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# This program is free software under the GPL (>=v2) |
# This program is free software under the GPL (>=v2) |
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# Read the file COPYING coming with Thuban for details. |
# Read the file COPYING coming with Thuban for details. |
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""" |
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Functions to generate Classifications |
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""" |
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__version__ = "$Revision$" |
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# $Source$ |
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# $Id$ |
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import operator |
import operator |
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from color import Color |
from color import Color |
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from classification import Classification, ClassGroupSingleton, \ |
from classification import Classification, ClassGroupSingleton, \ |
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ClassGroupRange, ClassGroupProperties |
ClassGroupRange, ClassGroupProperties |
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class ClassGenerator: |
def GenSingletonsFromList(_list, numGroups, ramp): |
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"""Generate a new classification consisting solely of singletons. |
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The resulting classification will consist of at most 'numGroups' |
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groups whose group properties ramp between 'prop1' and 'prop2'. There |
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could be fewer groups if '_list' contains fewer that 'numGroups' items. |
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_list -- any object that implements the iterator interface |
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numGroups -- how many groups to generate. This can not be |
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determined while the classification is being |
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generated because the stepping values must |
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be precalculated to ramp between prop1 and prop2. |
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ramp -- an object which implements the CustomRamp interface |
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""" |
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def GenSingletonsFromList(self, list, numGroups, ramp): |
clazz = Classification() |
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"""Generate a new classification consisting solely of singletons. |
if numGroups == 0: return clazz |
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The resulting classification will consist of at most 'numGroups' |
ramp.SetNumGroups(numGroups) |
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groups whose group properties ramp between 'prop1' and 'prop2'. There |
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could be fewer groups if 'list' contains fewer that 'numGroups' items. |
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list -- any object that implements the iterator interface |
for value, prop in zip(_list, ramp): |
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clazz.AppendGroup(ClassGroupSingleton(value, prop)) |
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numGroups -- how many groups to generate. This can not be |
return clazz |
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determined while the classification is being |
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generated because the stepping values must |
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be precalculated to ramp between prop1 and prop2. |
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prop1 -- initial group property values |
def GenSingletons(min, max, numGroups, ramp): |
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prop2 -- final group property values |
clazz = Classification() |
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""" |
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clazz = Classification() |
#step = int((max - min) / float(numGroups)) |
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if numGroups == 0: return clazz |
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if numGroups > 0: |
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step = int((max - min + 1) / float(numGroups)) |
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cur_value = min |
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ramp.SetNumGroups(numGroups) |
ramp.SetNumGroups(numGroups) |
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for value, prop in zip(list, ramp): |
for prop in ramp: |
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clazz.AppendGroup(ClassGroupSingleton(value, prop)) |
clazz.AppendGroup(ClassGroupSingleton(cur_value), prop) |
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cur_value += step |
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return clazz |
return clazz |
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def GenSingletons(self, min, max, numGroups, ramp): |
def GenUniformDistribution(min, max, numGroups, |
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ramp, intStep = False): |
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"""Generate a classification with numGroups range groups |
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each with the same interval. |
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clazz = Classification() |
intStep -- force the calculated stepping to an integer. |
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Useful if the values are integers but the |
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number of groups specified doesn't evenly |
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divide (max - min). |
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""" |
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#step = int((max - min) / float(numGroups)) |
clazz = Classification() |
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if numGroups == 0: return clazz |
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if numGroups > 0: |
ramp.SetNumGroups(numGroups) |
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step = int((max - min + 1) / float(numGroups)) |
step = (max - min) / float(numGroups) |
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cur_value = min |
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ramp.SetNumGroups(numGroups) |
if intStep: |
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step = int(step) |
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for prop in ramp: |
cur_min = min |
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clazz.AppendGroup(ClassGroupSingleton(cur_value), prop) |
cur_max = cur_min + step |
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cur_value += step |
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return clazz |
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def GenUnifromDistribution(self, min, max, numGroups, |
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ramp, intStep = False): |
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"""Generate a classification with numGroups range groups |
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each with the same interval. |
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intStep -- force the calculated stepping to an integer. |
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Useful if the values are integers but the |
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number of groups specified doesn't evenly |
