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## Side by Side Diff: Modules/_decimal/libmpdec/literature/matrix-transform.txt

Issue 7652: Merge C version of decimal into py3k.
Patch Set: Created 7 years, 8 months ago
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6 The Matrix Fourier Transform:
7 =============================
8
9 In libmpdec, the Matrix Fourier Transform  is called four-step transform
10 after a variant that appears in . The algorithm requires that the input
11 array can be viewed as an R*C matrix.
12
13 All operations are done modulo p. For readability, the proofs drop all
14 instances of (mod p).
15
16
17 Algorithm four-step (forward transform):
18 ----------------------------------------
19
20 a := input array
21 d := len(a) = R * C
22 p := prime
23 w := primitive root of unity of the prime field
24 r := w**((p-1)/d)
25 A := output array
26
27 1) Apply a length R FNT to each column.
28
29 2) Multiply each matrix element (addressed by j*C+m) by r**(j*m).
30
31 3) Apply a length C FNT to each row.
32
33 4) Transpose the matrix.
34
35
36 Proof (forward transform):
37 --------------------------
38
39 The algorithm can be derived starting from the regular definition of
40 the finite-field transform of length d:
41
42 d-1
43 ,----
44 \
45 A[k] = | a[l] * r**(k * l)
46 /
47 `----
48 l = 0
49
50
51 The sum can be rearranged into the sum of the sums of columns:
52
53 C-1 R-1
54 ,---- ,----
55 \ \
56 = | | a[i * C + j] * r**(k * (i * C + j))
57 / /
58 `---- `----
59 j = 0 i = 0
60
61
62 Extracting a constant from the inner sum:
63
64 C-1 R-1
65 ,---- ,----
66 \ \
67 = | r**k*j * | a[i * C + j] * r**(k * i * C)
68 / /
69 `---- `----
70 j = 0 i = 0
71
72
73 Without any loss of generality, let k = n * R + m,
74 where n < C and m < R:
75
76 C-1 R-1
77 ,---- ,----
78 \ \
79 A[n*R+m] = | r**(R*n*j) * r**(m*j) * | a[i*C+j] * r**(R*C*n*i) * r**(C* m*i)
80 / /
81 `---- `----
82 j = 0 i = 0
83
84
85 Since r = w ** ((p-1) / (R*C)):
86
87 a) r**(R*C*n*i) = w**((p-1)*n*i) = 1
88
89 b) r**(C*m*i) = w**((p-1) / R) ** (m*i) = r_R ** (m*i)
90
91 c) r**(R*n*j) = w**((p-1) / C) ** (n*j) = r_C ** (n*j)
92
93 r_R := root of the subfield of length R.
94 r_C := root of the subfield of length C.
95
96
97 C-1 R-1
98 ,---- ,----
99 \ \
100 A[n*R+m] = | r_C**(n*j) * [ r**(m*j) * | a[i*C+j] * r_R**(m*i) ]
101 / ^ /
102 `---- | `---- 1) transform the columns
103 j = 0 | i = 0
104 ^ |
105 | `-- 2) multiply
106 |
107 `-- 3) transform the rows
108
109
110 Note that the entire RHS is a function of n and m and that the results
111 for each pair (n, m) are stored in Fortran order.
112
113 Let the term in square brackets be f(m, j). Step 1) and 2) precalculate
114 the term for all (m, j). After that, the original matrix is now a lookup
115 table with the mth element in the jth column at location m * C + j.
116
117 Let the complete RHS be g(m, n). Step 3) does an in-place transform of
118 length n on all rows. After that, the original matrix is now a lookup
119 table with the mth element in the nth column at location m * C + n.
120
121 But each (m, n) pair should be written to location n * R + m. Therefore,
122 step 4) transposes the result of step 3).
123
124
125
126 Algorithm four-step (inverse transform):
127 ----------------------------------------
128
129 A := input array
130 d := len(A) = R * C
131 p := prime
132 d' := d**(p-2) # inverse of d
133 w := primitive root of unity of the prime field
134 r := w**((p-1)/d) # root of the subfield
135 r' := w**((p-1) - (p-1)/d) # inverse of r
136 a := output array
137
138 0) View the matrix as a C*R matrix.
