1 | /************************************************************************* |
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2 | Copyright (c) 2005-2007, Sergey Bochkanov (ALGLIB project). |
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3 | |
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4 | Redistribution and use in source and binary forms, with or without |
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5 | modification, are permitted provided that the following conditions are |
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6 | met: |
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7 | |
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8 | - Redistributions of source code must retain the above copyright |
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9 | notice, this list of conditions and the following disclaimer. |
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10 | |
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11 | - Redistributions in binary form must reproduce the above copyright |
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12 | notice, this list of conditions and the following disclaimer listed |
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13 | in this license in the documentation and/or other materials |
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14 | provided with the distribution. |
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15 | |
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16 | - Neither the name of the copyright holders nor the names of its |
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17 | contributors may be used to endorse or promote products derived from |
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18 | this software without specific prior written permission. |
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19 | |
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20 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
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21 | "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
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22 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
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23 | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT |
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24 | OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, |
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25 | SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT |
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26 | LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, |
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27 | DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY |
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28 | THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
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29 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
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30 | OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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31 | *************************************************************************/ |
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32 | |
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33 | #ifndef _blas_h |
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34 | #define _blas_h |
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35 | |
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36 | #include "ap.h" |
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37 | #include "amp.h" |
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38 | namespace blas |
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39 | { |
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40 | template<unsigned int Precision> |
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41 | amp::ampf<Precision> vectornorm2(const ap::template_1d_array< amp::ampf<Precision> >& x, |
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42 | int i1, |
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43 | int i2); |
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44 | template<unsigned int Precision> |
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45 | int vectoridxabsmax(const ap::template_1d_array< amp::ampf<Precision> >& x, |
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46 | int i1, |
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47 | int i2); |
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48 | template<unsigned int Precision> |
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49 | int columnidxabsmax(const ap::template_2d_array< amp::ampf<Precision> >& x, |
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50 | int i1, |
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51 | int i2, |
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52 | int j); |
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53 | template<unsigned int Precision> |
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54 | int rowidxabsmax(const ap::template_2d_array< amp::ampf<Precision> >& x, |
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55 | int j1, |
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56 | int j2, |
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57 | int i); |
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58 | template<unsigned int Precision> |
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59 | amp::ampf<Precision> upperhessenberg1norm(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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60 | int i1, |
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61 | int i2, |
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62 | int j1, |
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63 | int j2, |
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64 | ap::template_1d_array< amp::ampf<Precision> >& work); |
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65 | template<unsigned int Precision> |
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66 | void copymatrix(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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67 | int is1, |
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68 | int is2, |
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69 | int js1, |
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70 | int js2, |
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71 | ap::template_2d_array< amp::ampf<Precision> >& b, |
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72 | int id1, |
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73 | int id2, |
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74 | int jd1, |
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75 | int jd2); |
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76 | template<unsigned int Precision> |
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77 | void inplacetranspose(ap::template_2d_array< amp::ampf<Precision> >& a, |
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78 | int i1, |
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79 | int i2, |
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80 | int j1, |
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81 | int j2, |
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82 | ap::template_1d_array< amp::ampf<Precision> >& work); |
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83 | template<unsigned int Precision> |
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84 | void copyandtranspose(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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85 | int is1, |
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86 | int is2, |
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87 | int js1, |
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88 | int js2, |
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89 | ap::template_2d_array< amp::ampf<Precision> >& b, |
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90 | int id1, |
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91 | int id2, |
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92 | int jd1, |
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93 | int jd2); |
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94 | template<unsigned int Precision> |
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95 | void matrixvectormultiply(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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96 | int i1, |
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97 | int i2, |
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98 | int j1, |
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99 | int j2, |
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100 | bool trans, |
