 441 | |
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| 442 | if __name__ == "__main__": |
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| 443 | demo() |
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