1 | #include <kernel/mod2.h> |
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2 | #include <kernel/structs.h> |
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3 | #include <polys/polys.h> |
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4 | #include <MinorProcessor.h> |
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5 | #include <kernel/febase.h> |
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6 | #include <kernel/kstd1.h> |
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7 | #include <polys/kbuckets.h> |
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8 | |
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9 | #ifdef COUNT_AND_PRINT_OPERATIONS |
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10 | long addsPoly = 0; /* for the number of additions of two polynomials */ |
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11 | long multsPoly = 0; /* for the number of multiplications of two polynomials */ |
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12 | long addsPolyForDiv = 0; /* for the number of additions of two polynomials for |
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13 | polynomial division part */ |
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14 | long multsPolyForDiv = 0; /* for the number of multiplications of two polynomials |
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15 | for polynomial division part */ |
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16 | long multsMon = 0; /* for the number of multiplications of two monomials */ |
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17 | long multsMonForDiv = 0; /* for the number of m-m-multiplications for polynomial |
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18 | division part */ |
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19 | long savedMultsMFD = 0; /* number of m-m-multiplications that could be saved |
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20 | when polynomial division would be optimal |
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21 | (if p / t1 = t2 + ..., then t1 * t2 = LT(p), i.e., |
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22 | this multiplication need not be performed which |
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23 | would save one m-m-multiplication) */ |
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24 | long divsMon = 0; /* for the number of divisions of two monomials; |
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25 | these are all guaranteed to work, i.e., m1/m2 only |
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26 | when exponentVector(m1) >= exponentVector(m2) */ |
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27 | void printCounters (char* prefix, bool resetToZero) |
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28 | { |
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29 | printf("%s [p+p(div) | p*p(div) | m*m(div, -save) | m/m ]", prefix); |
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30 | printf(" = [%ld(%ld) | %ld(%ld) | %ld(%d, -%ld) | %ld]\n", |
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31 | addsPoly, addsPolyForDiv, multsPoly, multsPolyForDiv, |
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32 | multsMon, multsMonForDiv, savedMultsMFD, divsMon); |
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33 | if (resetToZero) |
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34 | { |
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35 | multsMon = 0; addsPoly = 0; multsPoly = 0; divsMon = 0; |
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36 | savedMultsMFD = 0; multsMonForDiv = 0; addsPolyForDiv = 0; |
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37 | multsPolyForDiv = 0; |
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38 | } |
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39 | } |
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40 | #endif |
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41 | /* COUNT_AND_PRINT_OPERATIONS */ |
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42 | |
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43 | void MinorProcessor::print() const |
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44 | { |
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45 | PrintS(this->toString().c_str()); |
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46 | } |
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47 | |
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48 | int MinorProcessor::getBestLine (const int k, const MinorKey& mk) const |
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49 | { |
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50 | /* This method identifies the row or column with the most zeros. |
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51 | The returned index (bestIndex) is absolute within the pre- |
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52 | defined matrix. |
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53 | If some row has the most zeros, then the absolute (0-based) |
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54 | row index is returned. |
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55 | If, contrariwise, some column has the most zeros, then -1 minus |
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56 | the absolute (0-based) column index is returned. */ |
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57 | int numberOfZeros = 0; |
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58 | int bestIndex = 100000; /* We start with an invalid row/column index. */ |
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59 | int maxNumberOfZeros = -1; /* We update this variable whenever we find |
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60 | a new so-far optimal row or column. */ |
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61 | for (int r = 0; r < k; r++) |
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62 | { |
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63 | /* iterate through all k rows of the momentary minor */ |
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64 | int absoluteR = mk.getAbsoluteRowIndex(r); |
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65 | numberOfZeros = 0; |
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66 | for (int c = 0; c < k; c++) |
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67 | { |
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68 | int absoluteC = mk.getAbsoluteColumnIndex(c); |
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69 | if (isEntryZero(absoluteR, absoluteC)) numberOfZeros++; |
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70 | } |
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71 | if (numberOfZeros > maxNumberOfZeros) |
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72 | { |
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73 | /* We found a new best line which is a row. */ |
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74 | bestIndex = absoluteR; |
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75 | maxNumberOfZeros = numberOfZeros; |
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76 | } |
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77 | }; |
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78 | for (int c = 0; c < k; c++) |
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79 | { |
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80 | int absoluteC = mk.getAbsoluteColumnIndex(c); |
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81 | numberOfZeros = 0; |
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82 | for (int r = 0; r < k; r++) |
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83 | { |
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84 | int absoluteR = mk.getAbsoluteRowIndex(r); |
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85 | if (isEntryZero(absoluteR, absoluteC)) numberOfZeros++; |
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86 | } |
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87 | if (numberOfZeros > maxNumberOfZeros) |
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88 | { |
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89 | /* We found a new best line which is a column. So we transform |
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90 | the return value. Note that we can easily retrieve absoluteC |
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91 | from bestLine: absoluteC = - 1 - bestLine. */ |
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92 | bestIndex = - absoluteC - 1; |
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93 | maxNumberOfZeros = numberOfZeros; |
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94 | } |
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95 | }; |
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96 | return bestIndex; |
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97 | } |
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98 | |
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99 | void MinorProcessor::setMinorSize(const int minorSize) |
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100 | { |
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101 | _minorSize = minorSize; |
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102 | _minor.reset(); |
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103 | } |
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104 | |
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105 | bool MinorProcessor::hasNextMinor() |
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106 | { |
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107 | return setNextKeys(_minorSize); |
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108 | } |
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109 | |
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110 | void MinorProcessor::getCurrentRowIndices(int* const target) const |
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111 | { |
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112 | return _minor.getAbsoluteRowIndices(target); |
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113 | } |
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114 | |
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115 | void MinorProcessor::getCurrentColumnIndices(int* const target) const |
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116 | { |
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117 | return _minor.getAbsoluteColumnIndices(target); |
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118 | } |
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119 | |
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120 | void MinorProcessor::defineSubMatrix(const int numberOfRows, |
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121 | const int* rowIndices, |
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122 | const int numberOfColumns, |
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123 | const int* columnIndices) |
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124 | { |
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125 | /* The method assumes ascending row and column indices in the |
