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[WIP] Categorical Color Mapping #6934

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[WIP] Categorical Color Mapping #6934

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a16e025
support for py.test, updating axis ticks, and unitData as class
story645 Aug 3, 2016
1075157
add pytest to travis, appveyor, and tox and py3.5 to tox
story645 Aug 3, 2016
c6eec14
refactored set_seq and set_locs into 1
story645 Aug 3, 2016
624991c
CategoryNorm
story645 Aug 17, 2016
9707a0f
Categorical mapping via units on norm
story645 Aug 17, 2016
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refactored set_seq and set_locs into 1
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@story645
story645 committed Aug 17, 2016
commit c6eec14320db7f8b8170a68d515a2e7596caaf97
34 changes: 13 additions & 21 deletions lib/matplotlib/category.py
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Original file line number Diff line number Diff line change
Expand Up @@ -101,8 +101,6 @@ def convert_to_string(value):
class UnitData(object):
# debatable makes sense to special code missing values
spdict = {'nan': -1.0, 'inf': -2.0, '-inf': -3.0}
# used to set out of bounds
LOWER_BOUND = -4

def __init__(self, data):
"""Create mapping between unique categorical values
Expand All @@ -113,32 +111,26 @@ def __init__(self, data):
sequence of values
"""
self.seq, self.locs = [], []
self._set_seq(data)
self._set_locs(0)
self._set_seq_locs(data, 0)

def update(self, new_data):
self._set_seq(new_data)
value = max(self.locs)
self._set_locs(value + 1)
# so as not to conflict with spdict
value = max(max(self.locs) + 1, 0)
self._set_seq_locs(new_data, value)

def _set_seq(self, data):
#magic to make it work under np1.6
def _set_seq_locs(self, data, value):
# magic to make it work under np1.6
strdata = to_array(data)
# np.unique makes dateframes work
for d in np.unique(strdata):
if d not in self.seq:
self.seq.append(convert_to_string(d))
self.locs.append(UnitData.LOWER_BOUND)

def _set_locs(self, value):
for i, s in enumerate(self.seq):
if s in UnitData.spdict.keys():
self.locs[i] = UnitData.spdict[s]
elif self.locs[i] == UnitData.LOWER_BOUND:
self.locs[i] = value
new_s = [d for d in np.unique(strdata) if d not in self.seq]
for ns in new_s:
self.seq.append(convert_to_string(ns))
if ns in UnitData.spdict.keys():
self.locs.append(UnitData.spdict[ns])
else:
self.locs.append(value)
value += 1


# Connects the convertor to matplotlib
units.registry[str] = StrCategoryConverter()
units.registry[bytes] = StrCategoryConverter()
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