I'm trying to find the optimum bandwidth for local regression (GWR), but I get an error which I don't understand how to fix. All my code runs fine until I ask for the optimum one. Any suggestions and/or explanations please? The purpose is to do spatial weighting, OLS, GWR and MGWR models, eventually though visualizing them with various maps.
# Get GWR model information
gwr_data.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 3340 entries, 0 to 3339
Data columns (total 24 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 Neighbourhood 3340 non-null object
1 PopDenKM 3340 non-null int64
2 AvInc 3340 non-null int64
3 NonImmPer 3340 non-null float64
4 ImmPer 3340 non-null float64
5 NoEduPer 3340 non-null float64
6 BacDegPer 3340 non-null float64
7 EmploymentRate 3340 non-null float64
8 UnemploymentRate 3340 non-null float64
9 TheftRate2016 3340 non-null float64
10 X 3340 non-null object
11 Y 3340 non-null object
12 NeighbourhoodName 3340 non-null object
13 Location_Type 3340 non-null object
14 Premises_Type 3340 non-null object
15 Bike_Make 3340 non-null object
16 Bike_Speed 3340 non-null int64
17 Bike_Colour 3340 non-null object
18 Cost_of_Bike 3340 non-null float64
19 Recovered 3340 non-null int64
20 Stolen 3340 non-null int64
21 Status 3340 non-null object
22 Longitude 3340 non-null object
23 Latitude 3340 non-null object
dtypes: float64(8), int64(5), object(11)
memory usage: 652.3+ KB
#Prepare dataset inputs
g_y = gwr_data['TheftRate2016'].values.reshape((-1,1))
g_X = gwr_data[['AvInc','NoEduPer','Cost_of_Bike', 'UnemploymentRate']].values
u = gwr_data['X']
v = gwr_data['Y']
g_coords = list(zip(u,v))
# Standardised our data to have mean of 0 and standard deviation of 1
g_X = (g_X - g_X.mean(axis=0)) / g_X.std(axis=0)
g_y = g_y.reshape((-1,1))
g_y = (g_y - g_y.mean(axis=0)) / g_y.std(axis=0)
# Select bandwidth for kernel
bw = mgwr.sel_bw.Sel_BW(g_coords,
g_y, # Independent variable
g_X, # Dependent variable
fixed=False, # True for fixed bandwidth and false for adaptive bandwidth
spherical=True) # Spherical coordinates (long-lat) or projected coordinates
# Calculate the optimum bandwidth for our local regression?
bw.search()
---------------------------------------------------------------------------
TypingError Traceback (most recent call last)
Input In [201], in <cell line: 2>()
1 # Calculate the optimum bandwidth for our local regression?
----> 2 bw.search()
File /opt/conda/lib/python3.9/site-packages/mgwr/sel_bw.py:319, in Sel_BW.search(self, search_method, criterion, bw_min, bw_max, interval, tol, max_iter, init_multi, tol_multi, rss_score, max_iter_multi, multi_bw_min, multi_bw_max, bws_same_times, pool, verbose)
316 self.bw_init = self.bw[
317 -1] #scalar, optimal bw from initial gwr model
318 else:
--> 319 self._bw()
320 self.sel_hist = self.bw[-1]
322 self.pool = None
File /opt/conda/lib/python3.9/site-packages/mgwr/sel_bw.py:337, in Sel_BW._bw(self)
334 a, c = self._init_section(self.X_glob, self.X_loc, self.coords,
335 self.constant)
336 delta = 0.38197 #1 - (np.sqrt(5.0)-1.0)/2.0
--> 337 self.bw = golden_section(a, c, delta, gwr_func, self.tol,
338 self.max_iter, self.int_score,
339 self.verbose)
340 elif self.search_method == 'interval':
341 self.bw = equal_interval(self.bw_min, self.bw_max, self.interval,
342 gwr_func, self.int_score, self.verbose)
File /opt/conda/lib/python3.9/site-packages/mgwr/search.py:62, in golden_section(a, c, delta, function, tol, max_iter, int_score, verbose)
60 score_b = dict[b]
61 else:
---> 62 score_b = function(b)
63 dict[b] = score_b
64 if verbose:
File /opt/conda/lib/python3.9/site-packages/mgwr/sel_bw.py:326, in Sel_BW._bw.<locals>.<lambda>(bw)
325 def _bw(self):
--> 326 gwr_func = lambda bw: getDiag[self.criterion](GWR(
327 self.coords, self.y, self.X_loc, bw, family=self.family, kernel=
328 self.kernel, fixed=self.fixed, constant=self.constant, offset=self.