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126 | two argument arrays. These indices are understood to be zero-based. |
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127 | The method will set the two arrays of ints in _container. |
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128 | Example: The indices 0, 2, 3, 7 will be converted to an array with |
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129 | one int representing the binary number 10001101 |
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130 | (check bits from right to left). */ |
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131 | |
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132 | _containerRows = numberOfRows; |
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133 | int highestRowIndex = rowIndices[numberOfRows - 1]; |
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134 | int rowBlockCount = (highestRowIndex / 32) + 1; |
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135 | unsigned int *rowBlocks=new unsigned int[rowBlockCount]; |
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136 | for (int i = 0; i < rowBlockCount; i++) rowBlocks[i] = 0; |
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137 | for (int i = 0; i < numberOfRows; i++) |
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138 | { |
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139 | int blockIndex = rowIndices[i] / 32; |
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140 | int offset = rowIndices[i] % 32; |
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141 | rowBlocks[blockIndex] += (1 << offset); |
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142 | } |
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143 | |
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144 | _containerColumns = numberOfColumns; |
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145 | int highestColumnIndex = columnIndices[numberOfColumns - 1]; |
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146 | int columnBlockCount = (highestColumnIndex / 32) + 1; |
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147 | unsigned *columnBlocks=new unsigned[columnBlockCount]; |
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148 | for (int i = 0; i < columnBlockCount; i++) columnBlocks[i] = 0; |
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149 | for (int i = 0; i < numberOfColumns; i++) |
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150 | { |
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151 | int blockIndex = columnIndices[i] / 32; |
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152 | int offset = columnIndices[i] % 32; |
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153 | columnBlocks[blockIndex] += (1 << offset); |
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154 | } |
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155 | |
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156 | _container.set(rowBlockCount, rowBlocks, columnBlockCount, columnBlocks); |
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157 | delete[] columnBlocks; |
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158 | delete[] rowBlocks; |
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159 | } |
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160 | |
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161 | bool MinorProcessor::setNextKeys(const int k) |
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162 | { |
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163 | /* This method moves _minor to the next valid (k x k)-minor within |
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164 | _container. It returns true iff this is successful, i.e. iff |
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165 | _minor did not already encode the terminal (k x k)-minor. */ |
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166 | if (_minor.compare(MinorKey(0, 0, 0, 0)) == 0) |
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167 | { |
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168 | /* This means that we haven't started yet. Thus, we are about |
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169 | to compute the first (k x k)-minor. */ |
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170 | _minor.selectFirstRows(k, _container); |
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171 | _minor.selectFirstColumns(k, _container); |
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172 | return true; |
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173 | } |
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174 | else if (_minor.selectNextColumns(k, _container)) |
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175 | { |
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176 | /* Here we were able to pick a next subset of columns |
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177 | within the same subset of rows. */ |
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178 | return true; |
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179 | } |
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180 | else if (_minor.selectNextRows(k, _container)) |
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181 | { |
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182 | /* Here we were not able to pick a next subset of columns |
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183 | within the same subset of rows. But we could pick a next |
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184 | subset of rows. We must hence reset the subset of columns: */ |
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185 | _minor.selectFirstColumns(k, _container); |
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186 | return true; |
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187 | } |
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188 | else |
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189 | { |
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190 | /* We were neither able to pick a next subset |
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191 | of columns nor of rows. I.e., we have iterated through |
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192 | all sensible choices of subsets of rows and columns. */ |
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193 | return false; |
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194 | } |
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195 | } |
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196 | |
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197 | bool MinorProcessor::isEntryZero (const int absoluteRowIndex, |
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198 | const int absoluteColumnIndex) const |
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199 | { |
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200 | assume(false); |
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201 | return false; |
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202 | } |
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203 | |
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204 | string MinorProcessor::toString () const |
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205 | { |
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206 | assume(false); |
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207 | return ""; |
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208 | } |
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209 | |
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210 | int MinorProcessor::IOverJ(const int i, const int j) |
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211 | { |
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212 | /* This is a non-recursive implementation. */ |
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213 | assert( (i >= 0) && (j >= 0) && (i >= j)); |
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214 | if (j == 0 || i == j) return 1; |
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215 | int result = 1; |
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216 | for (int k = i - j + 1; k <= i; k++) result *= k; |
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217 | /* Now, result = (i - j + 1) * ... * i. */ |
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218 | for (int k = 2; k <= j; k++) result /= k; |
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219 | /* Now, result = (i - j + 1) * ... * i / 1 / 2 ... |
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220 | ... / j = i! / j! / (i - j)!. */ |
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221 | return result; |
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222 | } |
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223 | |
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224 | int MinorProcessor::Faculty(const int i) |
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225 | { |
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226 | /* This is a non-recursive implementation. */ |
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227 | assert(i >= 0); |
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228 | int result = 1; |
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229 | for (int j = 1; j <= i; j++) result *= j; |
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230 | // Now, result = 1 * 2 * ... * i = i! |
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231 | return result; |
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232 | } |
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233 | |
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234 | int MinorProcessor::NumberOfRetrievals (const int rows, const int columns, |
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235 | const int containerMinorSize, |
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236 | const int minorSize, |
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237 | const bool multipleMinors) |
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238 | { |
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239 | /* This method computes the number of potential retrievals |
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240 | of a single minor when computing all minors of a given size |
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241 | within a matrix of given size. */ |
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242 | int result = 0; |
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243 | if (multipleMinors) |
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244 | { |
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245 | /* Here, we would like to compute all minors of size |
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246 | containerMinorSize x containerMinorSize in a matrix |
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247 | of size rows x columns. |
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248 | Then, we need to retrieve any minor of size |
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249 | minorSize x minorSize exactly n times, where n is as |
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250 | follows: */ |