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divide (max - min). |
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""" |
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clazz = Classification() |
i = 0 |
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if numGroups == 0: return clazz |
end = "[" |
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for prop in ramp: |
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ramp.SetNumGroups(numGroups) |
if i == (numGroups - 1): |
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cur_max = max |
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end = "]" |
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step = (max - min) / float(numGroups) |
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if intStep: |
# this check guards against rounding issues |
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step = int(step) |
if cur_min != cur_max: |
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range = Range(("[", cur_min, cur_max, end)) |
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clazz.AppendGroup(ClassGroupRange(range, None, prop)) |
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cur_min = min |
cur_min = cur_max |
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cur_max = cur_min + step |
cur_max += step |
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i += 1 |
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i = 0 |
return clazz |
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end = "[" |
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for prop in ramp: |
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if i == (numGroups - 1): |
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cur_max = max |
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end = "]" |
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def GenQuantiles(_list, percents, ramp, _range): |
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"""Generates a Classification which has groups of ranges that |
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represent quantiles of _list at the percentages given in percents. |
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Only the values that fall within _range are considered. |
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# this check guards against rounding issues |
Returns a tuple (adjusted, Classification) where adjusted is |
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if cur_min != cur_max: |
True if the Classification does not exactly represent the given |
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range = Range("[" + str(float(cur_min)) + ";" + |
range, or if the Classification is empty. |
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str(float(cur_max)) + end) |
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clazz.AppendGroup(ClassGroupRange(range, None, prop)) |
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cur_min = cur_max |
_list -- a sort list of values |
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cur_max += step |
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i += 1 |
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return clazz |
percents -- a sorted list of floats in the range 0.0-1.0 which |
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represent the upper bound of each quantile |
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ramp -- an object which implements the CustomRamp interface |
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def GenQuantiles(self, list, percents, ramp, _range): |
_range -- a Range object |
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clazz = Classification() |
""" |
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quantiles = self.CalculateQuantiles(list, percents, _range) |
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numGroups = len(quantiles[1]) |
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if numGroups == 0: return clazz |
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ramp.SetNumGroups(numGroups) |
clazz = Classification() |
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quantiles = CalculateQuantiles(_list, percents, _range) |
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adjusted = True |
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if quantiles is not None: |
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numGroups = len(quantiles[3]) |
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if numGroups != 0: |
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adjusted = quantiles[0] |
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ramp.SetNumGroups(numGroups) |
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start, min, endMax, right = _range.GetRange() |
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oldp = 0 |
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i = 1 |
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end = "]" |
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left, min, max, right = _range.GetRange() |
for (q, p), prop in zip(quantiles[3], ramp): |
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if i == numGroups: |
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max = endMax |
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end = right |
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else: |
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max = _list[q] |
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start = "[" |
group = ClassGroupRange(Range((start, min, max, end)), |
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oldp = 0 |
None, prop) |
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for (q, p), prop in zip(quantiles[1], ramp): |
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max = list[q] |
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group = ClassGroupRange(Range(start + str(min) + ";" + |
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str(max) + "]"), |
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None, prop) |
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group.SetLabel("%s%% - %s%%" % (round(oldp*100, 2), |
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round(p*100, 2))) |
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oldp = p |
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start = "]" |
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min = max |
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clazz.AppendGroup(group) |
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return (quantiles[0], clazz) |
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def CalculateQuantiles(self, list, percents, _range): |
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"""Calculate quantiles for the given list of percents from the |
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sorted list of values that are in range. |
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percents is a sorted list of floats in the range 0.0-1.0 |
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This may not actually generate numGroups quantiles if |
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many of the values that fall on quantile borders are the same. |
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Returns a tuple of the form: (adjusted, [quantile_list]) |
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where adjusted is true if the the quantile percentages differ from |
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those supplied, and quantile_list is a list of tuples of the form: |
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(list_index, quantile_percentage) |
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""" |
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quantiles = [] |
group.SetLabel("%s%% - %s%%" % (round(oldp*100, 2), |
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round(p*100, 2))) |