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101 | const ap::template_1d_array< amp::ampf<Precision> >& x, |
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102 | int ix1, |
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103 | int ix2, |
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104 | amp::ampf<Precision> alpha, |
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105 | ap::template_1d_array< amp::ampf<Precision> >& y, |
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106 | int iy1, |
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107 | int iy2, |
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108 | amp::ampf<Precision> beta); |
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109 | template<unsigned int Precision> |
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110 | amp::ampf<Precision> pythag2(amp::ampf<Precision> x, |
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111 | amp::ampf<Precision> y); |
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112 | template<unsigned int Precision> |
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113 | void matrixmatrixmultiply(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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114 | int ai1, |
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115 | int ai2, |
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116 | int aj1, |
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117 | int aj2, |
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118 | bool transa, |
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119 | const ap::template_2d_array< amp::ampf<Precision> >& b, |
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120 | int bi1, |
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121 | int bi2, |
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122 | int bj1, |
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123 | int bj2, |
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124 | bool transb, |
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125 | amp::ampf<Precision> alpha, |
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126 | ap::template_2d_array< amp::ampf<Precision> >& c, |
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127 | int ci1, |
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128 | int ci2, |
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129 | int cj1, |
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130 | int cj2, |
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131 | amp::ampf<Precision> beta, |
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132 | ap::template_1d_array< amp::ampf<Precision> >& work); |
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133 | |
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134 | |
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135 | template<unsigned int Precision> |
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136 | amp::ampf<Precision> vectornorm2(const ap::template_1d_array< amp::ampf<Precision> >& x, |
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137 | int i1, |
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138 | int i2) |
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139 | { |
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140 | amp::ampf<Precision> result; |
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141 | int n; |
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142 | int ix; |
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143 | amp::ampf<Precision> absxi; |
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144 | amp::ampf<Precision> scl; |
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145 | amp::ampf<Precision> ssq; |
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146 | |
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147 | |
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148 | n = i2-i1+1; |
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149 | if( n<1 ) |
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150 | { |
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151 | result = 0; |
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152 | return result; |
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153 | } |
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154 | if( n==1 ) |
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155 | { |
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156 | result = amp::abs<Precision>(x(i1)); |
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157 | return result; |
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158 | } |
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159 | scl = 0; |
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160 | ssq = 1; |
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161 | for(ix=i1; ix<=i2; ix++) |
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162 | { |
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163 | if( x(ix)!=0 ) |
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164 | { |
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165 | absxi = amp::abs<Precision>(x(ix)); |
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166 | if( scl<absxi ) |
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167 | { |
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168 | ssq = 1+ssq*amp::sqr<Precision>(scl/absxi); |
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169 | scl = absxi; |
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170 | } |
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171 | else |
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172 | { |
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173 | ssq = ssq+amp::sqr<Precision>(absxi/scl); |
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174 | } |
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175 | } |
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176 | } |
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177 | result = scl*amp::sqrt<Precision>(ssq); |
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178 | return result; |
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179 | } |
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180 | |
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181 | |
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182 | template<unsigned int Precision> |
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183 | int vectoridxabsmax(const ap::template_1d_array< amp::ampf<Precision> >& x, |
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184 | int i1, |
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185 | int i2) |
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186 | { |
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187 | int result; |
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188 | int i; |
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189 | amp::ampf<Precision> a; |
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190 | |
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191 | |
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192 | result = i1; |
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193 | a = amp::abs<Precision>(x(result)); |
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194 | for(i=i1+1; i<=i2; i++) |
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195 | { |
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196 | if( amp::abs<Precision>(x(i))>amp::abs<Precision>(x(result)) ) |
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197 | { |
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198 | result = i; |
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199 | } |
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200 | } |
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201 | return result; |
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202 | } |
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203 | |
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204 | |
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205 | template<unsigned int Precision> |
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206 | int columnidxabsmax(const ap::template_2d_array< amp::ampf<Precision> >& x, |
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207 | int i1, |
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208 | int i2, |
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209 | int j) |
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210 | { |
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211 | int result; |
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212 | int i; |
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213 | amp::ampf<Precision> a; |
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214 | |
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215 | |
