|
1 | 1 | """ common utilities """
|
2 | 2 |
|
| 3 | +import itertools |
| 4 | +from warnings import catch_warnings |
| 5 | +import numpy as np |
| 6 | + |
| 7 | +from pandas.compat import lrange |
| 8 | +from pandas.types.common import is_scalar |
| 9 | +from pandas import Series, DataFrame, Panel, date_range, UInt64Index |
| 10 | +from pandas.util import testing as tm |
| 11 | +from pandas.formats.printing import pprint_thing |
| 12 | + |
| 13 | +_verbose = False |
| 14 | + |
3 | 15 |
|
4 | 16 | def _mklbl(prefix, n):
|
5 | 17 | return ["%s%s" % (prefix, i) for i in range(n)]
|
| 18 | + |
| 19 | + |
| 20 | +def _axify(obj, key, axis): |
| 21 | + # create a tuple accessor |
| 22 | + axes = [slice(None)] * obj.ndim |
| 23 | + axes[axis] = key |
| 24 | + return tuple(axes) |
| 25 | + |
| 26 | + |
| 27 | +class Base(object): |
| 28 | + """ indexing comprehensive base class """ |
| 29 | + |
| 30 | + _objs = set(['series', 'frame', 'panel']) |
| 31 | + _typs = set(['ints', 'uints', 'labels', 'mixed', |
| 32 | + 'ts', 'floats', 'empty', 'ts_rev']) |
| 33 | + |
| 34 | + def setUp(self): |
| 35 | + |
| 36 | + self.series_ints = Series(np.random.rand(4), index=lrange(0, 8, 2)) |
| 37 | + self.frame_ints = DataFrame(np.random.randn(4, 4), |
| 38 | + index=lrange(0, 8, 2), |
| 39 | + columns=lrange(0, 12, 3)) |
| 40 | + self.panel_ints = Panel(np.random.rand(4, 4, 4), |
| 41 | + items=lrange(0, 8, 2), |
| 42 | + major_axis=lrange(0, 12, 3), |
| 43 | + minor_axis=lrange(0, 16, 4)) |
| 44 | + |
| 45 | + self.series_uints = Series(np.random.rand(4), |
| 46 | + index=UInt64Index(lrange(0, 8, 2))) |
| 47 | + self.frame_uints = DataFrame(np.random.randn(4, 4), |
| 48 | + index=UInt64Index(lrange(0, 8, 2)), |
| 49 | + columns=UInt64Index(lrange(0, 12, 3))) |
| 50 | + self.panel_uints = Panel(np.random.rand(4, 4, 4), |
| 51 | + items=UInt64Index(lrange(0, 8, 2)), |
| 52 | + major_axis=UInt64Index(lrange(0, 12, 3)), |
| 53 | + minor_axis=UInt64Index(lrange(0, 16, 4))) |
| 54 | + |
| 55 | + self.series_labels = Series(np.random.randn(4), index=list('abcd')) |
| 56 | + self.frame_labels = DataFrame(np.random.randn(4, 4), |
| 57 | + index=list('abcd'), columns=list('ABCD')) |
| 58 | + self.panel_labels = Panel(np.random.randn(4, 4, 4), |
| 59 | + items=list('abcd'), |
| 60 | + major_axis=list('ABCD'), |
| 61 | + minor_axis=list('ZYXW')) |
| 62 | + |
| 63 | + self.series_mixed = Series(np.random.randn(4), index=[2, 4, 'null', 8]) |
| 64 | + self.frame_mixed = DataFrame(np.random.randn(4, 4), |
| 65 | + index=[2, 4, 'null', 8]) |
| 66 | + self.panel_mixed = Panel(np.random.randn(4, 4, 4), |
| 67 | + items=[2, 4, 'null', 8]) |
| 68 | + |
| 69 | + self.series_ts = Series(np.random.randn(4), |
| 70 | + index=date_range('20130101', periods=4)) |
| 71 | + self.frame_ts = DataFrame(np.random.randn(4, 4), |
| 72 | + index=date_range('20130101', periods=4)) |
| 73 | + self.panel_ts = Panel(np.random.randn(4, 4, 4), |
| 74 | + items=date_range('20130101', periods=4)) |
| 75 | + |