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251 | result = IOverJ(rows - minorSize, containerMinorSize - minorSize) |
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252 | * IOverJ(columns - minorSize, containerMinorSize - minorSize) |
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253 | * Faculty(containerMinorSize - minorSize); |
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254 | } |
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255 | else |
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256 | { |
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257 | /* Here, we would like to compute just one minor of size |
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258 | containerMinorSize x containerMinorSize. Then, we need |
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259 | to retrieve any minor of size minorSize x minorSize exactly |
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260 | (containerMinorSize - minorSize)! times: */ |
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261 | result = Faculty(containerMinorSize - minorSize); |
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262 | } |
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263 | return result; |
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264 | } |
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265 | |
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266 | MinorProcessor::MinorProcessor () |
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267 | { |
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268 | _container = MinorKey(0, 0, 0, 0); |
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269 | _minor = MinorKey(0, 0, 0, 0); |
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270 | _containerRows = 0; |
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271 | _containerColumns = 0; |
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272 | _minorSize = 0; |
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273 | _rows = 0; |
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274 | _columns = 0; |
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275 | } |
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276 | |
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277 | MinorProcessor::~MinorProcessor () { } |
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278 | |
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279 | IntMinorProcessor::IntMinorProcessor () |
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280 | { |
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281 | _intMatrix = 0; |
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282 | } |
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283 | |
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284 | string IntMinorProcessor::toString () const |
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285 | { |
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286 | char h[32]; |
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287 | string t = ""; |
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288 | string s = "IntMinorProcessor:"; |
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289 | s += "\n matrix: "; |
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290 | sprintf(h, "%d", _rows); s += h; |
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291 | s += " x "; |
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292 | sprintf(h, "%d", _columns); s += h; |
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293 | for (int r = 0; r < _rows; r++) |
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294 | { |
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295 | s += "\n "; |
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296 | for (int c = 0; c < _columns; c++) |
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297 | { |
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298 | sprintf(h, "%d", getEntry(r, c)); t = h; |
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299 | for (int k = 0; k < int(4 - strlen(h)); k++) s += " "; |
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300 | s += t; |
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301 | } |
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302 | } |
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303 | int myIndexArray[500]; |
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304 | s += "\n considered submatrix has row indices: "; |
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305 | _container.getAbsoluteRowIndices(myIndexArray); |
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306 | for (int k = 0; k < _containerRows; k++) |
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307 | { |
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308 | if (k != 0) s += ", "; |
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309 | sprintf(h, "%d", myIndexArray[k]); s += h; |
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310 | } |
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311 | s += " (first row of matrix has index 0)"; |
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312 | s += "\n considered submatrix has column indices: "; |
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313 | _container.getAbsoluteColumnIndices(myIndexArray); |
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314 | for (int k = 0; k < _containerColumns; k++) |
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315 | { |
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316 | if (k != 0) s += ", "; |
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317 | sprintf(h, "%d", myIndexArray[k]); s += h; |
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318 | } |
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319 | s += " (first column of matrix has index 0)"; |
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320 | s += "\n size of considered minor(s): "; |
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321 | sprintf(h, "%d", _minorSize); s += h; |
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322 | s += "x"; |
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323 | s += h; |
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324 | return s; |
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325 | } |
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326 | |
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327 | IntMinorProcessor::~IntMinorProcessor() |
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328 | { |
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329 | /* free memory of _intMatrix */ |
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330 | delete [] _intMatrix; _intMatrix = 0; |
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331 | } |
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332 | |
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333 | bool IntMinorProcessor::isEntryZero (const int absoluteRowIndex, |
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334 | const int absoluteColumnIndex) const |
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335 | { |
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336 | return getEntry(absoluteRowIndex, absoluteColumnIndex) == 0; |
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337 | } |
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338 | |
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339 | void IntMinorProcessor::defineMatrix (const int numberOfRows, |
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340 | const int numberOfColumns, |
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341 | const int* matrix) |
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342 | { |
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343 | /* free memory of _intMatrix */ |
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344 | delete [] _intMatrix; _intMatrix = 0; |
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345 | |
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346 | _rows = numberOfRows; |
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347 | _columns = numberOfColumns; |
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348 | |
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349 | /* allocate memory for new entries in _intMatrix */ |
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350 | int n = _rows * _columns; |
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351 | _intMatrix = new int[n]; |
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352 | |
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353 | /* copying values from one-dimensional method |
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354 | parameter "matrix" */ |
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355 | for (int i = 0; i < n; i++) |
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356 | _intMatrix[i] = matrix[i]; |
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357 | } |
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358 | |
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359 | IntMinorValue IntMinorProcessor::getMinor(const int dimension, |
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360 | const int* rowIndices, |
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361 | const int* columnIndices, |
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362 | Cache<MinorKey, IntMinorValue>& c, |
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363 | const int characteristic, |
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364 | const ideal& iSB) |
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365 | { |
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366 | defineSubMatrix(dimension, rowIndices, dimension, columnIndices); |
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367 | _minorSize = dimension; |
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368 | /* call a helper method which recursively computes the minor using the |
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369 | cache c: */ |
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370 | return getMinorPrivateLaplace(dimension, _container, false, c, |
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371 | characteristic, iSB); |
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372 | } |
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373 | |
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374 | IntMinorValue IntMinorProcessor::getMinor(const int dimension, |
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375 | const int* rowIndices, |
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376 | const int* columnIndices, |
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377 | const int characteristic, |
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378 | const ideal& iSB, |
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379 | const char* algorithm) |
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380 | { |
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381 | defineSubMatrix(dimension, rowIndices, dimension, columnIndices); |
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382 | _minorSize = dimension; |
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383 | |