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adjusted = False |
oldp = p |
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if len(percents) != 0: |
start = "]" |
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min = max |
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clazz.AppendGroup(group) |
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i += 1 |
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return (adjusted, clazz) |
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def GenQuantiles0(_list, percents, ramp, _range): |
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"""Same as GenQuantiles, but the first class won't be added to |
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the classification. |
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Returns a tuple (adjusted, Classification, upper_class0) where |
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upper_class0 is the highest value inside the first class. |
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_list -- a sort list of values |
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percents -- a sorted list of floats in the range 0.0-1.0 which |
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represent the upper bound of each quantile |
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ramp -- an object which implements the CustomRamp interface |
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_range -- a Range object |
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""" |
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clazz = Classification() |
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quantiles = CalculateQuantiles(_list, percents, _range) |
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adjusted = True |
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if quantiles is not None: |
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numGroups = len(quantiles[3]) - 1 |
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if numGroups > 0: |
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adjusted = quantiles[0] |
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ramp.SetNumGroups(numGroups) |
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start, min, endMax, right = _range.GetRange() |
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class0 = quantiles[3][0] |
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min = _list[class0[0]] |
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oldp = class0[1] |
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i = 1 |
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end = "]" |
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for (q, p), prop in zip(quantiles[3][1:], ramp): |
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if i == numGroups: |
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max = endMax |
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end = right |
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else: |
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max = _list[q] |
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group = ClassGroupRange(Range((start, min, max, end)), |
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None, prop) |
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group.SetLabel("%s%% - %s%%" % (round(oldp*100, 2), |
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round(p*100, 2))) |
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oldp = p |
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start = "]" |
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min = max |
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clazz.AppendGroup(group) |
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i += 1 |
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return (adjusted, clazz, _list[class0[0]]) |
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def CalculateQuantiles(_list, percents, _range): |
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"""Calculate quantiles for the given _list of percents from the |
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sorted list of values that are in range. |
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This may not actually generate len(percents) quantiles if |
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many of the values that fall on quantile borders are the same. |
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Returns a tuple of the form: |
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(adjusted, minIndex, maxIndex, [quantile_list]) |
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where adjusted is True if the the quantile percentages differ from |
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those supplied, minIndex is the index into _list where the |
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minimum value used is located, maxIndex is the index into _list |
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where the maximum value used is located, and quantile_list is a |
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list of tuples of the form: (list_index, quantile_percentage) |
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Returns None, if no quantiles could be generated based on the |
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given range or input list. |
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_list -- a sort list of values |
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percents -- a sorted list of floats in the range 0.0-1.0 which |
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represent the upper bound of each quantile |
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_range -- a Range object |
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""" |
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quantiles = [] |
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adjusted = False |
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if len(percents) != 0: |
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# |
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# find what part of the _list range covers |
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# |
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minIndex = -1 |
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maxIndex = -2 |
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for i in xrange(0, len(_list), 1): |
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if operator.contains(_range, _list[i]): |
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minIndex = i |
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break |
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for i in xrange(len(_list)-1, -1, -1): |
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if operator.contains(_range, _list[i]): |
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maxIndex = i |
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break |
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numValues = maxIndex - minIndex + 1 |
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if numValues > 0: |
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# |
# |
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# find what part of the list range covers |
# build a list of unique indices into list of where each |
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# quantile *should* be. set adjusted if the resulting |
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# indices are different |
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# |
# |
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minIndex = -1 |
quantiles = {} |
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maxIndex = -2 |
for p in percents: |
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for i in xrange(0, len(list), 1): |
