Performance

[krober10nd]

Hey Darren,

I used line_profiler with a decorator above the kernel _inpoly() to see if there were any hotspots we could improve...Overall great. Below is the output from line_profiler running example.py. Doesn't look like it could be improved much. As you can see, the continue if catch appears to occupy 14% of the total time.

(base) keiths-MacBook-Pro:inpoly-python Keith$ kernprof -l -v example.py INPOLY2: 2.289767026901245 Wrote profile results to example.py.lprof Timer unit: 1e-06 s

Total time: 1.26219 s File: /Users/Keith/junk/inpoly-python/inpoly/inpoly2.py Function: _inpoly at line 131

Line # Hits Time Per Hit % Time Line Contents

131 @profile 132 def inpoly(vert, node, edge, ftol, lbar): 133 """ 134 INPOLY: the local pycode version of the crossing-number 135 test. Loop over edges; do a binary-search for the first 136 vertex that intersects with the edge y-range; crossing- 137 number comparisons; break when the local y-range is met. 138
139 """ 140
141 1 11.0 11.0 0.0 feps = ftol * (lbar ** +2) 142 1 2.0 2.0 0.0 veps = ftol * (lbar ** +1) 143
144 1 27.0 27.0 0.0 stat = np.full(vert.shape[0], False, dtype=np.bool) 145 1 12.0 12.0 0.0 bnds = np.full(vert.shape[0], False, dtype=np.bool) 146
147 # ----------------------------------- compute y-range overlap 148 1 47.0 47.0 0.0 XONE = node[edge[:, 0], 0] 149 1 42.0 42.0 0.0 XTWO = node[edge[:, 1], 0] 150 1 86.0 86.0 0.0 YONE = node[edge[:, 0], 1] 151 1 80.0 80.0 0.0 YTWO = node[edge[:, 1], 1] 152
153 1 66.0 66.0 0.0 XMIN = np.minimum(XONE, XTWO) 154 1 83.0 83.0 0.0 XMAX = np.maximum(XONE, XTWO) 155
156 1 62.0 62.0 0.0 XMAX = XMAX + veps 157 1 10.0 10.0 0.0 YMIN = YONE - veps 158 1 46.0 46.0 0.0 YMAX = YTWO + veps 159
160 1 51.0 51.0 0.0 YDEL = YTWO - YONE 161 1 44.0 44.0 0.0 XDEL = XTWO - XONE 162
163 1 750.0 750.0 0.1 ione = np.searchsorted(vert[:, 1], YMIN, "left") 164 1 826.0 826.0 0.1 itwo = np.searchsorted(vert[:, 1], YMAX, "right") 165
166 # ----------------------------------- loop over polygon edges 167 11000 7184.0 0.7 0.6 for epos in range(edge.shape[0]): 168
169 10999 9413.0 0.9 0.7 xone = XONE[epos] 170 10999 8909.0 0.8 0.7 xtwo = XTWO[epos] 171 10999 8982.0 0.8 0.7 yone = YONE[epos] 172 10999 8884.0 0.8 0.7 ytwo = YTWO[epos] 173
174 10999 8760.0 0.8 0.7 xmin = XMIN[epos] 175 10999 8695.0 0.8 0.7 xmax = XMAX[epos] 176
177 10999 8706.0 0.8 0.7 xdel = XDEL[epos] 178 10999 8821.0 0.8 0.7 ydel = YDEL[epos] 179
180 # ------------------------------- calc. edge-intersection 181 264806 186197.0 0.7 14.8 for jpos in range(ione[epos], itwo[epos]): 182
183 253807 182977.0 0.7 14.5 if bnds[jpos]: 184 87497 55301.0 0.6 4.4 continue 185
186 166310 147738.0 0.9 11.7 xpos = vert[jpos, 0] 187 166310 144366.0 0.9 11.4 ypos = vert[jpos, 1] 188
189 166310 117233.0 0.7 9.3 if xpos >= xmin: 190 90503 66346.0 0.7 5.3 if xpos <= xmax: 191 # ------------------- compute crossing number 192 25671 24757.0 1.0 2.0 mul1 = ydel * (xpos - xone) 193 25671 23340.0 0.9 1.8 mul2 = xdel * (ypos - yone) 194
195 25671 71918.0 2.8 5.7 if feps >= np.abs(mul2 - mul1): 196 # ------------------- BNDS -- approx. on edge 197 21998 17140.0 0.8 1.4 bnds[jpos] = True 198 21998 20768.0 0.9 1.6 stat[jpos] = True 199
200 3673 2657.0 0.7 0.2 elif (ypos == yone) and (xpos == xone): 201 # ------------------- BNDS -- match about ONE 202 bnds[jpos] = True 203 stat[jpos] = True 204
205 3673 2516.0 0.7 0.2 elif (ypos == ytwo) and (xpos == xtwo): 206 # ------------------- BNDS -- match about TWO 207 bnds[jpos] = True 208 stat[jpos] = True 209
210 3673 2889.0 0.8 0.2 elif (mul1 < mul2) and (ypos >= yone) and (ypos < ytwo): 211 # ------------------- advance crossing number 212 1819 1829.0 1.0 0.1 stat[jpos] = not stat[jpos] 213
214 75807 57239.0 0.8 4.5 elif (ypos >= yone) and (ypos < ytwo): 215 # ----------------------- advance crossing number 216 66373 56383.0 0.8 4.5 stat[jpos] = not stat[jpos] 217
218 1 1.0 1.0 0.0 return stat, bnds