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Merge pull request astropy#937 from taldcroft/table/stack
Stack tables horizontally (by columns) or vertically (by rows, i.e. append)
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| """ | ||
| High-level table operations: | ||
| - join() | ||
| - hstack() | ||
| - vstack() | ||
| """ | ||
| # Licensed under a 3-clause BSD style license - see LICENSE.rst | ||
|
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| from copy import deepcopy | ||
| import warnings | ||
| import collections | ||
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| from ..utils import OrderedDict, metadata | ||
| from . import np_utils | ||
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| __all__ = ['join', 'hstack', 'vstack'] | ||
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| def _merge_col_meta(out, tables, col_name_map, idx_left=0, idx_right=1): | ||
| """ | ||
| Merge column meta data for the ``out`` table. | ||
| This merges column meta, which includes attributes units, format, | ||
| and description, as well as the actual `meta` atttribute. It is | ||
| assumed that the ``out`` table was created by merging ``tables``. | ||
| The ``col_name_map`` provides the mapping from col name in ``out`` | ||
| back to the original name (which may be different). | ||
| """ | ||
| # Set column meta | ||
| attrs = ('units', 'format', 'description') | ||
| for out_col in out.columns.values(): | ||
| for idx_table, table in enumerate(tables): | ||
| left_col = out_col | ||
| right_name = col_name_map[out_col.name][idx_table] | ||
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| if right_name: | ||
| right_col = table[right_name] | ||
| out_col.meta = metadata.merge(left_col.meta, right_col.meta) | ||
| for attr in attrs: | ||
| left_attr = getattr(left_col, attr) | ||
| right_attr = getattr(right_col, attr) | ||
| merge_attr = left_attr or right_attr | ||
| setattr(out_col, attr, merge_attr) | ||
| if left_attr and right_attr and left_attr != right_attr: | ||
| warnings.warn('In merged column {0!r} the {1!r} attribute does not match ' | ||
| '({2} != {3}). Using {2} for merged output' | ||
| .format(out_col.name, attr, left_attr, right_attr), | ||
| metadata.MergeConflictWarning) | ||
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| def _merge_table_meta(out, tables): | ||
| out_meta = deepcopy(tables[0].meta) | ||
| for table in tables[1:]: | ||
| out_meta = metadata.merge(out_meta, table.meta) | ||
| out.meta.update(out_meta) | ||
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| def _get_list_of_tables(tables): | ||
| """ | ||
| Check that tables is a Table or sequence of Tables. Returns the | ||
| corresponding list of Tables. | ||
| """ | ||
| from .table import Table | ||
| err = '`tables` arg must be a Table or sequence of Tables' | ||
| if isinstance(tables, Table): | ||
| tables = [tables] | ||
| elif isinstance(tables, collections.Sequence): | ||
| if any(not isinstance(x, Table) for x in tables): | ||
| raise TypeError(err) | ||
| else: | ||
| raise TypeError(err) | ||
|
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| return list(tables) | ||
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| def join(left, right, keys=None, join_type='inner', | ||
| uniq_col_name='{col_name}_{table_name}', | ||
| table_names=['1', '2']): | ||
| """ | ||
| Perform a join of the left table with the right table on specified keys. | ||
| Parameters | ||
| ---------- | ||
| left : Table object or a value that will initialize a Table object | ||
| Left side table in the join | ||
| right : Table object or a value that will initialize a Table object | ||
| Right side table in the join | ||
| keys : str or list of str | ||
| Column(s) used to match rows of left and right tables. Default | ||
| is to use all columns which are common to both tables. | ||
| join_type : str | ||
| Join type ('inner' | 'outer' | 'left' | 'right'), default is 'inner' | ||
| uniq_col_name : str or None | ||
| String generate a unique output column name in case of a conflict. | ||
| The default is '{col_name}_{table_name}'. | ||
| table_names : list of str or None | ||
| Two-element list of table names used when generating unique output | ||
| column names. The default is ['1', '2']. | ||
| """ | ||
| from .table import Table | ||
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| # Try converting inputs to Table as needed | ||
| if not isinstance(left, Table): | ||
| left = Table(left) | ||
| if not isinstance(right, Table): | ||
| right = Table(right) | ||
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| col_name_map = OrderedDict() | ||
| out_data = np_utils.join(left._data, right._data, keys, join_type, | ||
| uniq_col_name, table_names, col_name_map) | ||
| # Create the output (Table or subclass of Table) | ||