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384 | /* call a helper method which computes the minor (without a cache): */ |
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385 | if (strcmp(algorithm, "Laplace") == 0) |
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386 | return getMinorPrivateLaplace(_minorSize, _container, characteristic, |
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387 | iSB); |
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388 | else if (strcmp(algorithm, "Bareiss") == 0) |
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389 | return getMinorPrivateBareiss(_minorSize, _container, characteristic, |
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390 | iSB); |
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391 | else assume(false); |
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392 | |
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393 | /* The following code is never reached and just there to make the |
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394 | compiler happy: */ |
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395 | return IntMinorValue(); |
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396 | } |
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397 | |
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398 | IntMinorValue IntMinorProcessor::getNextMinor(const int characteristic, |
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399 | const ideal& iSB, |
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400 | const char* algorithm) |
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401 | { |
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402 | /* call a helper method which computes the minor (without a cache): */ |
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403 | if (strcmp(algorithm, "Laplace") == 0) |
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404 | return getMinorPrivateLaplace(_minorSize, _minor, characteristic, iSB); |
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405 | else if (strcmp(algorithm, "Bareiss") == 0) |
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406 | return getMinorPrivateBareiss(_minorSize, _minor, characteristic, iSB); |
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407 | else assume(false); |
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408 | |
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409 | /* The following code is never reached and just there to make the |
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410 | compiler happy: */ |
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411 | return IntMinorValue(); |
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412 | } |
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413 | |
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414 | IntMinorValue IntMinorProcessor::getNextMinor(Cache<MinorKey, |
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415 | IntMinorValue>& c, |
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416 | const int characteristic, |
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417 | const ideal& iSB) |
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418 | { |
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419 | /* computation with cache */ |
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420 | return getMinorPrivateLaplace(_minorSize, _minor, true, c, characteristic, |
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421 | iSB); |
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422 | } |
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423 | |
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424 | /* computes the reduction of an integer i modulo an ideal |
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425 | which captures a std basis */ |
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426 | int getReduction (const int i, const ideal& iSB) |
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427 | { |
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428 | if (i == 0) return 0; |
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429 | poly f = pISet(i); |
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430 | poly g = kNF(iSB, currRing->qideal, f); |
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431 | int result = 0; |
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432 | if (g != NULL) result = n_Int(pGetCoeff(g), currRing); |
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433 | pDelete(&f); |
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434 | pDelete(&g); |
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435 | return result; |
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436 | } |
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437 | |
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438 | IntMinorValue IntMinorProcessor::getMinorPrivateLaplace( |
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439 | const int k, |
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440 | const MinorKey& mk, |
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441 | const int characteristic, |
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442 | const ideal& iSB) |
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443 | { |
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444 | assert(k > 0); /* k is the minor's dimension; the minor must be at least |
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445 | 1x1 */ |
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446 | /* The method works by recursion, and using Lapace's Theorem along the |
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447 | row/column with the most zeros. */ |
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448 | if (k == 1) |
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449 | { |
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450 | int e = getEntry(mk.getAbsoluteRowIndex(0), mk.getAbsoluteColumnIndex(0)); |
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451 | if (characteristic != 0) e = e % characteristic; |
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452 | if (iSB != 0) e = getReduction(e, iSB); |
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453 | return IntMinorValue(e, 0, 0, 0, 0, -1, -1); /* "-1" is to signal that any |
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454 | statistics about the number |
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455 | of retrievals does not make |
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456 | sense, as we do not use a |
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457 | cache. */ |
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458 | } |
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459 | else |
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460 | { |
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461 | /* Here, the minor must be 2x2 or larger. */ |
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462 | int b = getBestLine(k, mk); /* row or column with most |
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463 | zeros */ |
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464 | int result = 0; /* This will contain the |
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465 | value of the minor. */ |
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466 | int s = 0; int m = 0; int as = 0; int am = 0; /* counters for additions and |
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467 | multiplications, ..."a*" |
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468 | for accumulated operation |
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469 | counters */ |
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470 | bool hadNonZeroEntry = false; |
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471 | if (b >= 0) |
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472 | { |
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473 | /* This means that the best line is the row with absolute (0-based) |
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474 | index b. |
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475 | Using Laplace, the sign of the contributing minors must be iterating; |
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476 | the initial sign depends on the relative index of b in minorRowKey: */ |
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477 | int sign = (mk.getRelativeRowIndex(b) % 2 == 0 ? 1 : -1); |
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478 | for (int c = 0; c < k; c++) /* This iterates over all involved columns. */ |
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479 | { |
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480 | int absoluteC = mk.getAbsoluteColumnIndex(c); |
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481 | if (getEntry(b, absoluteC) != 0) /* Only then do we have to consider |
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482 | this sub-determinante. */ |
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483 | { |
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484 | hadNonZeroEntry = true; |
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485 | /* Next MinorKey is mk with row b and column absoluteC omitted: */ |
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486 | MinorKey subMk = mk.getSubMinorKey(b, absoluteC); |
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487 | IntMinorValue mv = getMinorPrivateLaplace(k - 1, subMk, |
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488 | characteristic, iSB); /* recursive call */ |
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489 | m += mv.getMultiplications(); |
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490 | s += mv.getAdditions(); |
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491 | am += mv.getAccumulatedMultiplications(); |
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492 | as += mv.getAccumulatedAdditions(); |
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493 | /* adding sub-determinante times matrix entry |
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494 | times appropriate sign: */ |
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495 | result += sign * mv.getResult() * getEntry(b, absoluteC); |
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496 | |
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497 | if (characteristic != 0) result = result % characteristic; |
---|
498 | s++; m++; as++, am++; /* This is for the last addition and |
---|
499 | multiplication. */ |
---|
500 | } |
---|
501 | sign = - sign; /* alternating the sign */ |
---|
502 | } |
---|
503 | } |
---|
504 | else |
---|
505 | { |
---|
506 | b = - b - 1; |
---|
507 | /* This means that the best line is the column with absolute (0-based) |
---|
508 | index b. |
---|
509 | Using Laplace, the sign of the contributing minors must be iterating; |
---|
510 | the initial sign depends on the relative index of b in |
---|
511 | minorColumnKey: */ |
---|
512 | int sign = (mk.getRelativeColumnIndex(b) % 2 == 0 ? 1 : -1); |
---|
513 | for (int r = 0; r < k; r++) /* This iterates over all involved rows. */ |
---|
514 | { |
---|
515 | int absoluteR = mk.getAbsoluteRowIndex(r); |
---|
516 | if (getEntry(absoluteR, b) != 0) /* Only then do we have to consider |
