Grammalecte  Check-in [6ee195e8d3]

Overview
Comment:[graphspell] JaroWinkler: modify variable names
Downloads: Tarball | ZIP archive | SQL archive
Timelines: family | ancestors | descendants | both | trunk | graphspell
Files: files | file ages | folders
SHA3-256: 6ee195e8d3e283062d755428846877d8801d50f9f31d8b44bbeda69d4c2bbacf
User & Date: olr on 2021-02-10 08:45:16
Other Links: manifest | tags
Context
2021-02-10
10:14
[fr] faux positifs et ajustements check-in: 4698a4f99c user: olr tags: trunk, fr
08:45
[graphspell] JaroWinkler: modify variable names check-in: 6ee195e8d3 user: olr tags: trunk, graphspell
2021-02-09
16:23
[graphspell] suggestion mechanism: extend search further check-in: d2cc0989db user: olr tags: trunk, graphspell
Changes

Modified graphspell/str_transform.py from [3aad4bb295] to [d580e06cf9].

110
111
112
113
114
115
116
117

118
119
120
121
122
123
124
125
126








127
128
129
130
131
132
133
134
135
136
137
138










139
140
141
142

143
144
145
146
147
148
149
150
151





152
153
154
155
156



157
158
159
160
161
162
163
164
165
166
167









168
169
170

171
172
173
174


175
176
177

178
179

180
181

182
183
184

185
186
187
188
189
190
191



192
193
194
195
196
197
198
110
111
112
113
114
115
116

117
118








119
120
121
122
123
124
125
126
127
128










129
130
131
132
133
134
135
136
137
138
139
140
141

142
143
144
145
146





147
148
149
150
151
152
153



154
155
156
157
158









159
160
161
162
163
164
165
166
167
168
169

170
171
172


173
174
175
176

177
178

179
180

181
182
183

184
185
186
187
188



189
190
191
192
193
194
195
196
197
198







-
+

-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+


-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+



-
+




-
-
-
-
-
+
+
+
+
+


-
-
-
+
+
+


-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+


-
+


-
-
+
+


-
+

-
+

-
+


-
+




-
-
-
+
+
+







                d[i-1, j-1] + nCost,    # Substitution
            )
            if i and j and s1[i] == s2[j-1] and s1[i-1] == s2[j]:
                d[i, j] = min(d[i, j], d[i-2, j-2] + nCost)     # Transposition
    return d[nLen1-1, nLen2-1]


def distanceJaroWinkler (a, b, boost = .666):
def distanceJaroWinkler (sWord1, sWord2, fBoost = .666):
    # https://github.com/thsig/jaro-winkler-JS
    #if (a == b): return 1.0
    a_len = len(a)
    b_len = len(b)
    nMax = max(a_len, b_len)
    a_flag = [None for _ in range(nMax)]
    b_flag = [None for _ in range(nMax)]
    search_range = (max(a_len, b_len) // 2) - 1
    minv = min(a_len, b_len)
    #if (sWord1 == sWord2): return 1.0
    nLen1 = len(sWord1)
    nLen2 = len(sWord2)
    nMax = max(nLen1, nLen2)
    aFlags1 = [ None for _ in range(nMax) ]
    aFlags2 = [ None for _ in range(nMax) ]
    nSearchRange = (max(nLen1, nLen2) // 2) - 1
    nMinLen = min(nLen1, nLen2)

    # Looking only within the search range, count and flag the matched pairs.
    Num_com = 0
    yl1 = b_len - 1
    for i in range(a_len):
        lowlim = i - search_range  if i >= search_range  else 0
        hilim  = i + search_range  if (i + search_range) <= yl1  else yl1
        for j in range(lowlim, hilim+1):
            if b_flag[j] != 1 and a[j:j+1] == b[i:i+1]:
                a_flag[j] = 1
                b_flag[i] = 1
                Num_com += 1
    nCommon = 0
    yl1 = nLen2 - 1
    for i in range(nLen1):
        nLowLim = i - nSearchRange  if i >= nSearchRange  else 0
        nHiLim  = i + nSearchRange  if (i + nSearchRange) <= yl1  else yl1
        for j in range(nLowLim, nHiLim+1):
            if aFlags2[j] != 1 and sWord1[j:j+1] == sWord2[i:i+1]:
                aFlags1[j] = 1
                aFlags2[i] = 1
                nCommon += 1
                break