| 76 | + dates_rev = (date_range('20130101', periods=4) |
| 77 | + .sort_values(ascending=False)) |
| 78 | + self.series_ts_rev = Series(np.random.randn(4), |
| 79 | + index=dates_rev) |
| 80 | + self.frame_ts_rev = DataFrame(np.random.randn(4, 4), |
| 81 | + index=dates_rev) |
| 82 | + self.panel_ts_rev = Panel(np.random.randn(4, 4, 4), |
| 83 | + items=dates_rev) |
| 84 | + |
| 85 | + self.frame_empty = DataFrame({}) |
| 86 | + self.series_empty = Series({}) |
| 87 | + self.panel_empty = Panel({}) |
| 88 | + |
| 89 | + # form agglomerates |
| 90 | + for o in self._objs: |
| 91 | + |
| 92 | + d = dict() |
| 93 | + for t in self._typs: |
| 94 | + d[t] = getattr(self, '%s_%s' % (o, t), None) |
| 95 | + |
| 96 | + setattr(self, o, d) |
| 97 | + |
| 98 | + def generate_indices(self, f, values=False): |
| 99 | + """ generate the indicies |
| 100 | + if values is True , use the axis values |
| 101 | + is False, use the range |
| 102 | + """ |
| 103 | + |
| 104 | + axes = f.axes |
| 105 | + if values: |
| 106 | + axes = [lrange(len(a)) for a in axes] |
| 107 | + |
| 108 | + return itertools.product(*axes) |
| 109 | + |
| 110 | + def get_result(self, obj, method, key, axis): |
| 111 | + """ return the result for this obj with this key and this axis """ |
| 112 | + |
| 113 | + if isinstance(key, dict): |
| 114 | + key = key[axis] |
| 115 | + |
| 116 | + # use an artifical conversion to map the key as integers to the labels |
| 117 | + # so ix can work for comparisions |
| 118 | + if method == 'indexer': |
| 119 | + method = 'ix' |
| 120 | + key = obj._get_axis(axis)[key] |
| 121 | + |
| 122 | + # in case we actually want 0 index slicing |
| 123 | + try: |
| 124 | + with catch_warnings(record=True): |
| 125 | + xp = getattr(obj, method).__getitem__(_axify(obj, key, axis)) |
| 126 | + except: |
| 127 | + xp = getattr(obj, method).__getitem__(key) |
| 128 | + |
| 129 | + return xp |
| 130 | + |
| 131 | + def get_value(self, f, i, values=False): |
| 132 | + """ return the value for the location i """ |
| 133 | + |
| 134 | + # check agains values |
| 135 | + if values: |
| 136 | + return f.values[i] |
| 137 | + |
| 138 | + # this is equiv of f[col][row]..... |
| 139 | + # v = f |
| 140 | + # for a in reversed(i): |
| 141 | + # v = v.__getitem__(a) |
| 142 | + # return v |
| 143 | + with catch_warnings(record=True): |
| 144 | + return f.ix[i] |
| 145 | + |
| 146 | + def check_values(self, f, func, values=False): |
| 147 | + |
| 148 | + if f is None: |
| 149 | + return |
| 150 | + axes = f.axes |
| 151 | + indicies = itertools.product(*axes) |
| 152 | + |
| 153 | + for i in indicies: |
| 154 | + result = getattr(f, func)[i] |
| 155 | + |
| 156 | + # check agains values |
| 157 | + if values: |
| 158 | + expected = f.values[i] |
| 159 | + else: |
| 160 | + expected = f |
| 161 | + for a in reversed(i): |
| 162 | + expected = expected.__getitem__(a) |
| 163 | + |
| 164 | + tm.assert_almost_equal(result, expected) |
| 165 | + |