index = min(minIndex + int(p*numValues)-1, maxIndex) |
| 292 |
if operator.contains(_range, list[i]): |
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minIndex = i |
adjusted = adjusted \ |
| 294 |
break |
or quantiles.has_key(index) \ |
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or ((index - minIndex + 1) / float(numValues)) != p |
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for i in xrange(len(list)-1, -1, -1): |
quantiles[index] = 0 |
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if operator.contains(_range, list[i]): |
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maxIndex = i |
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break; |
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numValues = maxIndex - minIndex + 1 |
quantiles = quantiles.keys() |
| 300 |
if minIndex <= maxIndex: |
quantiles.sort() |
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| 302 |
# |
# |
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# build a list of unique indices into list of where each |
# the current quantile index must be strictly greater than |
| 304 |
# quantile *should* be. set adjusted if the resulting |
# the lowerBound |
| 305 |
# indices are different |
# |
| 306 |
# |
lowerBound = minIndex - 1 |
|
quantiles = {} |
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for p in percents: |
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index = min(minIndex + int(p*numValues)-1, maxIndex) |
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adjusted = adjusted \ |
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or quantiles.has_key(index) \ |
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or ((index - minIndex + 1) / float(numValues)) != p |
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| 308 |
quantiles[index] = 0 |
for qindex in xrange(len(quantiles)): |
| 309 |
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if lowerBound >= maxIndex: |
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# discard higher quantiles |
| 311 |
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quantiles = quantiles[:qindex] |
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break |
| 313 |
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| 314 |
quantiles = quantiles.keys() |
# lowerBound + 1 is always a valid index |
|
quantiles.sort() |
|
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|
| 316 |
# |
# |
| 317 |
# the current quantile index must be strictly greater than |
# bump up the current quantile index to be a usable index |
| 318 |
# the lowerBound |
# if it currently falls below the lowerBound |
| 319 |
# |
# |
| 320 |
lowerBound = minIndex - 1 |
if quantiles[qindex] <= lowerBound: |
| 321 |
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quantiles[qindex] = lowerBound + 1 |
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for qindex in range(len(quantiles)): |
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if lowerBound >= maxIndex: |
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# discard higher quantiles |
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quantiles = quantiles[:qindex] |
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break |
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# lowerBound + 1 is always a valid index |
|
| 322 |
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| 323 |
# |
listIndex = quantiles[qindex] |
| 324 |
# bump up the current quantile index to be a usable index |
value = _list[listIndex] |
| 325 |
# if it currently falls below the lowerBound |
|
| 326 |
# |
# |
| 327 |
if quantiles[qindex] <= lowerBound: |
# look for similar values around the quantile index |
| 328 |
quantiles[qindex] = min(lowerBound + 1, maxIndex) |
# |
| 329 |
|
lindex = listIndex - 1 |
| 330 |
listIndex = quantiles[qindex] |
while lindex > lowerBound and value == _list[lindex]: |
| 331 |
value = list[quantiles[qindex]] |
lindex -= 1 |
| 332 |
|
lcount = (listIndex - 1) - lindex |
| 333 |
# |
|
| 334 |
# look for similar values around the quantile index |
rindex = listIndex + 1 |
| 335 |
# |
while rindex < maxIndex + 1 and value == _list[rindex]: |
| 336 |
lindex = listIndex - 1 |
rindex += 1 |
| 337 |
lcount = 0 |
rcount = (listIndex + 1) - rindex |
| 338 |
while lindex > lowerBound: |
|
| 339 |
if value != list[lindex]: break |
# |
| 340 |
lcount += 1 |
# adjust the current quantile index based on how many |
| 341 |
lindex -= 1 |
# numbers in the _list are the same as the current value |
| 342 |
|
# |
| 343 |
rindex = listIndex + 1 |
newIndex = listIndex |
| 344 |
rcount = 0 |
if lcount == rcount: |
| 345 |
while rindex < maxIndex + 1: |
if lcount != 0: |
| 346 |
if value != list[rindex]: break |
# |
| 347 |
rcount += 1 |
# there are an equal number of numbers to the left |
| 348 |
rindex += 1 |
# and right, try going to the left first unless |
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# |
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# adjust the current quantile index based on how many |
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# numbers in the list are the same as the current value |
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# |
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newIndex = listIndex |
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if lcount == rcount: |
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if lcount != 0: |
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# |
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# there are an equal number of numbers to the left |
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# and right, try going to the left first unless |
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# doing so creates an empty quantile. |
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# |
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if lindex != lowerBound: |
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newIndex = lindex |
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else: |
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newIndex = rindex - 1 |
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|
|
elif lcount < rcount: |
|
|
# there are fewer items to the left, so |
|
|
# try going to the left first unless |
|
| 349 |
# doing so creates an empty quantile. |
# doing so creates an empty quantile. |
| 350 |
|
# |
| 351 |
if lindex != lowerBound: |
if lindex != lowerBound: |
| 352 |
newIndex = lindex |
newIndex = lindex |
| 353 |
else: |
else: |
| 354 |
newIndex = rindex - 1 |
newIndex = rindex - 1 |
| 355 |
|
|
| 356 |
elif rcount < lcount: |
elif lcount < rcount: |
| 357 |
# there are fewer items to the right, so go to the right |
# there are fewer items to the left, so |
| 358 |
|
# try going to the left first unless |
| 359 |
|
# doing so creates an empty quantile. |
| 360 |
|
if lindex != lowerBound: |
| 361 |
|
newIndex = lindex |
| 362 |
|
else: |
| 363 |
newIndex = rindex - 1 |
newIndex = rindex - 1 |
| 364 |
|
|
| 365 |
quantiles[qindex] = newIndex |
elif rcount < lcount: |
| 366 |
lowerBound = quantiles[qindex] |
# there are fewer items to the right, so go to the right |
| 367 |
|
newIndex = rindex - 1 |
| 368 |
# |
|
| 369 |
# since quantiles is only set if the code is at least a little |
adjusted = adjusted or newIndex != listIndex |
| 370 |
# successful, an empty list will be generated in the case that |
|
| 371 |
# we fail to get to the real body of the algorithm |
quantiles[qindex] = newIndex |
| 372 |
# |
lowerBound = quantiles[qindex] |
| 373 |
return (adjusted, |
|
| 374 |
[(q, (q - minIndex+1) / float(numValues)) for q in quantiles]) |
if len(quantiles) == 0: |
| 375 |
|
return None |
| 376 |
|
else: |
| 377 |
|
return (adjusted, minIndex, maxIndex, |
| 378 |
|
[(q, (q - minIndex+1) / float(numValues)) \ |
| 379 |
|
for q in quantiles]) |
| 380 |
|
|
| 381 |
CLR = 0 |
CLR = 0 |
| 382 |
STEP = 1 |
STEP = 1 |
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