21 |
import classifier, resource |
import classifier, resource |
22 |
|
|
23 |
from Thuban.Model.classgen import \ |
from Thuban.Model.classgen import \ |
24 |
GenUniformDistribution, GenSingletonsFromList, GenQuantiles, \ |
generate_uniform_distribution, generate_singletons, generate_quantiles, \ |
25 |
CustomRamp, GreyRamp, RedRamp, GreenRamp, BlueRamp, GreenToRedRamp, \ |
CustomRamp, GreyRamp, RedRamp, GreenRamp, BlueRamp, GreenToRedRamp, \ |
26 |
HotToColdRamp |
HotToColdRamp |
27 |
|
|
211 |
and max is not None \ |
and max is not None \ |
212 |
and numGroups is not None: |
and numGroups is not None: |
213 |
|
|
214 |
self.clazz = GenUniformDistribution( |
self.clazz = generate_uniform_distribution( |
215 |
min, max, numGroups, ramp, |
min, max, numGroups, ramp, |
216 |
self.type == FIELDTYPE_INT) |
self.type == FIELDTYPE_INT) |
217 |
|
|
224 |
if len(list) > 0 \ |
if len(list) > 0 \ |
225 |
and numGroups is not None: |
and numGroups is not None: |
226 |
|
|
227 |
self.clazz = GenSingletonsFromList( |
self.clazz = generate_singletons( |
228 |
list, numGroups, ramp) |
list, numGroups, ramp) |
229 |
|
|
230 |
self.parent._SetClassification(self.clazz) |
self.parent._SetClassification(self.clazz) |
238 |
delta = 1 / float(numGroups) |
delta = 1 / float(numGroups) |
239 |
percents = [delta * i for i in range(1, numGroups + 1)] |
percents = [delta * i for i in range(1, numGroups + 1)] |
240 |
adjusted, self.clazz = \ |
adjusted, self.clazz = \ |
241 |
GenQuantiles(_list, percents, ramp, _range) |
generate_quantiles(_list, percents, ramp, _range) |
242 |
|
|
243 |
if adjusted: |
if adjusted: |
244 |
dlg = wxMessageDialog(self, |
dlg = wxMessageDialog(self, |
554 |
return valid |
return valid |
555 |
|
|
556 |
def __CalcStepping(self, min, max, ngroups): |
def __CalcStepping(self, min, max, ngroups): |
|
step = (max - min) / float(ngroups) |
|
557 |
if self.fieldType == FIELDTYPE_INT: |
if self.fieldType == FIELDTYPE_INT: |
558 |
step = int(step) |
step = int((max - min + 1) / float(ngroups)) |
559 |
|
else: |
560 |
|
step = (max - min) / float(ngroups) |
561 |
|
|
562 |
return step |
return step |
563 |
|
|