ENH: beef up Float64HashTable, add algorithms.py to start collecting central algos, close #502 at some point

Author: wesm

pandas/core/algorithms.py

@@ -0,0 +1,80 @@
+"""
+Generic data algorithms
+"""
+
+import numpy as np
+
+from pandas.core.series import Series
+import pandas.core.common as com
+import pandas._tseries as lib
+
+def match(values, index):
+    """
+
+
+    Parameters
+    ----------
+
+    Returns
+    -------
+    match : ndarray
+    """
+    if com.is_float_dtype(index):
+        return _match_generic(values, index, lib.Float64HashTable,
+                              _ensure_float64)
+    elif com.is_integer_dtype(index):
+        return _match_generic(values, index, lib.Int64HashTable,
+                              _ensure_int64)
+    else:
+        return _match_generic(values, index, lib.PyObjectHashTable,
+                              _ensure_object)
+
+
+def count(values, uniques=None):
+    if uniques is not None:
+        raise NotImplementedError
+    else:
+        if com.is_float_dtype(values):
+            return _count_generic(values, lib.Float64HashTable,
+                                  _ensure_float64)
+        elif com.is_integer_dtype(values):
+            return _count_generic(values, lib.Int64HashTable,
+                                  _ensure_int64)
+        else:
+            return _count_generic(values, lib.PyObjectHashTable,
+                                  _ensure_object)
+
+def _count_generic(values, table_type, type_caster):
+    values = type_caster(values)
+    table = table_type(len(values))
+    uniques, labels, counts = table.factorize(values)
+
+    return Series(counts, index=uniques)
+
+def _match_generic(values, index, table_type, type_caster):
+    values = type_caster(values)
+    index = type_caster(index)
+    table = table_type(len(index))
+    table.map_locations(index)
+    return table.lookup(values)
+
+def factorize(values):
+    pass
+
+def unique(values):
+    pass
+
+def _ensure_float64(arr):
+    if arr.dtype != np.float64:
+        arr = arr.astype(np.float64)
+    return arr
+
+def _ensure_int64(arr):
+    if arr.dtype != np.int64:
+        arr = arr.astype(np.int64)
+    return arr
+
+def _ensure_object(arr):
+    if arr.dtype != np.object_:
+        arr = arr.astype('O')
+    return arr