| out = Table(out_data) | ||
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| # Merge the column and table meta data. Table subclasses might override | ||
| # these methods for custom merge behavior. | ||
| _merge_col_meta(out, [left, right], col_name_map) | ||
| _merge_table_meta(out, [left, right]) | ||
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| return out | ||
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| def vstack(tables, join_type='outer'): | ||
| """ | ||
| Stack tables vertically (along rows) | ||
| A ``join_type`` of 'exact' means that the tables must all | ||
| have exactly the same column names (though the order can vary). If | ||
| ``join_type`` is 'inner' then the intersection of common columns will | ||
| be output. A value of 'outer' (default) means the output will have the union of | ||
| all columns, with table values being masked where no common values are | ||
| available. | ||
| Parameters | ||
| ---------- | ||
| tables : Table or list of Table objects | ||
| Table(s) to stack along rows (vertically) with the current table | ||
| join_type : str | ||
| Join type ('inner' | 'exact' | 'outer'), default is 'exact' | ||
| Examples | ||
| -------- | ||
| To stack two tables along rows do:: | ||
| >>> from astropy.table import vstack, Table | ||
| >>> t1 = Table({'a': [1, 2], 'b': [3, 4]}, names=('a', 'b')) | ||
| >>> t2 = Table({'a': [5, 6], 'b': [7, 8]}, names=('a', 'b')) | ||
| >>> print t1 | ||
| a b | ||
| --- --- | ||
| 1 3 | ||
| 2 4 | ||
| >>> print t2 | ||
| a b | ||
| --- --- | ||
| 5 7 | ||
| 6 8 | ||
| >>> print vstack([t1, t2]) | ||
| a b | ||
| --- --- | ||
| 1 3 | ||
| 2 4 | ||
| 5 7 | ||
| 6 8 | ||
| """ | ||
| from .table import Table | ||
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| tables = _get_list_of_tables(tables) # validates input | ||
| arrays = [table._data for table in tables] | ||
| col_name_map = OrderedDict() | ||
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| out_data = np_utils.vstack(arrays, join_type, col_name_map) | ||
| out = Table(out_data) | ||
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| # Merge column and table metadata | ||
| _merge_col_meta(out, tables, col_name_map) | ||
| _merge_table_meta(out, tables) | ||
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| return out | ||
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| def hstack(tables, join_type='outer', | ||
| uniq_col_name='{col_name}_{table_name}', table_names=None): | ||
| """ | ||
| Stack tables along columns (horizontally) | ||
| A ``join_type`` of 'exact' means that the tables must all | ||
| have exactly the same number of row. If ``join_type`` is 'inner' then | ||
| the intersection of rows will be output. A value of 'outer' (default) means | ||
| the output will have the union of all rows, with table values being | ||
| masked where no common values are available. | ||
| Parameters | ||
| ---------- | ||
| tables : List of Table objects | ||
| Tables to stack along columns (horizontally) with the current table | ||
| join_type : str | ||
| Join type ('inner' | 'exact' | 'outer'), default is 'outer' | ||
| uniq_col_name : str or None | ||
| String generate a unique output column name in case of a conflict. | ||
| The default is '{col_name}_{table_name}'. | ||
| table_names : list of str or None | ||
| Two-element list of table names used when generating unique output | ||
| column names. The default is ['1', '2', ..]. | ||
| col_name_map : empty dict or None | ||
| If passed as a dict then it will be updated in-place with the | ||
| mapping of output to input column names. | ||
| Examples | ||
| -------- | ||
| To stack two tables horizontally (along columns) do:: | ||
| >>> from astropy.table import Table, hstack | ||
| >>> t1 = Table({'a': [1, 2], 'b': [3, 4]}, names=('a', 'b')) | ||
| >>> t2 = Table({'c': [5, 6], 'd': [7, 8]}, names=('c', 'd')) | ||
| >>> print t1 | ||
| a b | ||
| --- --- | ||
| 1 3 | ||
| 2 4 | ||
| >>> print t2 | ||
| c d | ||
| --- --- | ||
| 5 7 | ||
| 6 8 | ||
| >>> print hstack([t1, t2]) | ||
| a b c d | ||
| --- --- --- --- | ||
| 1 3 5 7 | ||
| 2 4 6 8 | ||
| """ | ||
| from .table import Table | ||
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| tables = _get_list_of_tables(tables) # validates input | ||
| arrays = [table._data for table in tables] | ||
| col_name_map = OrderedDict() | ||
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| out_data = np_utils.hstack(arrays, join_type, uniq_col_name, table_names, | ||
| col_name_map) | ||
| out = Table(out_data) | ||
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| _merge_col_meta(out, tables, col_name_map) | ||
| _merge_table_meta(out, tables) | ||
|
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| return out |
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