329 offset, spherical=self.spherical).fit(lite=True, pool=self.pool))
331 self._optimized_function = gwr_func
333 if self.search_method == 'golden_section':
File /opt/conda/lib/python3.9/site-packages/mgwr/gwr.py:335, in GWR.fit(self, ini_params, tol, max_iter, solve, lite, pool)
332 else:
333 rslt = map(self._local_fit, range(m)) #sequential
--> 335 rslt_list = list(zip(*rslt))
336 influ = np.array(rslt_list[0]).reshape(-1, 1)
337 resid = np.array(rslt_list[1]).reshape(-1, 1)
File /opt/conda/lib/python3.9/site-packages/mgwr/gwr.py:248, in GWR._local_fit(self, i)
244 def _local_fit(self, i):
245 """
246 Local fitting at location i.
247 """
--> 248 wi = self._build_wi(i, self.bw).reshape(-1, 1) #local spatial weights
250 if isinstance(self.family, Gaussian):
251 betas, inv_xtx_xt = _compute_betas_gwr(self.y, self.X, wi)
File /opt/conda/lib/python3.9/site-packages/mgwr/gwr.py:236, in GWR._build_wi(self, i, bw)
233 def _build_wi(self, i, bw):
235 try:
--> 236 wi = Kernel(i, self.coords, bw, fixed=self.fixed,
237 function=self.kernel, points=self.points,
238 spherical=self.spherical).kernel
239 except BaseException:
240 raise # TypeError('Unsupported kernel function ', kernel)
File /opt/conda/lib/python3.9/site-packages/mgwr/kernels.py:47, in Kernel.__init__(self, i, data, bw, fixed, function, eps, ids, points, spherical)
43 def __init__(self, i, data, bw=None, fixed=True, function='triangular',
44 eps=1.0000001, ids=None, points=None, spherical=False):
46 if points is None:
---> 47 self.dvec = local_cdist(data[i], data, spherical).reshape(-1)
48 else:
49 self.dvec = local_cdist(points[i], data, spherical).reshape(-1)
File /opt/conda/lib/python3.9/site-packages/numba/core/dispatcher.py:468, in _DispatcherBase._compile_for_args(self, *args, **kws)
464 msg = (f"{str(e).rstrip()} \n\nThis error may have been caused "
465 f"by the following argument(s):\n{args_str}\n")
466 e.patch_message(msg)
--> 468 error_rewrite(e, 'typing')
469 except errors.UnsupportedError as e:
470 # Something unsupported is present in the user code, add help info
471 error_rewrite(e, 'unsupported_error')
File /opt/conda/lib/python3.9/site-packages/numba/core/dispatcher.py:409, in _DispatcherBase._compile_for_args.<locals>.error_rewrite(e, issue_type)
407 raise e
408 else:
--> 409 raise e.with_traceback(None)
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
No implementation of function Function(<built-in function sub>) found for signature:
>>> sub(array([unichr x 16], 1d, A), [unichr x 16])
There are 12 candidate implementations:
- Of which 10 did not match due to:
Overload of function 'sub': File: <numerous>: Line N/A.
With argument(s): '(array([unichr x 16], 1d, A), [unichr x 16])':
No match.
- Of which 2 did not match due to:
Operator Overload in function 'sub': File: unknown: Line unknown.
With argument(s): '(array([unichr x 16], 1d, A), [unichr x 16])':
No match for registered cases:
* (int64, int64) -> int64
* (int64, uint64) -> int64
* (uint64, int64) -> int64
* (uint64, uint64) -> uint64
* (float32, float32) -> float32
* (float64, float64) -> float64
* (complex64, complex64) -> complex64
* (complex128, complex128) -> complex128
During: typing of intrinsic-call at /opt/conda/lib/python3.9/site-packages/mgwr/kernels.py (24)
File "../../opt/conda/lib/python3.9/site-packages/mgwr/kernels.py", line 24:
def local_cdist(coords_i, coords, spherical):
<source elided>
if spherical:
dLat = np.radians(coords[:, 1] - coords_i[1])
^