---|
517 | this sub-determinante. */ |
---|
518 | { |
---|
519 | hadNonZeroEntry = true; |
---|
520 | /* Next MinorKey is mk with row absoluteR and column b omitted. */ |
---|
521 | MinorKey subMk = mk.getSubMinorKey(absoluteR, b); |
---|
522 | IntMinorValue mv = getMinorPrivateLaplace(k - 1, subMk, characteristic, iSB); /* recursive call */ |
---|
523 | m += mv.getMultiplications(); |
---|
524 | s += mv.getAdditions(); |
---|
525 | am += mv.getAccumulatedMultiplications(); |
---|
526 | as += mv.getAccumulatedAdditions(); |
---|
527 | /* adding sub-determinante times matrix entry |
---|
528 | times appropriate sign: */ |
---|
529 | result += sign * mv.getResult() * getEntry(absoluteR, b); |
---|
530 | if (characteristic != 0) result = result % characteristic; |
---|
531 | s++; m++; as++, am++; /* This is for the last addition and |
---|
532 | multiplication. */ |
---|
533 | } |
---|
534 | sign = - sign; /* alternating the sign */ |
---|
535 | } |
---|
536 | } |
---|
537 | if (hadNonZeroEntry) |
---|
538 | { |
---|
539 | s--; as--; /* first addition was 0 + ..., so we do not count it */ |
---|
540 | } |
---|
541 | if (s < 0) s = 0; /* may happen when all subminors are zero and no |
---|
542 | addition needs to be performed */ |
---|
543 | if (as < 0) as = 0; /* may happen when all subminors are zero and no |
---|
544 | addition needs to be performed */ |
---|
545 | if (iSB != 0) result = getReduction(result, iSB); |
---|
546 | IntMinorValue newMV(result, m, s, am, as, -1, -1); |
---|
547 | /* "-1" is to signal that any statistics about the number of retrievals |
---|
548 | does not make sense, as we do not use a cache. */ |
---|
549 | return newMV; |
---|
550 | } |
---|
551 | } |
---|
552 | |
---|
553 | /* This method can only be used in the case of coefficients |
---|
554 | coming from a field or at least from an integral domain. */ |
---|
555 | IntMinorValue IntMinorProcessor::getMinorPrivateBareiss( |
---|
556 | const int k, |
---|
557 | const MinorKey& mk, |
---|
558 | const int characteristic, |
---|
559 | const ideal& iSB) |
---|
560 | { |
---|
561 | assert(k > 0); /* k is the minor's dimension; the minor must be at least |
---|
562 | 1x1 */ |
---|
563 | int *theRows=new int[k]; mk.getAbsoluteRowIndices(theRows); |
---|
564 | int *theColumns=new int[k]; mk.getAbsoluteColumnIndices(theColumns); |
---|
565 | /* the next line provides the return value for the case k = 1 */ |
---|
566 | int e = getEntry(theRows[0], theColumns[0]); |
---|
567 | if (characteristic != 0) e = e % characteristic; |
---|
568 | if (iSB != 0) e = getReduction(e, iSB); |
---|
569 | IntMinorValue mv(e, 0, 0, 0, 0, -1, -1); |
---|
570 | if (k > 1) |
---|
571 | { |
---|
572 | /* the matrix to perform Bareiss with */ |
---|
573 | long *tempMatrix=new long[k * k]; |
---|
574 | /* copy correct set of entries from _intMatrix to tempMatrix */ |
---|
575 | int i = 0; |
---|
576 | for (int r = 0; r < k; r++) |
---|
577 | for (int c = 0; c < k; c++) |
---|
578 | { |
---|
579 | e = getEntry(theRows[r], theColumns[c]); |
---|
580 | if (characteristic != 0) e = e % characteristic; |
---|
581 | tempMatrix[i++] = e; |
---|
582 | } |
---|
583 | /* Bareiss algorithm operating on tempMatrix which is at least 2x2 */ |
---|
584 | int sign = 1; /* This will store the correct sign resulting |
---|
585 | from permuting the rows of tempMatrix. */ |
---|
586 | int *rowPermutation=new int[k]; |
---|
587 | /* This is for storing the permutation of rows |
---|
588 | resulting from searching for a non-zero |
---|
589 | pivot element. */ |
---|
590 | for (int i = 0; i < k; i++) rowPermutation[i] = i; |
---|
591 | int divisor = 1; /* the Bareiss divisor */ |
---|
592 | for (int r = 0; r <= k - 2; r++) |
---|
593 | { |
---|
594 | /* look for a non-zero entry in column r: */ |
---|
595 | int i = r; |
---|
596 | while ((i < k) && (tempMatrix[rowPermutation[i] * k + r] == 0)) |
---|
597 | i++; |
---|
598 | if (i == k) |
---|
599 | /* There is no non-zero entry; hence the minor is zero. */ |
---|
600 | return IntMinorValue(0, 0, 0, 0, 0, -1, -1); |
---|
601 | if (i != r) |
---|
602 | { |
---|
603 | /* We swap the rows with indices r and i: */ |
---|
604 | int j = rowPermutation[i]; |
---|
605 | rowPermutation[i] = rowPermutation[r]; |
---|
606 | rowPermutation[r] = j; |
---|
607 | /* Now we know that tempMatrix[rowPermutation[r] * k + r] is not zero. |
---|
608 | But carefull; we have to negate the sign, as there is always an odd |
---|
609 | number of row transpositions to swap two given rows of a matrix. */ |
---|
610 | sign = -sign; |
---|
611 | } |
---|
612 | if (r >= 1) divisor = tempMatrix[rowPermutation[r - 1] * k + r - 1]; |
---|
613 | for (int rr = r + 1; rr < k; rr++) |
---|
614 | for (int cc = r + 1; cc < k; cc++) |
---|
615 | { |
---|
616 | e = rowPermutation[rr] * k + cc; |
---|
617 | /* Attention: The following may cause an overflow and |
---|
618 | thus a wrong result: */ |
---|
619 | tempMatrix[e] = tempMatrix[e] * tempMatrix[rowPermutation[r] * k + r] |
---|
620 | - tempMatrix[rowPermutation[r] * k + cc] |
---|
621 | * tempMatrix[rowPermutation[rr] * k + r]; |
---|
622 | /* The following is, by theory, always a division without |
---|
623 | remainder: */ |
---|
624 | tempMatrix[e] = tempMatrix[e] / divisor; |
---|
625 | if (characteristic != 0) |
---|
626 | tempMatrix[e] = tempMatrix[e] % characteristic; |
---|
627 | } |
---|
628 | delete[] rowPermutation; |
---|
629 | delete[] tempMatrix; |
---|
630 | } |
---|
631 | int theValue = sign * tempMatrix[rowPermutation[k - 1] * k + k - 1]; |
---|
632 | if (iSB != 0) theValue = getReduction(theValue, iSB); |
---|
633 | mv = IntMinorValue(theValue, 0, 0, 0, 0, -1, -1); |
---|
634 | } |
---|
635 | delete [] theRows; |
---|
636 | delete [] theColumns; |
---|
637 | return mv; |
---|
638 | } |
---|
639 | |
---|
640 | int IntMinorProcessor::getEntry (const int rowIndex, |
---|
641 | const int columnIndex) const |
---|
642 | { |
---|
643 | return _intMatrix[rowIndex * _columns + columnIndex]; |
---|
644 | } |
---|
645 | |
---|
646 | IntMinorValue IntMinorProcessor::getMinorPrivateLaplace( |
---|
647 | const int k, const MinorKey& mk, |
---|
648 | const bool multipleMinors, |
---|
649 | Cache<MinorKey, IntMinorValue>& cch, |
---|
650 | const int characteristic, const ideal& iSB) |
---|
651 | { |
---|
652 | assert(k > 0); /* k is the minor's dimension; the minor must be at least |
---|
653 | 1x1 */ |
---|
654 | /* The method works by recursion, and using Lapace's Theorem along |
---|
655 | the row/column with the most zeros. */ |
---|
656 | if (k == 1) |
---|
657 | { |
---|
658 | int e = getEntry(mk.getAbsoluteRowIndex(0), mk.getAbsoluteColumnIndex(0)); |
---|
659 | if (characteristic != 0) e = e % characteristic; |
---|
660 | if (iSB != 0) e = getReduction(e, iSB); |
---|
661 | return IntMinorValue(e, 0, 0, 0, 0, -1, -1); |
---|
662 | /* we set "-1" as, for k == 1, we do not have any cache retrievals */ |
---|
663 | } |
---|
664 | else |
---|
665 | { |
---|
666 | int b = getBestLine(k, mk); /* row or column with |
---|
667 | most zeros */ |
---|
668 | int result = 0; /* This will contain the |
---|
669 | value of the minor. */ |
---|
670 | int s = 0; int m = 0; int as = 0; int am = 0; /* counters for additions |
---|
671 | and multiplications, |
---|
672 | ..."a*" for |
---|
673 | accumulated operation |
---|
674 | counters */ |
---|
675 | IntMinorValue mv(0, 0, 0, 0, 0, 0, 0); /* for storing all |
---|
676 | intermediate minors */ |
---|
677 | bool hadNonZeroEntry = false; |
---|
678 | if (b >= 0) |
---|
679 | { |
---|
680 | /* This means that the best line is the row with absolute (0-based) |
---|
681 | index b. |
---|
682 | Using Laplace, the sign of the contributing minors must be |
---|
683 | iterating; the initial sign depends on the relative index of b |
---|
684 | in minorRowKey: */ |
---|
685 | int sign = (mk.getRelativeRowIndex(b) % 2 == 0 ? 1 : -1); |
---|
686 | for (int c = 0; c < k; c++) /* This iterates over all involved |
---|
687 | columns. */ |
---|
688 | { |
---|
689 | int absoluteC = mk.getAbsoluteColumnIndex(c); |
---|
690 | if (getEntry(b, absoluteC) != 0) /* Only then do we have to consider |
---|
691 | this sub-determinante. */ |
---|
692 | { |
---|
693 | hadNonZeroEntry = true; |
---|
694 | /* Next MinorKey is mk with row b and column absoluteC omitted. */ |
---|
695 | MinorKey subMk = mk.getSubMinorKey(b, absoluteC); |
---|
696 | if (cch.hasKey(subMk)) |
---|
697 | { /* trying to find the result in the cache */ |
---|
698 | mv = cch.getValue(subMk); |
---|
699 | mv.incrementRetrievals(); /* once more, we made use of the cached |
---|
700 | value for key mk */ |
---|
701 | cch.put(subMk, mv); /* We need to do this with "put", as the |
---|
702 | (altered) number of retrievals may have |
---|
703 | an impact on the internal ordering among |
---|
704 | the cached entries. */ |
---|
705 | } |
---|
706 | else |
---|
707 | { |
---|
708 | mv = getMinorPrivateLaplace(k - 1, subMk, multipleMinors, cch, |
---|
709 | characteristic, iSB); /* recursive call */ |
---|
710 | /* As this minor was not in the cache, we count the additions |
---|
711 | and multiplications that we needed to perform in the |
---|
712 | recursive call: */ |
---|
713 | m += mv.getMultiplications(); |
---|
714 | s += mv.getAdditions(); |
---|
715 | } |
---|
716 | /* In any case, we count all nested operations in the accumulative |
---|
717 | counters: */ |
---|
718 | am += mv.getAccumulatedMultiplications(); |
---|
719 | as += mv.getAccumulatedAdditions(); |
---|
720 | /* adding sub-determinante times matrix entry times appropriate |
---|
721 | sign */ |
---|
722 | result += sign * mv.getResult() * getEntry(b, absoluteC); |
---|
723 | if (characteristic != 0) result = result % characteristic; |
---|
724 | s++; m++; as++; am++; /* This is for the last addition and |
---|
725 | multiplication. */ |
---|
726 | } |
---|
727 | sign = - sign; /* alternating the sign */ |
---|
728 | } |
---|
729 | } |
---|
730 | else |
---|
731 | { |
---|
732 | b = - b - 1; |
---|
733 | /* This means that the best line is the column with absolute (0-based) |
---|
734 | index b. |
---|
735 | Using Laplace, the sign of the contributing minors must be iterating; |
---|
736 | the initial sign depends on the relative index of b in |
---|
737 | minorColumnKey: */ |
---|
738 | int sign = (mk.getRelativeColumnIndex(b) % 2 == 0 ? 1 : -1); |
---|
739 | for (int r = 0; r < k; r++) /* This iterates over all involved rows. */ |
---|
740 | { |
---|
741 | int absoluteR = mk.getAbsoluteRowIndex(r); |
---|
742 | if (getEntry(absoluteR, b) != 0) /* Only then do we have to consider |
---|
743 | this sub-determinante. */ |
---|
744 | { |
---|
745 | hadNonZeroEntry = true; |
---|
746 | /* Next MinorKey is mk with row absoluteR and column b omitted. */ |
---|
747 | MinorKey subMk = mk.getSubMinorKey(absoluteR, b); |
---|
748 | if (cch.hasKey(subMk)) |
---|
749 | { /* trying to find the result in the cache */ |
---|
750 | mv = cch.getValue(subMk); |
---|
751 | mv.incrementRetrievals(); /* once more, we made use of the cached |
---|
752 | value for key mk */ |
---|
753 | cch.put(subMk, mv); /* We need to do this with "put", as the |
---|
754 | (altered) number of retrievals may have an |
---|
755 | impact on the internal ordering among the |
---|
756 | cached entries. */ |
---|
757 | } |
---|
758 | else |
---|
759 | { |
---|
