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| 1 | +# -*- coding: utf-8 OA-*-za |
| 2 | +""" |
| 3 | +catch all for categorical functions |
| 4 | +""" |
| 5 | +from __future__ import (absolute_import, division, print_function, |
| 6 | + unicode_literals) |
| 7 | + |
| 8 | +import six |
| 9 | + |
| 10 | +import numpy as np |
| 11 | + |
| 12 | +import matplotlib.units as units |
| 13 | +import matplotlib.ticker as ticker |
| 14 | + |
| 15 | + |
| 16 | +# pure hack for numpy 1.6 support |
| 17 | +from distutils.version import LooseVersion |
| 18 | + |
| 19 | +NP_NEW = (LooseVersion(np.version.version) >= LooseVersion('1.7')) |
| 20 | + |
| 21 | + |
| 22 | +def to_array(data, maxlen=100): |
| 23 | + if NP_NEW: |
| 24 | + return np.array(data, dtype=np.unicode) |
| 25 | + try: |
| 26 | + vals = np.array(data, dtype=('|S', maxlen)) |
| 27 | + except UnicodeEncodeError: |
| 28 | + # pure hack |
| 29 | + vals = np.array([convert_to_string(d) for d in data]) |
| 30 | + return vals |
| 31 | + |
| 32 | + |
| 33 | +class StrCategoryConverter(units.ConversionInterface): |
| 34 | + @staticmethod |
| 35 | + def convert(value, unit, axis): |
| 36 | + """Uses axis.unit_data map to encode |
| 37 | + data as floats |
| 38 | + """ |
| 39 | + vmap = dict(axis.unit_data) |
| 40 | + |
| 41 | + if isinstance(value, six.string_types): |
| 42 | + return vmap[value] |
| 43 | + |
| 44 | + vals = to_array(value) |
| 45 | + for lab, loc in axis.unit_data: |
| 46 | + vals[vals == lab] = loc |
| 47 | + |
| 48 | + return vals.astype('float') |
| 49 | + |
| 50 | + @staticmethod |
| 51 | + def axisinfo(unit, axis): |
| 52 | + seq, locs = zip(*axis.unit_data) |
| 53 | + majloc = StrCategoryLocator(locs) |
| 54 | + majfmt = StrCategoryFormatter(seq) |
| 55 | + return units.AxisInfo(majloc=majloc, majfmt=majfmt) |
| 56 | + |
| 57 | + @staticmethod |
| 58 | + def default_units(data, axis): |
| 59 | + # the conversion call stack is: |
| 60 | + # default_units->axis_info->convert |
| 61 | + axis.unit_data = map_categories(data, axis.unit_data) |
| 62 | + return None |
| 63 | + |
| 64 | + |
| 65 | +class StrCategoryLocator(ticker.FixedLocator): |
| 66 | + def __init__(self, locs): |
|
F438
67 | + super(StrCategoryLocator, self).__init__(locs, None) |
| 68 | + |
| 69 | + |
| 70 | +class StrCategoryFormatter(ticker.FixedFormatter): |
| 71 | + def __init__(self, seq): |
| 72 | + super(StrCategoryFormatter, self).__init__(seq) |
| 73 | + |
| 74 | + |
| 75 | +def convert_to_string(value): |
| 76 | + """Helper function for numpy 1.6, can be replaced with |
| 77 | + np.array(...,dtype=unicode) for all later versions of numpy""" |
| 78 | + |
| 79 | + if isinstance(value, six.string_types): |
| 80 | + return value |
| 81 | + if np.isfinite(value): |
| 82 | + value = np.asarray(value, dtype=str)[np.newaxis][0] |
| 83 | + elif np.isnan(value): |
| 84 | + value = 'nan' |
| 85 | + elif np.isposinf(value): |
| 86 | + value = 'inf' |
| 87 | + elif np.isneginf(value): |
| 88 | + value = '-inf' |
| 89 | + else: |
| 90 | + raise ValueError("Unconvertable {}".format(value)) |
| 91 | + return value |
| 92 | + |
| 93 | + |
| 94 | +def map_categories(data, old_map=None): |
| 95 | + """Create mapping between unique categorical |
| 96 | + values and numerical identifier. |
| 97 | +
|
| 98 | + Paramters |
| 99 | + --------- |
| 100 | + data: iterable |
| 101 | + sequence of values |
| 102 | + old_map: list of tuple, optional |
| 103 | + if not `None`, than old_mapping will be updated with new values and |
| 104 | + previous mappings will remain unchanged) |
| 105 | + sort: bool, optional |
| 106 | + sort keys by ASCII value |
| 107 | +
|
| 108 | + Returns |
| 109 | + ------- |
| 110 | + list of tuple |
| 111 | + [(label, ticklocation),...] |
| 112 | +
|
| 113 | + """ |
| 114 | + |
| 115 | + # code typical missing data in the negative range because |
| 116 | + # everything else will always have positive encoding |
| 117 | + # question able if it even makes sense |
| 118 | + spdict = {'nan': -1.0, 'inf': -2.0, '-inf': -3.0} |
| 119 | + |
| 120 | + if isinstance(data, six.string_types): |
| 121 | + data = [data] |
| 122 | + |
| 123 | + # will update this post cbook/dict support |
| 124 | + strdata = to_array(data) |
| 125 | + uniq = np.unique(strdata) |
| 126 | + |
| 127 | + if old_map: |
| 128 | + olabs, okeys = zip(*old_map) |
| 129 | + svalue = max(okeys) + 1 |
| 130 | + else: |
| 131 | + old_map, olabs, okeys = [], [], [] |
| 132 | + svalue = 0 |
| 133 | + |
| 134 | + category_map = old_map[:] |
| 135 | + |
| 136 | + new_labs = [u for u in uniq if u not in olabs] |
| 137 | + missing = [nl for nl in new_labs if nl in spdict.keys()] |
| 138 | + |
| 139 | + category_map.extend([(m, spdict[m]) for m in missing]) |
| 140 | + |
| 141 | + new_labs = [nl for nl in new_labs if nl not in missing] |
| 142 | + |
| 143 | + new_locs = np.arange(svalue, svalue + len(new_labs), dtype='float') |
| 144 | + category_map.extend(list(zip(new_labs, new_locs))) |
| 145 | + return category_map |
| 146 | + |
| 147 | + |
| 148 | +# Connects the convertor to matplotlib |
| 149 | +units.registry[str] = StrCategoryConverter() |
| 150 | +units.registry[bytes] = StrCategoryConverter() |
| 151 | +units.registry[six.text_type] = StrCategoryConverter() |
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