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216 | result = i1; |
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217 | a = amp::abs<Precision>(x(result,j)); |
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218 | for(i=i1+1; i<=i2; i++) |
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219 | { |
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220 | if( amp::abs<Precision>(x(i,j))>amp::abs<Precision>(x(result,j)) ) |
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221 | { |
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222 | result = i; |
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223 | } |
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224 | } |
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225 | return result; |
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226 | } |
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227 | |
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228 | |
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229 | template<unsigned int Precision> |
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230 | int rowidxabsmax(const ap::template_2d_array< amp::ampf<Precision> >& x, |
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231 | int j1, |
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232 | int j2, |
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233 | int i) |
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234 | { |
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235 | int result; |
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236 | int j; |
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237 | amp::ampf<Precision> a; |
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238 | |
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239 | |
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240 | result = j1; |
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241 | a = amp::abs<Precision>(x(i,result)); |
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242 | for(j=j1+1; j<=j2; j++) |
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243 | { |
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244 | if( amp::abs<Precision>(x(i,j))>amp::abs<Precision>(x(i,result)) ) |
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245 | { |
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246 | result = j; |
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247 | } |
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248 | } |
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249 | return result; |
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250 | } |
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251 | |
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252 | |
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253 | template<unsigned int Precision> |
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254 | amp::ampf<Precision> upperhessenberg1norm(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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255 | int i1, |
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256 | int i2, |
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257 | int j1, |
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258 | int j2, |
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259 | ap::template_1d_array< amp::ampf<Precision> >& work) |
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260 | { |
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261 | amp::ampf<Precision> result; |
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262 | int i; |
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263 | int j; |
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264 | |
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265 | |
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266 | ap::ap_error::make_assertion(i2-i1==j2-j1); |
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267 | for(j=j1; j<=j2; j++) |
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268 | { |
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269 | work(j) = 0; |
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270 | } |
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271 | for(i=i1; i<=i2; i++) |
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272 | { |
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273 | for(j=ap::maxint(j1, j1+i-i1-1); j<=j2; j++) |
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274 | { |
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275 | work(j) = work(j)+amp::abs<Precision>(a(i,j)); |
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276 | } |
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277 | } |
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278 | result = 0; |
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279 | for(j=j1; j<=j2; j++) |
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280 | { |
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281 | result = amp::maximum<Precision>(result, work(j)); |
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282 | } |
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283 | return result; |
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284 | } |
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285 | |
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286 | |
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287 | template<unsigned int Precision> |
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288 | void copymatrix(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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289 | int is1, |
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290 | int is2, |
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291 | int js1, |
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292 | int js2, |
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293 | ap::template_2d_array< amp::ampf<Precision> >& b, |
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294 | int id1, |
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295 | int id2, |
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296 | int jd1, |
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297 | int jd2) |
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298 | { |
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299 | int isrc; |
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300 | int idst; |
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301 | |
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302 | |
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303 | if( is1>is2 || js1>js2 ) |
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304 | { |
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305 | return; |
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306 | } |
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307 | ap::ap_error::make_assertion(is2-is1==id2-id1); |
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308 | ap::ap_error::make_assertion(js2-js1==jd2-jd1); |
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309 | for(isrc=is1; isrc<=is2; isrc++) |
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310 | { |
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311 | idst = isrc-is1+id1; |
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312 | ap::vmove(b.getrow(idst, jd1, jd2), a.getrow(isrc, js1, js2)); |
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313 | } |
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314 | } |
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315 | |
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316 | |
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317 | template<unsigned int Precision> |
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318 | void inplacetranspose(ap::template_2d_array< amp::ampf<Precision> >& a, |
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319 | int i1, |
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320 | int i2, |
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321 | int j1, |
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322 | int j2, |
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323 | ap::template_1d_array< amp::ampf<Precision> >& work) |
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324 | { |
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325 | int i; |
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326 | int j; |
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327 | int ips; |
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328 | int jps; |
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329 | int l; |
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330 | |
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331 | |
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332 | if( i1>i2 || j1>j2 ) |