    # Return if no characters in common
    if Num_com == 0:
    if nCommon == 0:
        return 0.0

    # Count the number of transpositions
    k = 0
    N_trans = 0
    for i in range(a_len):
        if a_flag[i] == 1:
            for j in range(k, b_len):
                if b_flag[j] == 1:
    nTrans = 0
    for i in range(nLen1):
        if aFlags1[i] == 1:
            for j in range(k, nLen2):
                if aFlags2[j] == 1:
                    k = j + 1
                    break
            if a[i] != b[j]:
                N_trans += 1
    N_trans = N_trans // 2
            if sWord1[i] != sWord2[j]:
                nTrans += 1
    nTrans = nTrans // 2

    # Adjust for similarities in nonmatched characters
    N_simi = 0
    if minv > Num_com:
        for i in range(a_len):
            if not a_flag[i]:
                for j in range(b_len):
                    if not b_flag[j]:
                        if a[i] in dDistanceBetweenChars and b[j] in dDistanceBetweenChars[a[i]]:
                            N_simi += dDistanceBetweenChars[a[i]][b[j]]
                            b_flag[j] = 2
    nSimi = 0
    if nMinLen > nCommon:
        for i in range(nLen1):
            if not aFlags1[i]:
                for j in range(nLen2):
                    if not aFlags2[j]:
                        if sWord1[i] in dDistanceBetweenChars and sWord2[j] in dDistanceBetweenChars[sWord1[i]]:
                            nSimi += dDistanceBetweenChars[sWord1[i]][sWord2[j]]
                            aFlags2[j] = 2
                            break

    Num_sim = (N_simi / 10.0) + Num_com
    fSim = (nSimi / 10.0) + nCommon

    # Main weight computation
    weight = Num_sim / a_len + Num_sim / b_len + (Num_com - N_trans) / Num_com
    weight = weight / 3
    fWeight = fSim / nLen1 + fSim / nLen2 + (nCommon - nTrans) / nCommon
    fWeight = fWeight / 3

    # Continue to boost the weight if the strings are similar
    if weight > boost:
    if fWeight > fBoost:
        # Adjust for having up to the first 4 characters in common
        j = 4  if minv >= 4  else minv
        j = 4  if nMinLen >= 4  else nMinLen
        i = 0
        while i < j  and a[i] == b[i]:
        while i < j  and sWord1[i] == sWord2[i]:
            i += 1
        if i:
            weight += i * 0.1 * (1.0 - weight)
            fWeight += i * 0.1 * (1.0 - fWeight)
        # Adjust for long strings.
        # After agreeing beginning chars, at least two more must agree
        # and the agreeing characters must be more than half of the
        # remaining characters.
        if minv > 4  and  Num_com > i + 1  and  2 * Num_com >= minv + i:
            weight += (1 - weight) * ((Num_com - i - 1) / (a_len * b_len - i*2 + 2))
    return weight
        if nMinLen > 4  and  nCommon > i + 1  and  2 * nCommon >= nMinLen + i:
            fWeight += (1 - fWeight) * ((nCommon - i - 1) / (nLen1 * nLen2 - i*2 + 2))
    return fWeight


def distanceSift4 (s1, s2, nMaxOffset=5):
    "implementation of general Sift4."
    # https://siderite.blogspot.com/2014/11/super-fast-and-accurate-string-distance.html
    if not s1:
        return len(s2)