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delete some functions in pd_dataframe_ext.py #799

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AlexanderKalistratov merged 16 commits into from
Apr 20, 2020
Merged

delete some functions in pd_dataframe_ext.py #799

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8873758
delete some files in pd_dataframe_ext.py
Rubtsowa Apr 10, 2020
7dc6cf6
Merge branch 'master' of https://github.com/IntelPython/hpat into del…
Rubtsowa Apr 10, 2020
c0092f0
delete dataframe_pass
Rubtsowa Apr 13, 2020
bfff6a2
delete datetime_date_ext
Rubtsowa Apr 13, 2020
a1dcf01
delete some functions in pd_categorical_ext
Rubtsowa Apr 13, 2020
234b8d3
delete some functions in split_iml
Rubtsowa Apr 13, 2020
dbc9b71
delete some functions in pd_series_ext
Rubtsowa Apr 13, 2020
d8e1da3
delete some functions in join.py
Rubtsowa Apr 14, 2020
a0dc9f8
delete some functions in hiframes
Rubtsowa Apr 14, 2020
b10b8a3
delete some functions in aggregate.py
Rubtsowa Apr 16, 2020
923c3c2
delete some functions in api.py
Rubtsowa Apr 16, 2020
d815f09
delete some functions in split_impl.py
Rubtsowa Apr 17, 2020
e63ac85
delete some functions in pd_timestamp_ext.py
Rubtsowa Apr 17, 2020
8ac16d9
delete some functions in join.py
Rubtsowa Apr 17, 2020
5b19fa6
delete pd_index_ext.py
Rubtsowa Apr 20, 2020
6592675
delete hiframes_untyped.py
Rubtsowa Apr 20, 2020
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delete some functions in pd_categorical_ext
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@Rubtsowa
Rubtsowa committed Apr 13, 2020
commit a1dcf01c773fb08b23d574b45a8f13d91ece8729
78 changes: 0 additions & 78 deletions sdc/hiframes/pd_categorical_ext.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,12 +29,10 @@
from numba.extending import (box, unbox, typeof_impl, register_model, models,
NativeValue, lower_builtin, lower_cast, overload,
type_callable, overload_method, intrinsic)
from numba.targets.imputils import impl_ret_borrowed
from numba import types
from numba.targets.boxing import box_array, unbox_array

import numpy as np
import pandas as pd


class PDCategoricalDtype(types.Opaque):
Expand All @@ -44,31 +42,13 @@ def __init__(self, _categories):
super(PDCategoricalDtype, self).__init__(name=name)


@register_model(PDCategoricalDtype)
class CategoricalDtypeModel(models.IntegerModel):
def __init__(self, dmm, fe_type):
int_dtype = get_categories_int_type(fe_type)
super(CategoricalDtypeModel, self).__init__(dmm, int_dtype)


# Array of categorical data (similar to Pandas Categorical array)
# same as Array but knows how to box etc.
# TODO: defer to Array for all operations
class CategoricalArray(types.Array):
def __init__(self, dtype):
self.dtype = dtype
super(CategoricalArray, self).__init__(
dtype, 1, 'C', name='CategoricalArray({})'.format(dtype))


@register_model(CategoricalArray)
class CategoricalArrayModel(models.ArrayModel):
def __init__(self, dmm, fe_type):
int_dtype = get_categories_int_type(fe_type.dtype)
data_array = types.Array(int_dtype, 1, 'C')
super(CategoricalArrayModel, self).__init__(dmm, data_array)


@unbox(CategoricalArray)
def unbox_categorical_array(typ, val, c):
arr_obj = c.pyapi.object_getattr_string(val, "codes")
Expand Down Expand Up @@ -105,15 +85,7 @@ def box_categorical_array(typ, val, c):
idx = c.context.get_constant(types.intp, i)
c.pyapi.incref(item_objs[i])
c.pyapi.list_setitem(list_obj, idx, item_objs[i])
# TODO: why does list_pack crash for test_csv_cat2?
#list_obj = c.pyapi.list_pack(item_objs)

# call pd.api.types.CategoricalDtype(['A', 'B', 'C'])
# api_obj = c.pyapi.object_getattr_string(pd_class_obj, "api")
# types_obj = c.pyapi.object_getattr_string(api_obj, "types")
# pd_dtype = c.pyapi.call_method(types_obj, "CategoricalDtype", (list_obj,))
# c.pyapi.decref(api_obj)
# c.pyapi.decref(types_obj)

int_dtype = get_categories_int_type(dtype)
arr = box_array(types.Array(int_dtype, 1, 'C'), val, c)
Expand All @@ -138,53 +110,3 @@ def _get_cat_obj_items(categories, c):

dtype = numba.typeof(val)
return [c.box(dtype, c.context.get_constant(dtype, item)) for item in categories]

# HACK: dummy overload for CategoricalDtype to avoid type inference errors
# TODO: implement dtype properly
@overload(pd.api.types.CategoricalDtype)
def cat_overload_dummy(val_list):
return lambda val_list: 1


@intrinsic
def fix_cat_array_type(typingctx, arr=None):
# fix array type from Array(CatDtype) to CategoricalArray(CatDtype)
# no-op for other arrays
fixed_arr = arr
if isinstance(arr.dtype, PDCategoricalDtype):
fixed_arr = CategoricalArray(arr.dtype)

def codegen(context, builder, sig, args):
return impl_ret_borrowed(context, builder, sig.return_type, args[0])

return fixed_arr(arr), codegen


@intrinsic
def cat_array_to_int(typingctx, arr=None):
# TODO: fix aliasing
# get the underlying integer array for a CategoricalArray
out_arr = arr
if isinstance(arr.dtype, PDCategoricalDtype):
int_dtype = get_categories_int_type(arr.dtype)
out_arr = types.Array(int_dtype, 1, 'C')

def codegen(context, builder, sig, args):
return impl_ret_borrowed(context, builder, sig.return_type, args[0])

return out_arr(arr), codegen


@overload_method(CategoricalArray, 'copy')
def cat_arr_copy_overload(arr):
return lambda arr: set_cat_dtype(cat_array_to_int(arr).copy(), arr)


@intrinsic
def set_cat_dtype(typingctx, arr, cat_arr=None):
# set dtype of integer array to categorical from categorical array

def codegen(context, builder, sig, args):
return impl_ret_borrowed(context, builder, sig.return_type, args[0])

return cat_arr(arr, cat_arr), codegen