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333 | { |
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334 | return; |
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335 | } |
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336 | ap::ap_error::make_assertion(i1-i2==j1-j2); |
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337 | for(i=i1; i<=i2-1; i++) |
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338 | { |
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339 | j = j1+i-i1; |
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340 | ips = i+1; |
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341 | jps = j1+ips-i1; |
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342 | l = i2-i; |
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343 | ap::vmove(work.getvector(1, l), a.getcolumn(j, ips, i2)); |
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344 | ap::vmove(a.getcolumn(j, ips, i2), a.getrow(i, jps, j2)); |
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345 | ap::vmove(a.getrow(i, jps, j2), work.getvector(1, l)); |
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346 | } |
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347 | } |
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348 | |
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349 | |
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350 | template<unsigned int Precision> |
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351 | void copyandtranspose(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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352 | int is1, |
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353 | int is2, |
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354 | int js1, |
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355 | int js2, |
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356 | ap::template_2d_array< amp::ampf<Precision> >& b, |
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357 | int id1, |
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358 | int id2, |
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359 | int jd1, |
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360 | int jd2) |
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361 | { |
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362 | int isrc; |
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363 | int jdst; |
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364 | |
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365 | |
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366 | if( is1>is2 || js1>js2 ) |
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367 | { |
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368 | return; |
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369 | } |
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370 | ap::ap_error::make_assertion(is2-is1==jd2-jd1); |
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371 | ap::ap_error::make_assertion(js2-js1==id2-id1); |
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372 | for(isrc=is1; isrc<=is2; isrc++) |
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373 | { |
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374 | jdst = isrc-is1+jd1; |
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375 | ap::vmove(b.getcolumn(jdst, id1, id2), a.getrow(isrc, js1, js2)); |
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376 | } |
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377 | } |
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378 | |
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379 | |
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380 | template<unsigned int Precision> |
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381 | void matrixvectormultiply(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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382 | int i1, |
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383 | int i2, |
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384 | int j1, |
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385 | int j2, |
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386 | bool trans, |
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387 | const ap::template_1d_array< amp::ampf<Precision> >& x, |
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388 | int ix1, |
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389 | int ix2, |
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390 | amp::ampf<Precision> alpha, |
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391 | ap::template_1d_array< amp::ampf<Precision> >& y, |
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392 | int iy1, |
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393 | int iy2, |
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394 | amp::ampf<Precision> beta) |
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395 | { |
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396 | int i; |
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397 | amp::ampf<Precision> v; |
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398 | |
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399 | |
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400 | if( !trans ) |
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401 | { |
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402 | |
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403 | // |
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404 | // y := alpha*A*x + beta*y; |
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405 | // |
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406 | if( i1>i2 || j1>j2 ) |
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407 | { |
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408 | return; |
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409 | } |
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410 | ap::ap_error::make_assertion(j2-j1==ix2-ix1); |
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411 | ap::ap_error::make_assertion(i2-i1==iy2-iy1); |
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412 | |
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413 | // |
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414 | // beta*y |
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415 | // |
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416 | if( beta==0 ) |
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417 | { |
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418 | for(i=iy1; i<=iy2; i++) |
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419 | { |
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420 | y(i) = 0; |
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421 | } |
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422 | } |
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423 | else |
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424 | { |
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425 | ap::vmul(y.getvector(iy1, iy2), beta); |
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426 | } |
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427 | |
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428 | // |
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429 | // alpha*A*x |
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430 | // |
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431 | for(i=i1; i<=i2; i++) |
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432 | { |
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433 | v = ap::vdotproduct(a.getrow(i, j1, j2), x.getvector(ix1, ix2)); |
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434 | y(iy1+i-i1) = y(iy1+i-i1)+alpha*v; |
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435 | } |
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436 | } |
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437 | else |
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438 | { |
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439 | |
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440 | // |
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441 | // y := alpha*A'*x + beta*y; |
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442 | // |
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443 | if( i1>i2 || j1>j2 ) |
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444 | { |
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445 | return; |
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446 | } |
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447 | ap::ap_error::make_assertion(i2-i1==ix2-ix1); |
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448 | ap::ap_error::make_assertion(j2-j1==iy2-iy1); |
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449 | |
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450 | // |