760 | mv = getMinorPrivateLaplace(k - 1, subMk, multipleMinors, cch, characteristic, iSB); /* recursive call */ |
---|
761 | /* As this minor was not in the cache, we count the additions and |
---|
762 | multiplications that we needed to do in the recursive call: */ |
---|
763 | m += mv.getMultiplications(); |
---|
764 | s += mv.getAdditions(); |
---|
765 | } |
---|
766 | /* In any case, we count all nested operations in the accumulative |
---|
767 | counters: */ |
---|
768 | am += mv.getAccumulatedMultiplications(); |
---|
769 | as += mv.getAccumulatedAdditions(); |
---|
770 | /* adding sub-determinante times matrix entry times appropriate |
---|
771 | sign: */ |
---|
772 | result += sign * mv.getResult() * getEntry(absoluteR, b); |
---|
773 | if (characteristic != 0) result = result % characteristic; |
---|
774 | s++; m++; as++; am++; /* This is for the last addition and |
---|
775 | multiplication. */ |
---|
776 | } |
---|
777 | sign = - sign; /* alternating the sign */ |
---|
778 | } |
---|
779 | } |
---|
780 | /* Let's cache the newly computed minor: */ |
---|
781 | int potentialRetrievals = NumberOfRetrievals(_containerRows, |
---|
782 | _containerColumns, |
---|
783 | _minorSize, k, |
---|
784 | multipleMinors); |
---|
785 | if (hadNonZeroEntry) |
---|
786 | { |
---|
787 | s--; as--; /* first addition was 0 + ..., so we do not count it */ |
---|
788 | } |
---|
789 | if (s < 0) s = 0; /* may happen when all subminors are zero and no |
---|
790 | addition needs to be performed */ |
---|
791 | if (as < 0) as = 0; /* may happen when all subminors are zero and no |
---|
792 | addition needs to be performed */ |
---|
793 | if (iSB != 0) result = getReduction(result, iSB); |
---|
794 | IntMinorValue newMV(result, m, s, am, as, 1, potentialRetrievals); |
---|
795 | cch.put(mk, newMV); /* Here's the actual put inside the cache. */ |
---|
796 | return newMV; |
---|
797 | } |
---|
798 | } |
---|
799 | |
---|
800 | PolyMinorProcessor::PolyMinorProcessor () |
---|
801 | { |
---|
802 | _polyMatrix = 0; |
---|
803 | } |
---|
804 | |
---|
805 | poly PolyMinorProcessor::getEntry (const int rowIndex, |
---|
806 | const int columnIndex) const |
---|
807 | { |
---|
808 | return _polyMatrix[rowIndex * _columns + columnIndex]; |
---|
809 | } |
---|
810 | |
---|
811 | bool PolyMinorProcessor::isEntryZero (const int absoluteRowIndex, |
---|
812 | const int absoluteColumnIndex) const |
---|
813 | { |
---|
814 | return getEntry(absoluteRowIndex, absoluteColumnIndex) == NULL; |
---|
815 | } |
---|
816 | |
---|
817 | string PolyMinorProcessor::toString () const |
---|
818 | { |
---|
819 | char h[32]; |
---|
820 | string t = ""; |
---|
821 | string s = "PolyMinorProcessor:"; |
---|
822 | s += "\n matrix: "; |
---|
823 | sprintf(h, "%d", _rows); s += h; |
---|
824 | s += " x "; |
---|
825 | sprintf(h, "%d", _columns); s += h; |
---|
826 | int myIndexArray[500]; |
---|
827 | s += "\n considered submatrix has row indices: "; |
---|
828 | _container.getAbsoluteRowIndices(myIndexArray); |
---|
829 | for (int k = 0; k < _containerRows; k++) |
---|
830 | { |
---|
831 | if (k != 0) s += ", "; |
---|
832 | sprintf(h, "%d", myIndexArray[k]); s += h; |
---|
833 | } |
---|
834 | s += " (first row of matrix has index 0)"; |
---|
835 | s += "\n considered submatrix has column indices: "; |
---|
836 | _container.getAbsoluteColumnIndices(myIndexArray); |
---|
837 | for (int k = 0; k < _containerColumns; k++) |
---|
838 | { |
---|
839 | if (k != 0) s += ", "; |
---|
840 | sprintf(h, "%d", myIndexArray[k]); s += h; |
---|
841 | } |
---|
842 | s += " (first column of matrix has index 0)"; |
---|
843 | s += "\n size of considered minor(s): "; |
---|
844 | sprintf(h, "%d", _minorSize); s += h; |
---|
845 | s += "x"; |
---|
846 | s += h; |
---|
847 | return s; |
---|
848 | } |
---|
849 | |
---|
850 | PolyMinorProcessor::~PolyMinorProcessor() |
---|
851 | { |
---|
852 | /* free memory of _polyMatrix */ |
---|
853 | int n = _rows * _columns; |
---|
854 | for (int i = 0; i < n; i++) |
---|
855 | p_Delete(&_polyMatrix[i], currRing); |
---|
856 | delete [] _polyMatrix; _polyMatrix = 0; |
---|
857 | } |
---|
858 | |
---|
859 | void PolyMinorProcessor::defineMatrix (const int numberOfRows, |
---|
860 | const int numberOfColumns, |
---|
861 | const poly* polyMatrix) |
---|
862 | { |
---|
863 | /* free memory of _polyMatrix */ |
---|
864 | int n = _rows * _columns; |
---|
865 | for (int i = 0; i < n; i++) |
---|
866 | p_Delete(&_polyMatrix[i], currRing); |
---|
867 | delete [] _polyMatrix; _polyMatrix = 0; |
---|
868 | |
---|
869 | _rows = numberOfRows; |
---|
870 | _columns = numberOfColumns; |
---|
871 | n = _rows * _columns; |
---|
872 | |
---|
873 | /* allocate memory for new entries in _polyMatrix */ |
---|
874 | _polyMatrix = new poly[n]; |
---|
875 | |
---|
876 | /* copying values from one-dimensional method |
---|
877 | parameter "polyMatrix" */ |
---|
878 | for (int i = 0; i < n; i++) |
---|
879 | _polyMatrix[i] = pCopy(polyMatrix[i]); |
---|
880 | } |
---|
881 | |
---|
882 | PolyMinorValue PolyMinorProcessor::getMinor(const int dimension, |
---|
883 | const int* rowIndices, |
---|
884 | const int* columnIndices, |
---|
885 | Cache<MinorKey, PolyMinorValue>& c, |
---|
886 | const ideal& iSB) |
---|
887 | { |
---|
888 | defineSubMatrix(dimension, rowIndices, dimension, columnIndices); |
---|
889 | _minorSize = dimension; |
---|
890 | /* call a helper method which recursively computes the minor using the cache |
---|
891 | c: */ |
---|
892 | return getMinorPrivateLaplace(dimension, _container, false, c, iSB); |
---|
893 | } |
---|
894 | |
---|
895 | PolyMinorValue PolyMinorProcessor::getMinor(const int dimension, |
---|
896 | const int* rowIndices, |
---|
897 | const int* columnIndices, |
---|
898 | const char* algorithm, |
---|
899 | const ideal& iSB) |
---|
900 | { |
---|
901 | defineSubMatrix(dimension, rowIndices, dimension, columnIndices); |
---|
902 | _minorSize = dimension; |
---|
903 | /* call a helper method which computes the minor (without using a cache): */ |
---|
904 | if (strcmp(algorithm, "Laplace") == 0) |
---|
905 | return getMinorPrivateLaplace(_minorSize, _container, iSB); |
---|
906 | else if (strcmp(algorithm, "Bareiss") == 0) |
---|
907 | return getMinorPrivateBareiss(_minorSize, _container, iSB); |
---|
908 | else assume(false); |
---|
909 | |
---|
910 | /* The following code is never reached and just there to make the |
---|
911 | compiler happy: */ |
---|
912 | return PolyMinorValue(); |
---|
913 | } |
---|
914 | |
---|
915 | PolyMinorValue PolyMinorProcessor::getNextMinor(const char* algorithm, |
---|
916 | const ideal& iSB) |
---|
917 | { |
---|
918 | /* call a helper method which computes the minor (without using a |
---|
919 | cache): */ |
---|
920 | if (strcmp(algorithm, "Laplace") == 0) |
---|
921 | return getMinorPrivateLaplace(_minorSize, _minor, iSB); |
---|
922 | else if (strcmp(algorithm, "Bareiss") == 0) |
---|
923 | return getMinorPrivateBareiss(_minorSize, _minor, iSB); |
---|
924 | else assume(false); |
---|
925 | |
---|
926 | /* The following code is never reached and just there to make the |
---|
927 | compiler happy: */ |
---|
928 | return PolyMinorValue(); |
---|
929 | } |
---|
930 | |
---|
931 | PolyMinorValue PolyMinorProcessor::getNextMinor(Cache<MinorKey, |
---|
932 | PolyMinorValue>& c, |
---|
933 | const ideal& iSB) |
---|
934 | { |
---|
935 | /* computation with cache */ |
---|
936 | return getMinorPrivateLaplace(_minorSize, _minor, true, c, iSB); |
---|
937 | } |
---|
938 | |
---|
939 | /* assumes that all entries in polyMatrix are already reduced w.r.t. iSB */ |
---|
940 | PolyMinorValue PolyMinorProcessor::getMinorPrivateLaplace(const int k, |
---|
941 | const MinorKey& mk, |
---|
942 | const ideal& iSB) |
---|
943 | { |
---|
944 | assert(k > 0); /* k is the minor's dimension; the minor must be at least |
---|
945 | 1x1 */ |
---|
946 | /* The method works by recursion, and using Lapace's Theorem along the |
---|
947 | row/column with the most zeros. */ |
---|
948 | if (k == 1) |
---|
949 | { |
---|
950 | PolyMinorValue pmv(getEntry(mk.getAbsoluteRowIndex(0), |
---|
951 | mk.getAbsoluteColumnIndex(0)), |
---|
952 | 0, 0, 0, 0, -1, -1); |
---|
953 | /* "-1" is to signal that any statistics about the number of retrievals |
---|
954 | does not make sense, as we do not use a cache. */ |
---|
955 | return pmv; |
---|
956 | } |
---|
957 | else |
---|
958 | { |
---|
959 | /* Here, the minor must be 2x2 or larger. */ |
---|
960 | int b = getBestLine(k, mk); /* row or column with most |
---|
961 | zeros */ |
---|
962 | poly result = NULL; /* This will contain the |
---|
963 | value of the minor. */ |
---|
964 | int s = 0; int m = 0; int as = 0; int am = 0; /* counters for additions |
---|
965 | and multiplications, |
---|
966 | ..."a*" for accumulated |
---|
967 | operation counters */ |
---|
968 | bool hadNonZeroEntry = false; |
---|
969 | if (b >= 0) |
---|
970 | { |
---|
971 | /* This means that the best line is the row with absolute (0-based) |
---|
972 | index b. |
---|
973 | Using Laplace, the sign of the contributing minors must be iterating; |
---|
974 | the initial sign depends on the relative index of b in minorRowKey: */ |
---|
975 | int sign = (mk.getRelativeRowIndex(b) % 2 == 0 ? 1 : -1); |
---|
976 | poly signPoly = NULL; |
---|
977 | for (int c = 0; c < k; c++) /* This iterates over all involved columns. */ |
---|
978 | { |
---|
979 | int absoluteC = mk.getAbsoluteColumnIndex(c); |
---|
980 | if (!isEntryZero(b, absoluteC)) /* Only then do we have to consider |
---|
981 | this sub-determinante. */ |
---|
982 | { |
---|
983 | hadNonZeroEntry = true; |
---|
984 | /* Next MinorKey is mk with row b and column absoluteC omitted. */ |
---|
985 | MinorKey subMk = mk.getSubMinorKey(b, absoluteC); |
---|
986 | /* recursive call: */ |
---|
987 | PolyMinorValue mv = getMinorPrivateLaplace(k - 1, subMk, iSB); |
---|
988 | m += mv.getMultiplications(); |
---|
989 | s += mv.getAdditions(); |
---|
990 | am += mv.getAccumulatedMultiplications(); |
---|
991 | as += mv.getAccumulatedAdditions(); |
---|
992 | pDelete(&signPoly); |
---|
993 | signPoly = pISet(sign); |
---|
994 | poly temp = pp_Mult_qq(mv.getResult(), getEntry(b, absoluteC), |
---|
995 | currRing); |
---|
996 | temp = p_Mult_q(signPoly, temp, currRing); |
---|
997 | result = p_Add_q(result, temp, currRing); |
---|
998 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
999 | multsPoly++; |
---|
1000 | addsPoly++; |
---|
1001 | multsMon += pLength(mv.getResult()) * pLength(getEntry(b, absoluteC)); |
---|
1002 | #endif |
---|
1003 | signPoly = NULL; |
---|
1004 | s++; m++; as++, am++; /* This is for the addition and multiplication |
---|
1005 | in the previous lines of code. */ |
---|
1006 | } |
---|
1007 | sign = - sign; /* alternating the sign */ |
---|
1008 | } |
---|
1009 | } |
---|
1010 | else |
---|
1011 | { |
---|
1012 | b = - b - 1; |
---|
1013 | /* This means that the best line is the column with absolute (0-based) |
---|
1014 | index b. |
---|
1015 | Using Laplace, the sign of the contributing minors must be iterating; |
---|
1016 | the initial sign depends on the relative index of b in |
---|
1017 | minorColumnKey: */ |
---|
1018 | int sign = (mk.getRelativeColumnIndex(b) % 2 == 0 ? 1 : -1); |
---|
1019 | poly signPoly = NULL; |
---|
1020 | for (int r = 0; r < k; r++) /* This iterates over all involved rows. */ |
---|
1021 | { |
---|
