| |
|
|
| """ |
| Helper functions for table development, mostly creating useful |
| tables for testing. |
| """ |
|
|
|
|
| from itertools import cycle |
| import string |
| import numpy as np |
|
|
| from .table import Table, Column |
| from astropy.utils.data_info import ParentDtypeInfo |
|
|
|
|
| class TimingTables: |
| """ |
| Object which contains two tables and various other attributes that |
| are useful for timing and other API tests. |
| """ |
|
|
| def __init__(self, size=1000, masked=False): |
| self.masked = masked |
|
|
| |
| self.table = Table(masked=self.masked) |
|
|
| |
| np.random.seed(12345) |
| self.table['i'] = np.arange(size) |
| self.table['a'] = np.random.random(size) |
| self.table['b'] = np.random.random(size) > 0.5 |
| self.table['c'] = np.random.random((size, 10)) |
| self.table['d'] = np.random.choice(np.array(list(string.ascii_letters)), size) |
|
|
| self.extra_row = {'a': 1.2, 'b': True, 'c': np.repeat(1, 10), 'd': 'Z'} |
| self.extra_column = np.random.randint(0, 100, size) |
| self.row_indices = np.where(self.table['a'] > 0.9)[0] |
| self.table_grouped = self.table.group_by('d') |
|
|
| |
| self.other_table = Table(masked=self.masked) |
| self.other_table['i'] = np.arange(1, size, 3) |
| self.other_table['f'] = np.random.random() |
| self.other_table.sort('f') |
|
|
| |
| self.other_table_2 = Table(masked=self.masked) |
| self.other_table_2['g'] = np.random.random(size) |
| self.other_table_2['h'] = np.random.random((size, 10)) |
|
|
| self.bool_mask = self.table['a'] > 0.6 |
|
|
|
|
| def simple_table(size=3, cols=None, kinds='ifS', masked=False): |
| """ |
| Return a simple table for testing. |
| |
| Example |
| -------- |
| :: |
| |
| >>> from astropy.table.table_helpers import simple_table |
| >>> print(simple_table(3, 6, masked=True, kinds='ifOS')) |
| a b c d e f |
| --- --- -------- --- --- --- |
| -- 1.0 {'c': 2} -- 5 5.0 |
| 2 2.0 -- e 6 -- |
| 3 -- {'e': 4} f -- 7.0 |
| |
| Parameters |
| ---------- |
| size : int |
| Number of table rows |
| cols : int, optional |
| Number of table columns. Defaults to number of kinds. |
| kinds : str |
| String consisting of the column dtype.kinds. This string |
| will be cycled through to generate the column dtype. |
| The allowed values are 'i', 'f', 'S', 'O'. |
| |
| Returns |
| ------- |
| out : `Table` |
| New table with appropriate characteristics |
| """ |
| if cols is None: |
| cols = len(kinds) |
| if cols > 26: |
| raise ValueError("Max 26 columns in SimpleTable") |
|
|
| columns = [] |
| names = [chr(ord('a') + ii) for ii in range(cols)] |
| letters = np.array([c for c in string.ascii_letters]) |
| for jj, kind in zip(range(cols), cycle(kinds)): |
| if kind == 'i': |
| data = np.arange(1, size + 1, dtype=np.int64) + jj |
| elif kind == 'f': |
| data = np.arange(size, dtype=np.float64) + jj |
| elif kind == 'S': |
| indices = (np.arange(size) + jj) % len(letters) |
| data = letters[indices] |
| elif kind == 'O': |
| indices = (np.arange(size) + jj) % len(letters) |
| vals = letters[indices] |
| data = [{val: index} for val, index in zip(vals, indices)] |
| else: |
| raise ValueError('Unknown data kind') |
| columns.append(Column(data)) |
|
|
| table = Table(columns, names=names, masked=masked) |
| if masked: |
| for ii, col in enumerate(table.columns.values()): |
| mask = np.array((np.arange(size) + ii) % 3, dtype=bool) |
| col.mask = ~mask |
|
|
| return table |
|
|
|
|
| def complex_table(): |
| """ |
| Return a masked table from the io.votable test set that has a wide variety |
| of stressing types. |
| """ |
| from astropy.utils.data import get_pkg_data_filename |
| from astropy.io.votable.table import parse |
| import warnings |
|
|
| with warnings.catch_warnings(): |
| warnings.simplefilter("ignore") |
| votable = parse(get_pkg_data_filename('../io/votable/tests/data/regression.xml'), |
| pedantic=False) |
| first_table = votable.get_first_table() |
| table = first_table.to_table() |
|
|
| return table |
|
|
|
|
| class ArrayWrapper: |
| """ |
| Minimal mixin using a simple wrapper around a numpy array |
| """ |
| info = ParentDtypeInfo() |
|
|
| def __init__(self, data): |
| self.data = np.array(data) |
| if 'info' in getattr(data, '__dict__', ()): |
| self.info = data.info |
|
|
| def __getitem__(self, item): |
| if isinstance(item, (int, np.integer)): |
| out = self.data[item] |
| else: |
| out = self.__class__(self.data[item]) |
| if 'info' in self.__dict__: |
| out.info = self.info |
| return out |
|
|
| def __setitem__(self, item, value): |
| self.data[item] = value |
|
|
| def __len__(self): |
| return len(self.data) |
|
|
| def __eq__(self, other): |
| """Minimal equality testing, mostly for mixin unit tests""" |
| if isinstance(other, ArrayWrapper): |
| return self.data == other.data |
| else: |
| return self.data == other |
|
|
| @property |
| def dtype(self): |
| return self.data.dtype |
|
|
| @property |
| def shape(self): |
| return self.data.shape |
|
|
| def __repr__(self): |
| return ("<{0} name='{1}' data={2}>" |
| .format(self.__class__.__name__, self.info.name, self.data)) |
|
|