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451 | // beta*y |
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452 | // |
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453 | if( beta==0 ) |
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454 | { |
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455 | for(i=iy1; i<=iy2; i++) |
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456 | { |
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457 | y(i) = 0; |
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458 | } |
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459 | } |
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460 | else |
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461 | { |
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462 | ap::vmul(y.getvector(iy1, iy2), beta); |
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463 | } |
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464 | |
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465 | // |
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466 | // alpha*A'*x |
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467 | // |
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468 | for(i=i1; i<=i2; i++) |
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469 | { |
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470 | v = alpha*x(ix1+i-i1); |
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471 | ap::vadd(y.getvector(iy1, iy2), a.getrow(i, j1, j2), v); |
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472 | } |
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473 | } |
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474 | } |
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475 | |
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476 | |
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477 | template<unsigned int Precision> |
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478 | amp::ampf<Precision> pythag2(amp::ampf<Precision> x, |
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479 | amp::ampf<Precision> y) |
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480 | { |
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481 | amp::ampf<Precision> result; |
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482 | amp::ampf<Precision> w; |
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483 | amp::ampf<Precision> xabs; |
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484 | amp::ampf<Precision> yabs; |
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485 | amp::ampf<Precision> z; |
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486 | |
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487 | |
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488 | xabs = amp::abs<Precision>(x); |
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489 | yabs = amp::abs<Precision>(y); |
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490 | w = amp::maximum<Precision>(xabs, yabs); |
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491 | z = amp::minimum<Precision>(xabs, yabs); |
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492 | if( z==0 ) |
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493 | { |
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494 | result = w; |
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495 | } |
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496 | else |
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497 | { |
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498 | result = w*amp::sqrt<Precision>(1+amp::sqr<Precision>(z/w)); |
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499 | } |
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500 | return result; |
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501 | } |
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502 | |
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503 | |
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504 | template<unsigned int Precision> |
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505 | void matrixmatrixmultiply(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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506 | int ai1, |
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507 | int ai2, |
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508 | int aj1, |
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509 | int aj2, |
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510 | bool transa, |
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511 | const ap::template_2d_array< amp::ampf<Precision> >& b, |
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512 | int bi1, |
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513 | int bi2, |
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514 | int bj1, |
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515 | int bj2, |
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516 | bool transb, |
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517 | amp::ampf<Precision> alpha, |
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518 | ap::template_2d_array< amp::ampf<Precision> >& c, |
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519 | int ci1, |
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520 | int ci2, |
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521 | int cj1, |
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522 | int cj2, |
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523 | amp::ampf<Precision> beta, |
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524 | ap::template_1d_array< amp::ampf<Precision> >& work) |
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525 | { |
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526 | int arows; |
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527 | int acols; |
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528 | int brows; |
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529 | int bcols; |
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530 | int crows; |
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531 | int ccols; |
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532 | int i; |
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533 | int j; |
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534 | int k; |
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535 | int l; |
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536 | int r; |
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537 | amp::ampf<Precision> v; |
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538 | |
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539 | |
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540 | |
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541 | // |
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542 | // Setup |
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543 | // |
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544 | if( !transa ) |
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545 | { |
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546 | arows = ai2-ai1+1; |
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547 | acols = aj2-aj1+1; |
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548 | } |
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549 | else |
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550 | { |
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551 | arows = aj2-aj1+1; |
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552 | acols = ai2-ai1+1; |
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553 | } |
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554 | if( !transb ) |
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555 | { |
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556 | brows = bi2-bi1+1; |
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557 | bcols = bj2-bj1+1; |
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558 | } |
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559 | else |
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560 | { |
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561 | brows = bj2-bj1+1; |
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562 | bcols = bi2-bi1+1; |
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563 | } |
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564 | ap::ap_error::make_assertion(acols==brows); |
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565 | if( arows<=0 || acols<=0 || brows<=0 || bcols<=0 ) |
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566 | { |
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567 | return; |
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568 | } |
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569 | crows = arows; |
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570 | ccols = bcols; |