1022 | int absoluteR = mk.getAbsoluteRowIndex(r); |
---|
1023 | if (!isEntryZero(absoluteR, b)) /* Only then do we have to consider |
---|
1024 | this sub-determinante. */ |
---|
1025 | { |
---|
1026 | hadNonZeroEntry = true; |
---|
1027 | /* This is mk with row absoluteR and column b omitted. */ |
---|
1028 | MinorKey subMk = mk.getSubMinorKey(absoluteR, b); |
---|
1029 | /* recursive call: */ |
---|
1030 | PolyMinorValue mv = getMinorPrivateLaplace(k - 1, subMk, iSB); |
---|
1031 | m += mv.getMultiplications(); |
---|
1032 | s += mv.getAdditions(); |
---|
1033 | am += mv.getAccumulatedMultiplications(); |
---|
1034 | as += mv.getAccumulatedAdditions(); |
---|
1035 | pDelete(&signPoly); |
---|
1036 | signPoly = pISet(sign); |
---|
1037 | poly temp = pp_Mult_qq(mv.getResult(), getEntry(absoluteR, b), |
---|
1038 | currRing); |
---|
1039 | temp = p_Mult_q(signPoly, temp, currRing); |
---|
1040 | result = p_Add_q(result, temp, currRing); |
---|
1041 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1042 | multsPoly++; |
---|
1043 | addsPoly++; |
---|
1044 | multsMon += pLength(mv.getResult()) * pLength(getEntry(absoluteR, b)); |
---|
1045 | #endif |
---|
1046 | signPoly = NULL; |
---|
1047 | s++; m++; as++, am++; /* This is for the addition and multiplication |
---|
1048 | in the previous lines of code. */ |
---|
1049 | } |
---|
1050 | sign = - sign; /* alternating the sign */ |
---|
1051 | } |
---|
1052 | } |
---|
1053 | if (hadNonZeroEntry) |
---|
1054 | { |
---|
1055 | s--; as--; /* first addition was 0 + ..., so we do not count it */ |
---|
1056 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1057 | addsPoly--; |
---|
1058 | #endif |
---|
1059 | } |
---|
1060 | if (s < 0) s = 0; /* may happen when all subminors are zero and no |
---|
1061 | addition needs to be performed */ |
---|
1062 | if (as < 0) as = 0; /* may happen when all subminors are zero and no |
---|
1063 | addition needs to be performed */ |
---|
1064 | if (iSB != 0) result = kNF(iSB, currRing->qideal, result); |
---|
1065 | PolyMinorValue newMV(result, m, s, am, as, -1, -1); |
---|
1066 | /* "-1" is to signal that any statistics about the number of retrievals |
---|
1067 | does not make sense, as we do not use a cache. */ |
---|
1068 | pDelete(&result); |
---|
1069 | return newMV; |
---|
1070 | } |
---|
1071 | } |
---|
1072 | |
---|
1073 | /* assumes that all entries in polyMatrix are already reduced w.r.t. iSB */ |
---|
1074 | PolyMinorValue PolyMinorProcessor::getMinorPrivateLaplace( |
---|
1075 | const int k, |
---|
1076 | const MinorKey& mk, |
---|
1077 | const bool multipleMinors, |
---|
1078 | Cache<MinorKey, PolyMinorValue>& cch, |
---|
1079 | const ideal& iSB) |
---|
1080 | { |
---|
1081 | assert(k > 0); /* k is the minor's dimension; the minor must be at least |
---|
1082 | 1x1 */ |
---|
1083 | /* The method works by recursion, and using Lapace's Theorem along |
---|
1084 | the row/column with the most zeros. */ |
---|
1085 | if (k == 1) |
---|
1086 | { |
---|
1087 | PolyMinorValue pmv(getEntry(mk.getAbsoluteRowIndex(0), |
---|
1088 | mk.getAbsoluteColumnIndex(0)), |
---|
1089 | 0, 0, 0, 0, -1, -1); |
---|
1090 | /* we set "-1" as, for k == 1, we do not have any cache retrievals */ |
---|
1091 | return pmv; |
---|
1092 | } |
---|
1093 | else |
---|
1094 | { |
---|
1095 | int b = getBestLine(k, mk); /* row or column with most |
---|
1096 | zeros */ |
---|
1097 | poly result = NULL; /* This will contain the |
---|
1098 | value of the minor. */ |
---|
1099 | int s = 0; int m = 0; int as = 0; int am = 0; /* counters for additions |
---|
1100 | and multiplications, |
---|
1101 | ..."a*" for accumulated |
---|
1102 | operation counters */ |
---|
1103 | bool hadNonZeroEntry = false; |
---|
1104 | if (b >= 0) |
---|
1105 | { |
---|
1106 | /* This means that the best line is the row with absolute (0-based) |
---|
1107 | index b. |
---|
1108 | Using Laplace, the sign of the contributing minors must be iterating; |
---|
1109 | the initial sign depends on the relative index of b in |
---|
1110 | minorRowKey: */ |
---|
1111 | int sign = (mk.getRelativeRowIndex(b) % 2 == 0 ? 1 : -1); |
---|
1112 | poly signPoly = NULL; |
---|
1113 | for (int c = 0; c < k; c++) /* This iterates over all involved columns. */ |
---|
1114 | { |
---|
1115 | int absoluteC = mk.getAbsoluteColumnIndex(c); |
---|
1116 | if (!isEntryZero(b, absoluteC)) /* Only then do we have to consider |
---|
1117 | this sub-determinante. */ |
---|
1118 | { |
---|
1119 | hadNonZeroEntry = true; |
---|
1120 | PolyMinorValue mv; /* for storing all intermediate minors */ |
---|
1121 | /* Next MinorKey is mk with row b and column absoluteC omitted. */ |
---|
1122 | MinorKey subMk = mk.getSubMinorKey(b, absoluteC); |
---|
1123 | if (cch.hasKey(subMk)) |
---|
1124 | { /* trying to find the result in the cache */ |
---|
1125 | mv = cch.getValue(subMk); |
---|
1126 | mv.incrementRetrievals(); /* once more, we made use of the cached |
---|
1127 | value for key mk */ |
---|
1128 | cch.put(subMk, mv); /* We need to do this with "put", as the |
---|
1129 | (altered) number of retrievals may have an |
---|
1130 | impact on the internal ordering among cache |
---|
1131 | entries. */ |
---|
1132 | } |
---|
1133 | else |
---|
1134 | { |
---|
1135 | /* recursive call: */ |
---|
1136 | mv = getMinorPrivateLaplace(k - 1, subMk, multipleMinors, cch, |
---|
1137 | iSB); |
---|
1138 | /* As this minor was not in the cache, we count the additions and |
---|
1139 | multiplications that we needed to do in the recursive call: */ |
---|
1140 | m += mv.getMultiplications(); |
---|
1141 | s += mv.getAdditions(); |
---|
1142 | } |
---|
1143 | /* In any case, we count all nested operations in the accumulative |
---|
1144 | counters: */ |
---|
1145 | am += mv.getAccumulatedMultiplications(); |
---|
1146 | as += mv.getAccumulatedAdditions(); |
---|
1147 | pDelete(&signPoly); |
---|
1148 | signPoly = pISet(sign); |
---|
1149 | poly temp = pp_Mult_qq(mv.getResult(), getEntry(b, absoluteC), |
---|
1150 | currRing); |
---|
1151 | temp = p_Mult_q(signPoly, temp, currRing); |
---|
1152 | result = p_Add_q(result, temp, currRing); |
---|
1153 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1154 | multsPoly++; |
---|
1155 | addsPoly++; |
---|
1156 | multsMon += pLength(mv.getResult()) * pLength(getEntry(b, absoluteC)); |
---|
1157 | #endif |
---|
1158 | signPoly = NULL; |
---|
1159 | s++; m++; as++; am++; /* This is for the addition and multiplication |
---|
1160 | in the previous lines of code. */ |
---|
1161 | } |
---|
1162 | sign = - sign; /* alternating the sign */ |
---|
1163 | } |
---|
1164 | } |
---|
1165 | else |
---|
1166 | { |
---|
1167 | b = - b - 1; |
---|
1168 | /* This means that the best line is the column with absolute (0-based) |
---|
1169 | index b. |
---|
1170 | Using Laplace, the sign of the contributing minors must be iterating; |
---|
1171 | the initial sign depends on the relative index of b in |
---|
1172 | minorColumnKey: */ |
---|
1173 | int sign = (mk.getRelativeColumnIndex(b) % 2 == 0 ? 1 : -1); |
---|
1174 | poly signPoly = NULL; |
---|
1175 | for (int r = 0; r < k; r++) /* This iterates over all involved rows. */ |
---|
1176 | { |
---|
1177 | int absoluteR = mk.getAbsoluteRowIndex(r); |
---|
1178 | if (!isEntryZero(absoluteR, b)) /* Only then do we have to consider |
---|
1179 | this sub-determinante. */ |
---|
1180 | { |
---|
1181 | hadNonZeroEntry = true; |
---|
1182 | PolyMinorValue mv; /* for storing all intermediate minors */ |
---|
1183 | /* Next MinorKey is mk with row absoluteR and column b omitted. */ |
---|
1184 | MinorKey subMk = mk.getSubMinorKey(absoluteR, b); |
---|
1185 | if (cch.hasKey(subMk)) |
---|
1186 | { /* trying to find the result in the cache */ |
---|
1187 | mv = cch.getValue(subMk); |
---|
1188 | mv.incrementRetrievals(); /* once more, we made use of the cached |
---|
1189 | value for key mk */ |
---|
1190 | cch.put(subMk, mv); /* We need to do this with "put", as the |
---|
1191 | (altered) number of retrievals may have an |
---|
1192 | impact on the internal ordering among the |
---|
1193 | cached entries. */ |
---|
1194 | } |
---|
1195 | else |
---|
1196 | { |
---|
1197 | mv = getMinorPrivateLaplace(k - 1, subMk, multipleMinors, cch, |
---|
1198 | iSB); /* recursive call */ |
---|
1199 | /* As this minor was not in the cache, we count the additions and |
---|
1200 | multiplications that we needed to do in the recursive call: */ |
---|
1201 | m += mv.getMultiplications(); |
---|
1202 | s += mv.getAdditions(); |
---|
1203 | } |
---|
1204 | /* In any case, we count all nested operations in the accumulative |
---|
1205 | counters: */ |
---|
1206 | am += mv.getAccumulatedMultiplications(); |
---|
1207 | as += mv.getAccumulatedAdditions(); |
---|
1208 | pDelete(&signPoly); |
---|
1209 | signPoly = pISet(sign); |
---|
1210 | poly temp = pp_Mult_qq(mv.getResult(), getEntry(absoluteR, b), |
---|
1211 | currRing); |
---|
1212 | temp = p_Mult_q(signPoly, temp, currRing); |
---|
1213 | result = p_Add_q(result, temp, currRing); |
---|
1214 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1215 | multsPoly++; |
---|
1216 | addsPoly++; |
---|
1217 | multsMon += pLength(mv.getResult()) * pLength(getEntry(absoluteR, b)); |
---|
1218 | #endif |
---|
1219 | signPoly = NULL; |
---|
1220 | s++; m++; as++; am++; /* This is for the addition and multiplication |
---|
1221 | in the previous lines of code. */ |
---|
1222 | } |
---|
1223 | sign = - sign; /* alternating the sign */ |
---|
1224 | } |
---|
1225 | } |
---|
1226 | /* Let's cache the newly computed minor: */ |
---|
1227 | int potentialRetrievals = NumberOfRetrievals(_containerRows, |
---|
1228 | _containerColumns, |
---|
1229 | _minorSize, |
---|
1230 | k, |
---|
1231 | multipleMinors); |
---|
1232 | if (hadNonZeroEntry) |
---|
1233 | { |
---|
1234 | s--; as--; /* first addition was 0 + ..., so we do not count it */ |
---|
1235 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1236 | addsPoly--; |
---|
1237 | #endif |
---|
1238 | } |
---|
1239 | if (s < 0) s = 0; /* may happen when all subminors are zero and no |
---|
1240 | addition needs to be performed */ |
---|
1241 | if (as < 0) as = 0; /* may happen when all subminors are zero and no |
---|
1242 | addition needs to be performed */ |
---|
1243 | if (iSB != 0) result = kNF(iSB, currRing->qideal, result); |
---|
1244 | PolyMinorValue newMV(result, m, s, am, as, 1, potentialRetrievals); |
---|
1245 | pDelete(&result); result = NULL; |
---|
1246 | cch.put(mk, newMV); /* Here's the actual put inside the cache. */ |
---|
1247 | return newMV; |
---|
1248 | } |
---|
1249 | } |
---|
1250 | |
---|
1251 | /* This can only be used in the case of coefficients coming from a field |
---|
1252 | or at least an integral domain. */ |
---|
1253 | void addOperationBucket(poly& f1, poly& f2, kBucket_pt& bucket) |
---|
1254 | { |
---|
1255 | /* fills all terms of f1 * f2 into the bucket */ |
---|
1256 | poly a = f1; poly b = f2; |
---|
1257 | int aLen = pLength(a); int bLen = pLength(b); |
---|
1258 | if (aLen > bLen) |
---|
1259 | { |
---|
1260 | b = f1; a = f2; bLen = aLen; |
---|
1261 | } |
---|
1262 | pNormalize(b); |
---|
1263 | |
---|
1264 | while (a != NULL) |
---|
1265 | { |
---|
1266 | /* The next line actually uses only LT(a): */ |
---|
1267 | kBucket_Plus_mm_Mult_pp(bucket, a, b, bLen); |
---|
1268 | a = pNext(a); |
---|
1269 | } |
---|
1270 | } |
