Comments (3)
ljwolf
commented on June 20, 2024
Could you provide a benchmark against the existing implementation & against the scipy stuff? I think we should probably (in future) default to the scipy implementation where we can.
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ljwolf
commented on June 20, 2024
If you use http://mortada.net/easily-profile-python-code-in-jupyter.html it should be real simple to see the savings. Hope that's alright.
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Ziqi-Li
commented on June 20, 2024
Thanks @ljwolf for pointing out the profiling tool
Before:
Timer unit: 1e-06 s
Total time: 19.7563 s
File: /Users/Ziqi/Desktop/developer/gwr/gwr/sel_bw.py
Function: _bw at line 281
Line # Hits Time Per Hit % Time Line Contents
==============================================================
281 def _bw(self):
282 1 5 5.0 0.0 gwr_func = lambda bw: self._fast_fit(bw,constant=self.constant)[self.criterion]
283 1 1 1.0 0.0 if self.search == 'golden_section':
284 1 989 989.0 0.0 a,c = self._init_section(self.X_glob, self.X_loc, self.coords,self.constant)
285 1 1 1.0 0.0 delta = 0.38197 #1 - (np.sqrt(5.0)-1.0)/2.0
286 1 19755331 19755331.0 100.0 self.bw = golden_section(a, c, delta, gwr_func, self.tol,self.max_iter, self.int_score)
287 elif self.search == 'interval':
288 self.bw = equal_interval(self.bw_min, self.bw_max, self.interval,gwr_func, self.int_score)
289 else:
290 raise TypeError('Unsupported computational search method ', search)
After:
Timer unit: 1e-06 s
Total time: 9.73623 s
File: /Users/Ziqi/Desktop/developer/gwr/gwr/sel_bw.py
Function: _bw at line 281
Line # Hits Time Per Hit % Time Line Contents
==============================================================
281 def _bw(self):
282 1 13 13.0 0.0 gwr_func = lambda bw: self._fast_fit(bw,constant=self.constant)[self.criterion]
283 1 1 1.0 0.0 if self.search == 'golden_section':
284 1 938 938.0 0.0 a,c = self._init_section(self.X_glob, self.X_loc, self.coords,self.constant)
285 1 1 1.0 0.0 delta = 0.38197 #1 - (np.sqrt(5.0)-1.0)/2.0
286 1 9735279 9735279.0 100.0 self.bw = golden_section(a, c, delta, gwr_func, self.tol,self.max_iter, self.int_score)
287 elif self.search == 'interval':
288 self.bw = equal_interval(self.bw_min, self.bw_max, self.interval,gwr_func, self.int_score)
289 else:
290 raise TypeError('Unsupported computational search method ', search)
19755331.0/9735279.0 ~ 2.03x speed up from golden_section()
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Related Issues (15)
- Move MGWR HOT 1
- Thoughts about adaptive gaussian HOT 2
- For fit parameters, use sklearn trailing `_` notation? HOT 1
- calling `search` modifies the method `search`, so it can only be called once. HOT 3
- Profiling for speed-up HOT 3
- Predition jpynb is broken HOT 1
- TypeError: ('Unsupported kernel function ', 'bisquare') HOT 4
- #Offset does not yet do anyhting and needs to be implemented HOT 3
- gwr is using example files that are not in libpysal (but in old pysal) HOT 1
- GWR speed-up HOT 1
- Possibility for adding a summary text for GWR diagnostics HOT 2
- Support for projected coordinates HOT 1
- Add "Global" R-squared HOT 1
- Resolve divide-by-zero issue for Gaussian GWR HOT 3
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