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571 | |
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572 | // |
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573 | // Test WORK |
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574 | // |
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575 | i = ap::maxint(arows, acols); |
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576 | i = ap::maxint(brows, i); |
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577 | i = ap::maxint(i, bcols); |
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578 | work(1) = 0; |
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579 | work(i) = 0; |
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580 | |
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581 | // |
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582 | // Prepare C |
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583 | // |
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584 | if( beta==0 ) |
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585 | { |
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586 | for(i=ci1; i<=ci2; i++) |
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587 | { |
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588 | for(j=cj1; j<=cj2; j++) |
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589 | { |
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590 | c(i,j) = 0; |
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591 | } |
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592 | } |
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593 | } |
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594 | else |
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595 | { |
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596 | for(i=ci1; i<=ci2; i++) |
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597 | { |
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598 | ap::vmul(c.getrow(i, cj1, cj2), beta); |
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599 | } |
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600 | } |
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601 | |
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602 | // |
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603 | // A*B |
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604 | // |
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605 | if( !transa && !transb ) |
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606 | { |
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607 | for(l=ai1; l<=ai2; l++) |
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608 | { |
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609 | for(r=bi1; r<=bi2; r++) |
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610 | { |
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611 | v = alpha*a(l,aj1+r-bi1); |
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612 | k = ci1+l-ai1; |
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613 | ap::vadd(c.getrow(k, cj1, cj2), b.getrow(r, bj1, bj2), v); |
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614 | } |
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615 | } |
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616 | return; |
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617 | } |
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618 | |
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619 | // |
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620 | // A*B' |
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621 | // |
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622 | if( !transa && transb ) |
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623 | { |
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624 | if( arows*acols<brows*bcols ) |
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625 | { |
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626 | for(r=bi1; r<=bi2; r++) |
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627 | { |
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628 | for(l=ai1; l<=ai2; l++) |
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629 | { |
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630 | v = ap::vdotproduct(a.getrow(l, aj1, aj2), b.getrow(r, bj1, bj2)); |
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631 | c(ci1+l-ai1,cj1+r-bi1) = c(ci1+l-ai1,cj1+r-bi1)+alpha*v; |
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632 | } |
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633 | } |
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634 | return; |
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635 | } |
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636 | else |
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637 | { |
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638 | for(l=ai1; l<=ai2; l++) |
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639 | { |
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640 | for(r=bi1; r<=bi2; r++) |
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641 | { |
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642 | v = ap::vdotproduct(a.getrow(l, aj1, aj2), b.getrow(r, bj1, bj2)); |
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643 | c(ci1+l-ai1,cj1+r-bi1) = c(ci1+l-ai1,cj1+r-bi1)+alpha*v; |
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644 | } |
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645 | } |
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646 | return; |
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647 | } |
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648 | } |
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649 | |
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650 | // |
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651 | // A'*B |
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652 | // |
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653 | if( transa && !transb ) |
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654 | { |
---|
655 | for(l=aj1; l<=aj2; l++) |
---|
656 | { |
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657 | for(r=bi1; r<=bi2; r++) |
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658 | { |
---|
659 | v = alpha*a(ai1+r-bi1,l); |
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660 | k = ci1+l-aj1; |
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661 | ap::vadd(c.getrow(k, cj1, cj2), b.getrow(r, bj1, bj2), v); |
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662 | } |
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663 | } |
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664 | return; |
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665 | } |
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666 | |
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667 | // |
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668 | // A'*B' |
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669 | // |
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670 | if( transa && transb ) |
---|
671 | { |
---|
672 | if( arows*acols<brows*bcols ) |
---|
673 | { |
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674 | for(r=bi1; r<=bi2; r++) |
---|
675 | { |
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676 | for(i=1; i<=crows; i++) |
---|
677 | { |
---|
678 | work(i) = amp::ampf<Precision>("0.0"); |
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679 | } |
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680 | for(l=ai1; l<=ai2; l++) |
---|
681 | { |
---|
682 | v = alpha*b(r,bj1+l-ai1); |
---|
683 | k = cj1+r-bi1; |
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684 | ap::vadd(work.getvector(1, crows), a.getrow(l, aj1, aj2), v); |
---|
685 | } |
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686 | ap::vadd(c.getcolumn(k, ci1, ci2), work.getvector(1, crows)); |
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687 | } |
---|
688 | return; |
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689 | } |
---|
690 | else |
---|
691 | { |
---|
692 | for(l=aj1; l<=aj2; l++) |
---|
693 | { |
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694 | k = ai2-ai1+1; |
---|
695 | ap::vmove(work.getvector(1, k), a.getcolumn(l, ai1, ai2)); |
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696 | for(r=bi1; r<=bi2; r++) |
---|
697 | { |
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698 | v = ap::vdotproduct(work.getvector(1, k), b.getrow(r, bj1, bj2)); |
---|
699 | c(ci1+l-aj1,cj1+r-bi1) = c(ci1+l-aj1,cj1+r-bi1)+alpha*v; |
---|
700 | } |
---|
701 | } |
---|
702 | return; |
---|
703 | } |
---|
704 | } |
---|
705 | } |
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706 | } // namespace |
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707 | |
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708 | #endif |
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