---|
1271 | |
---|
1272 | /* computes the polynomial (p1 * p2 - p3 * p4) and puts result into p1; |
---|
1273 | the method destroys the old value of p1; |
---|
1274 | p2, p3, and p4 may be pNormalize-d but must, apart from that, |
---|
1275 | not be changed; |
---|
1276 | This can only be used in the case of coefficients coming from a field |
---|
1277 | or at least an integral domain. */ |
---|
1278 | void elimOperationBucketNoDiv(poly &p1, poly &p2, poly &p3, poly &p4) |
---|
1279 | { |
---|
1280 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1281 | if ((pLength(p1) != 0) && (pLength(p2) != 0)) |
---|
1282 | { |
---|
1283 | multsPoly++; |
---|
1284 | multsMon += pLength(p1) * pLength(p2); |
---|
1285 | } |
---|
1286 | if ((pLength(p3) != 0) && (pLength(p4) != 0)) |
---|
1287 | { |
---|
1288 | multsPoly++; |
---|
1289 | multsMon += pLength(p3) * pLength(p4); |
---|
1290 | } |
---|
1291 | if ((pLength(p1) != 0) && (pLength(p2) != 0) && |
---|
1292 | (pLength(p3) != 0) && (pLength(p4) != 0)) |
---|
1293 | addsPoly++; |
---|
1294 | #endif |
---|
1295 | kBucket_pt myBucket = kBucketCreate(); |
---|
1296 | addOperationBucket(p1, p2, myBucket); |
---|
1297 | poly p3Neg = pNeg(pCopy(p3)); |
---|
1298 | addOperationBucket(p3Neg, p4, myBucket); |
---|
1299 | pDelete(&p3Neg); |
---|
1300 | pDelete(&p1); |
---|
1301 | p1 = kBucketClear(myBucket); |
---|
1302 | kBucketDestroy(&myBucket); |
---|
1303 | } |
---|
1304 | |
---|
1305 | /* computes the polynomial (p1 * p2 - p3 * p4) / p5 and puts result into p1; |
---|
1306 | the method destroys the old value of p1; |
---|
1307 | p2, p3, p4, and p5 may be pNormalize-d but must, apart from that, |
---|
1308 | not be changed; |
---|
1309 | c5 is assumed to be the leading coefficient of p5; |
---|
1310 | p5Len is assumed to be the length of p5; |
---|
1311 | This can only be used in the case of coefficients coming from a field |
---|
1312 | or at least an integral domain. */ |
---|
1313 | void elimOperationBucket(poly &p1, poly &p2, poly &p3, poly &p4, poly &p5, |
---|
1314 | number &c5, int p5Len) |
---|
1315 | { |
---|
1316 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1317 | if ((pLength(p1) != 0) && (pLength(p2) != 0)) |
---|
1318 | { |
---|
1319 | multsPoly++; |
---|
1320 | multsMon += pLength(p1) * pLength(p2); |
---|
1321 | } |
---|
1322 | if ((pLength(p3) != 0) && (pLength(p4) != 0)) |
---|
1323 | { |
---|
1324 | multsPoly++; |
---|
1325 | multsMon += pLength(p3) * pLength(p4); |
---|
1326 | } |
---|
1327 | if ((pLength(p1) != 0) && (pLength(p2) != 0) && |
---|
1328 | (pLength(p3) != 0) && (pLength(p4) != 0)) |
---|
1329 | addsPoly++; |
---|
1330 | #endif |
---|
1331 | kBucket_pt myBucket = kBucketCreate(); |
---|
1332 | addOperationBucket(p1, p2, myBucket); |
---|
1333 | poly p3Neg = pNeg(pCopy(p3)); |
---|
1334 | addOperationBucket(p3Neg, p4, myBucket); |
---|
1335 | pDelete(&p3Neg); |
---|
1336 | |
---|
1337 | /* Now, myBucket contains all terms of p1 * p2 - p3 * p4. |
---|
1338 | Now we need to perform the polynomial division myBucket / p5 |
---|
1339 | which is known to work without remainder: */ |
---|
1340 | pDelete(&p1); poly helperPoly = NULL; |
---|
1341 | |
---|
1342 | poly bucketLm = pCopy(kBucketGetLm(myBucket)); |
---|
1343 | while (bucketLm != NULL) |
---|
1344 | { |
---|
1345 | /* divide bucketLm by the leading term of p5 and put result into bucketLm; |
---|
1346 | we start with the coefficients; |
---|
1347 | note that bucketLm will always represent a term */ |
---|
1348 | number coeff = nDiv(pGetCoeff(bucketLm), c5); |
---|
1349 | nNormalize(coeff); |
---|
1350 | pSetCoeff(bucketLm, coeff); |
---|
1351 | /* subtract exponent vector of p5 from that of quotient; modifies |
---|
1352 | quotient */ |
---|
1353 | p_ExpVectorSub(bucketLm, p5, currRing); |
---|
1354 | #ifdef COUNT_AND_PRINT_OPERATIONS |
---|
1355 | divsMon++; |
---|
1356 | multsMonForDiv += p5Len; |
---|
1357 | multsMon += p5Len; |
---|
1358 | savedMultsMFD++; |
---|
1359 | multsPoly++; |
---|
1360 | multsPolyForDiv++; |
---|
1361 | addsPoly++; |
---|
1362 | addsPolyForDiv++; |
---|
1363 | #endif |
---|
1364 | kBucket_Minus_m_Mult_p(myBucket, bucketLm, p5, &p5Len); |
---|
1365 | /* The following lines make bucketLm the new leading term of p1, |
---|
1366 | i.e., put bucketLm in front of everything which is already in p1. |
---|
1367 | Thus, after the while loop, we need to revert p1. */ |
---|
1368 | helperPoly = bucketLm; |
---|
1369 | helperPoly->next = p1; |
---|
1370 | p1 = helperPoly; |
---|
1371 | |
---|
1372 | bucketLm = pCopy(kBucketGetLm(myBucket)); |
---|
1373 | } |
---|
1374 | p1 = pReverse(p1); |
---|
1375 | kBucketDestroy(&myBucket); |
---|
1376 | } |
---|
1377 | |
---|
1378 | /* assumes that all entries in polyMatrix are already reduced w.r.t. iSB |
---|
1379 | This can only be used in the case of coefficients coming from a field!!! */ |
---|
1380 | PolyMinorValue PolyMinorProcessor::getMinorPrivateBareiss(const int k, |
---|
1381 | const MinorKey& mk, |
---|
1382 | const ideal& iSB) |
---|
1383 | { |
---|
1384 | assert(k > 0); /* k is the minor's dimension; the minor must be at least |
---|
1385 | 1x1 */ |
---|
1386 | int *theRows=new int[k]; mk.getAbsoluteRowIndices(theRows); |
---|
1387 | int *theColumns=new int[k]; mk.getAbsoluteColumnIndices(theColumns); |
---|
1388 | if (k == 1) |
---|
1389 | { |
---|
1390 | PolyMinorValue tmp=PolyMinorValue(getEntry(theRows[0], theColumns[0]), |
---|
1391 | 0, 0, 0, 0, -1, -1); |
---|
1392 | delete[] theColumns; |
---|
1393 | delete[] theRows; |
---|
1394 | return tmp; |
---|
1395 | } |
---|
1396 | else /* k > 0 */ |
---|
1397 | { |
---|
1398 | /* the matrix to perform Bareiss with */ |
---|
1399 | poly* tempMatrix = (poly*)omAlloc(k * k * sizeof(poly)); |
---|
1400 | /* copy correct set of entries from _polyMatrix to tempMatrix */ |
---|
1401 | int i = 0; |
---|
1402 | for (int r = 0; r < k; r++) |
---|
1403 | for (int c = 0; c < k; c++) |
---|
1404 | tempMatrix[i++] = pCopy(getEntry(theRows[r], theColumns[c])); |
---|
1405 | |
---|
1406 | /* Bareiss algorithm operating on tempMatrix which is at least 2x2 */ |
---|
1407 | int sign = 1; /* This will store the correct sign resulting from |
---|
1408 | permuting the rows of tempMatrix. */ |
---|
1409 | int *rowPermutation=new int[k]; /* This is for storing the permutation of rows |
---|
1410 | resulting from searching for a non-zero pivot |
---|
1411 | element. */ |
---|
1412 | for (int i = 0; i < k; i++) rowPermutation[i] = i; |
---|
1413 | poly divisor = NULL; |
---|
1414 | int divisorLength = 0; |
---|
1415 | number divisorLC; |
---|
1416 | for (int r = 0; r <= k - 2; r++) |
---|
1417 | { |
---|
1418 | /* look for a non-zero entry in column r, rows = r .. (k - 1) |
---|
1419 | s.t. the polynomial has least complexity: */ |
---|
1420 | int minComplexity = -1; int complexity = 0; int bestRow = -1; |
---|
1421 | poly pp = NULL; |
---|
1422 | for (int i = r; i < k; i++) |
---|
1423 | { |
---|
1424 | pp = tempMatrix[rowPermutation[i] * k + r]; |
---|
1425 | if (pp != NULL) |
---|
1426 | { |
---|
1427 | if (minComplexity == -1) |
---|
1428 | { |
---|
1429 | minComplexity = pSize(pp); |
---|
1430 | bestRow = i; |
---|
1431 | } |
---|
1432 | else |
---|
1433 | { |
---|
1434 | complexity = 0; |
---|
1435 | while ((pp != NULL) && (complexity < minComplexity)) |
---|
1436 | { |
---|
1437 | complexity += nSize(pGetCoeff(pp)); pp = pNext(pp); |
---|
1438 | } |
---|
1439 | if (complexity < minComplexity) |
---|
1440 | { |
---|
1441 | minComplexity = complexity; |
---|
1442 | bestRow = i; |
---|
1443 | } |
---|
1444 | } |
---|
1445 | if (minComplexity <= 1) break; /* terminate the search */ |
---|
1446 | } |
---|
1447 | } |
---|
1448 | if (bestRow == -1) |
---|
1449 | { |
---|
1450 | /* There is no non-zero entry; hence the minor is zero. */ |
---|
1451 | for (int i = 0; i < k * k; i++) pDelete(&tempMatrix[i]); |
---|
1452 | return PolyMinorValue(NULL, 0, 0, 0, 0, -1, -1); |
---|
1453 | } |
---|
1454 | pNormalize(tempMatrix[rowPermutation[bestRow] * k + r]); |
---|
1455 | if (bestRow != r) |
---|
1456 | { |
---|
1457 | /* We swap the rows with indices r and i: */ |
---|
1458 | int j = rowPermutation[bestRow]; |
---|
1459 | rowPermutation[bestRow] = rowPermutation[r]; |
---|
1460 | rowPermutation[r] = j; |
---|
1461 | /* Now we know that tempMatrix[rowPermutation[r] * k + r] is not zero. |
---|
1462 | But carefull; we have to negate the sign, as there is always an odd |
---|
1463 | number of row transpositions to swap two given rows of a matrix. */ |
---|
1464 | sign = -sign; |
---|
1465 | } |
---|
1466 | #if (defined COUNT_AND_PRINT_OPERATIONS) && (COUNT_AND_PRINT_OPERATIONS > 2) |
---|
1467 | poly w = NULL; int wl = 0; |
---|
1468 | printf("matrix after %d steps:\n", r); |
---|
1469 | for (int u = 0; u < k; u++) |
---|
1470 | { |
---|
1471 | for (int v = 0; v < k; v++) |
---|
1472 | { |
---|
1473 | if ((v < r) && (u > v)) |
---|
1474 | wl = 0; |
---|
1475 | else |
---|
1476 | { |
---|
1477 | w = tempMatrix[rowPermutation[u] * k + v]; |
---|
1478 | wl = pLength(w); |
---|
1479 | } |
---|
1480 | printf("%5d ", wl); |
---|
1481 | } |
---|
1482 | printf("\n"); |
---|
1483 | } |
---|
1484 | printCounters ("", false); |
---|
1485 | #endif |
---|
1486 | if (r != 0) |
---|
1487 | { |
---|
1488 | divisor = tempMatrix[rowPermutation[r - 1] * k + r - 1]; |
---|
1489 | pNormalize(divisor); |
---|
1490 | divisorLength = pLength(divisor); |
---|
1491 | divisorLC = pGetCoeff(divisor); |
---|
1492 | } |
---|
1493 | for (int rr = r + 1; rr < k; rr++) |
---|
1494 | for (int cc = r + 1; cc < k; cc++) |
---|
1495 | { |
---|
1496 | if (r == 0) |
---|
1497 | elimOperationBucketNoDiv(tempMatrix[rowPermutation[rr] * k + cc], |
---|
1498 | tempMatrix[rowPermutation[r] * k + r], |
---|
1499 | tempMatrix[rowPermutation[r] * k + cc], |
---|
1500 | tempMatrix[rowPermutation[rr] * k + r]); |
---|
1501 | else |
---|
1502 | elimOperationBucket(tempMatrix[rowPermutation[rr] * k + cc], |
---|
1503 | tempMatrix[rowPermutation[r] * k + r], |
---|
1504 | tempMatrix[rowPermutation[r] * k + cc], |
---|
1505 | tempMatrix[rowPermutation[rr] * k + r], |
---|
1506 | divisor, divisorLC, divisorLength); |
---|
1507 | } |
---|
1508 | } |
---|
1509 | #if (defined COUNT_AND_PRINT_OPERATIONS) && (COUNT_AND_PRINT_OPERATIONS > 2) |
---|
1510 | poly w = NULL; int wl = 0; |
---|
1511 | printf("matrix after %d steps:\n", k - 1); |
---|
1512 | for (int u = 0; u < k; u++) |
---|
1513 | { |
---|
1514 | for (int v = 0; v < k; v++) |
---|
1515 | { |
---|
1516 | if ((v < k - 1) && (u > v)) |
---|
1517 | wl = 0; |
---|
1518 | else |
---|
1519 | { |
---|
1520 | w = tempMatrix[rowPermutation[u] * k + v]; |
---|
1521 | wl = pLength(w); |
---|
1522 | } |
---|
1523 | printf("%5d ", wl); |
---|
1524 | } |
---|
1525 | printf("\n"); |
---|
1526 | } |
---|
1527 | #endif |
---|
1528 | poly result = tempMatrix[rowPermutation[k - 1] * k + k - 1]; |
---|
1529 | if (sign == -1) result = pNeg(result); |
---|
1530 | if (iSB != 0) result = kNF(iSB, currRing->qideal, result); |
---|
1531 | PolyMinorValue mv(result, 0, 0, 0, 0, -1, -1); |
---|
1532 | for (int i = 0; i < k * k; i++) pDelete(&tempMatrix[i]); |
---|
1533 | omFreeSize(tempMatrix, k * k * sizeof(poly)); |
---|
1534 | delete[] rowPermutation; |
---|
1535 | delete[] theColumns; |
---|
1536 | delete[] theRows; |
---|
1537 | return mv; |
---|
1538 | } |
---|
1539 | } |
---|
1540 | |
---|