139
140 1) Transpose the matrix, producing an R*C matrix.
141
142 2) Apply a length C FNT to each row.
143
144 3) Multiply each matrix element (addressed by i*C+n) by r**(i*n).
145
146 4) Apply a length R FNT to each column.
147
148
149 Proof (inverse transform):
150 --------------------------
151
152 The algorithm can be derived starting from the regular definition of
153 the finite-field inverse transform of length d:
154
155 d-1
156 ,----
157 \
158 a[k] = d' * | A[l] * r' ** (k * l)
159 /
160 `----
161 l = 0
162
163
164 The sum can be rearranged into the sum of the sums of columns. Note
165 that at this stage we still have a C*R matrix, so C denotes the number
166 of rows:
167
168 R-1 C-1
169 ,---- ,----
170 \ \
171 = d' * | | a[j * R + i] * r' ** (k * (j * R + i))
172 / /
173 `---- `----
174 i = 0 j = 0
175
176
177 Extracting a constant from the inner sum:
178
179 R-1 C-1
180 ,---- ,----
181 \ \
182 = d' * | r' ** (k*i) * | a[j * R + i] * r' ** (k * j * R)
183 / /
184 `---- `----
185 i = 0 j = 0
186
187
188 Without any loss of generality, let k = m * C + n,
189 where m < R and n < C:
190
191 R-1 C-1
192 ,---- ,----
193 \ \
194 A[m*C+n] = d' * | r' ** (C*m*i) * r' ** (n*i) * | a[j*R+i] * r' ** (R *C*m*j) * r' ** (R*n*j)
195 / /
196 `---- `----
197 i = 0 j = 0
198
199
200 Since r' = w**((p-1) - (p-1)/d) and d = R*C:
201
202 a) r' ** (R*C*m*j) = w**((p-1)*R*C*m*j - (p-1)*m*j) = 1
203
204 b) r' ** (C*m*i) = w**((p-1)*C - (p-1)/R) ** (m*i) = r_R' ** (m*i)
205
206 c) r' ** (R*n*j) = r_C' ** (n*j)
207
208 d) d' = d**(p-2) = (R*C) ** (p-2) = R**(p-2) * C**(p-2) = R' * C'
209
210 r_R' := inverse of the root of the subfield of length R.
211 r_C' := inverse of the root of the subfield of length C.
212 R' := inverse of R
213 C' := inverse of C
214
215
216 R-1 C-1
217 ,---- ,---- 2) transform the rows of a^T
218 \ \
219 A[m*C+n] = R' * | r_R' ** (m*i) * [ r' ** (n*i) * C' * | a[j*R+i] * r_C' ** (n*j) ]
220 / ^ / ^
221 `---- | `---- |
222 i = 0 | j = 0 |
223 ^ | `-- 1) Tran spose input matrix
224 | `-- 3) multiply to a ddress elements by
225 | i * C + j
226 `-- 3) transform the columns
227
228
229
230 Note that the entire RHS is a function of m and n and that the results
231 for each pair (m, n) are stored in C order.
232
233 Let the term in square brackets be f(n, i). Without step 1), the sum
234 would perform a length C transform on the columns of the input matrix.
235 This is a) inefficient and b) the results are needed in C order, so
236 step 1) exchanges rows and columns.
237
238 Step 2) and 3) precalculate f(n, i) for all (n, i). After that, the
239 original matrix is now a lookup table with the ith element in the nth
240 column at location i * C + n.
241
242 Let the complete RHS be g(m, n). Step 4) does an in-place transform of
243 length m on all columns. After that, the original matrix is now a lookup
244 table with the mth element in the nth column at location m * C + n,
245 which means that all A[k] = A[m * C + n] are in the correct order.
246
247
248 --
249
250  Joerg Arndt: "Matters Computational"
251 http://www.jjj.de/fxt/
252  David H. Bailey: FFTs in External or Hierarchical Memory
253 http://crd.lbl.gov/~dhbailey/dhbpapers/
254
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256
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