| 166 | + def check_result(self, name, method1, key1, method2, key2, typs=None, |
| 167 | + objs=None, axes=None, fails=None): |
| 168 | + def _eq(t, o, a, obj, k1, k2): |
| 169 | + """ compare equal for these 2 keys """ |
| 170 | + |
| 171 | + if a is not None and a > obj.ndim - 1: |
| 172 | + return |
| 173 | + |
| 174 | + def _print(result, error=None): |
| 175 | + if error is not None: |
| 176 | + error = str(error) |
| 177 | + v = ("%-16.16s [%-16.16s]: [typ->%-8.8s,obj->%-8.8s," |
| 178 | + "key1->(%-4.4s),key2->(%-4.4s),axis->%s] %s" % |
| 179 | + (name, result, t, o, method1, method2, a, error or '')) |
| 180 | + if _verbose: |
| 181 | + pprint_thing(v) |
| 182 | + |
| 183 | + try: |
| 184 | + rs = getattr(obj, method1).__getitem__(_axify(obj, k1, a)) |
| 185 | + |
| 186 | + try: |
| 187 | + xp = self.get_result(obj, method2, k2, a) |
| 188 | + except: |
| 189 | + result = 'no comp' |
| 190 | + _print(result) |
| 191 | + return |
| 192 | + |
| 193 | + detail = None |
| 194 | + |
| 195 | + try: |
| 196 | + if is_scalar(rs) and is_scalar(xp): |
| 197 | + self.assertEqual(rs, xp) |
| 198 | + elif xp.ndim == 1: |
| 199 | + tm.assert_series_equal(rs, xp) |
| 200 | + elif xp.ndim == 2: |
| 201 | + tm.assert_frame_equal(rs, xp) |
| 202 | + elif xp.ndim == 3: |
| 203 | + tm.assert_panel_equal(rs, xp) |
| 204 | + result = 'ok' |
| 205 | + except AssertionError as e: |
| 206 | + detail = str(e) |
| 207 | + result = 'fail' |
| 208 | + |
| 209 | + # reverse the checks |
| 210 | + if fails is True: |
| 211 | + if result == 'fail': |
| 212 | + result = 'ok (fail)' |
| 213 | + |
| 214 | + _print(result) |
| 215 | + if not result.startswith('ok'): |
| 216 | + raise AssertionError(detail) |
| 217 | + |
| 218 | + except AssertionError: |
| 219 | + raise |
| 220 | + except Exception as detail: |
| 221 | + |
| 222 | + # if we are in fails, the ok, otherwise raise it |
| 223 | + if fails is not None: |
| 224 | + if isinstance(detail, fails): |
| 225 | + result = 'ok (%s)' % type(detail).__name__ |
| 226 | + _print(result) |
| 227 | + return |
| 228 | + |
| 229 | + result = type(detail).__name__ |
| 230 | + raise AssertionError(_print(result, error=detail)) |
| 231 | + |
| 232 | + if typs is None: |
| 233 | + typs = self._typs |
| 234 | + |
| 235 | + if objs is None: |
| 236 | + objs = self._objs |
| 237 | + |
| 238 | + if axes is not None: |
| 239 | + if not isinstance(axes, (tuple, list)): |
| 240 | + axes = [axes] |
| 241 | + else: |
| 242 | + axes = list(axes) |
| 243 | + else: |
| 244 | + axes = [0, 1, 2] |
| 245 | + |
| 246 | + # check |
| 247 | + for o in objs: |
| 248 | + if o not in self._objs: |
| 249 | + continue |
| 250 | + |
| 251 | + d = getattr(self, o) |
| 252 | + for a in axes: |
| 253 | + for t in typs: |
| 254 | + if t not in self._typs: |
| 255 | + continue |
| 256 | + |
| 257 | + obj = d[t] |
| 258 | + if obj is not None: |
| 259 | + obj = obj.copy() |
| 260 | + |
| 261 | + k2 = key2 |
| 262 | + _eq(t, o, a, obj, key1, k2) |
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