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Remove unused, avoid uses of deprecated api #22071

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Merged
merged 19 commits into from
Jul 31, 2018
Merged

Remove unused, avoid uses of deprecated api #22071

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f9a95e7
remove unused is_period
jbrockmendel Jul 26, 2018
4e05a07
move unused utils to _libs.util, docstrings
jbrockmendel Jul 26, 2018
d1cfac8
remove usages of deprecated API
jbrockmendel Jul 26, 2018
cf84856
docstring
jbrockmendel Jul 26, 2018
abda192
whitespace, docstring cleanup
jbrockmendel Jul 26, 2018
6d8c335
use util.is_array
jbrockmendel Jul 26, 2018
9360a85
update import
jbrockmendel Jul 26, 2018
ca05636
update test
jbrockmendel Jul 26, 2018
1f326e2
remove unused import
jbrockmendel Jul 26, 2018
82228e1
avoid need for cnp in util
jbrockmendel Jul 27, 2018
1dc6fff
Merge branch 'master' of https://github.com/pandas-dev/pandas into rm
jbrockmendel Jul 27, 2018
d318cc8
troubleshoot appveyor failure
jbrockmendel Jul 27, 2018
d25070d
try getting NPY_MIN_INT64 directly
jbrockmendel Jul 27, 2018
bed3eed
disentangle util from src, docstring
jbrockmendel Jul 27, 2018
6320a2c
dummy commit to allow push
jbrockmendel Jul 28, 2018
2650222
Merge branch 'master' of https://github.com/pandas-dev/pandas into rm
jbrockmendel Jul 28, 2018
d952272
revert removal of is_period
jbrockmendel Jul 29, 2018
559a461
Merge branch 'master' of https://github.com/pandas-dev/pandas into rm
jbrockmendel Jul 29, 2018
e6fa730
revert is_period changes
jbrockmendel Jul 30, 2018
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2 changes: 1 addition & 1 deletion pandas/_libs/algos.pyx
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Expand Up @@ -129,7 +129,7 @@ def is_lexsorted(list list_of_arrays):
for i in range(nlevels):
arr = list_of_arrays[i]
assert arr.dtype.name == 'int64'
vecs[i] = <int64_t*> arr.data
vecs[i] = <int64_t*> cnp.PyArray_DATA(arr)

# Assume uniqueness??
with nogil:
Expand Down
4 changes: 3 additions & 1 deletion pandas/_libs/groupby.pyx
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Expand Up @@ -7,10 +7,12 @@ from cython cimport Py_ssize_t
from libc.stdlib cimport malloc, free

import numpy as np
cimport numpy as cnp
from numpy cimport (ndarray,
double_t,
int8_t, int16_t, int32_t, int64_t, uint8_t, uint16_t,
uint32_t, uint64_t, float32_t, float64_t)
cnp.import_array()


from util cimport numeric, get_nat
Expand Down Expand Up @@ -118,7 +120,7 @@ def group_median_float64(ndarray[float64_t, ndim=2] out,
counts[:] = _counts[1:]

data = np.empty((K, N), dtype=np.float64)
ptr = <float64_t*> data.data
ptr = <float64_t*> cnp.PyArray_DATA(data)

take_2d_axis1_float64_float64(values.T, indexer, out=data)

Expand Down
6 changes: 3 additions & 3 deletions pandas/_libs/index.pyx
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Expand Up @@ -37,7 +37,7 @@ cdef inline bint is_definitely_invalid_key(object val):
return True

# we have a _data, means we are a NDFrame
return (PySlice_Check(val) or cnp.PyArray_Check(val)
return (PySlice_Check(val) or util.is_array(val)
or PyList_Check(val) or hasattr(val, '_data'))


Expand Down Expand Up @@ -104,7 +104,7 @@ cdef class IndexEngine:
void* data_ptr

loc = self.get_loc(key)
if PySlice_Check(loc) or cnp.PyArray_Check(loc):
if PySlice_Check(loc) or util.is_array(loc):
return arr[loc]
else:
return get_value_at(arr, loc, tz=tz)
Expand All @@ -120,7 +120,7 @@ cdef class IndexEngine:
loc = self.get_loc(key)
value = convert_scalar(arr, value)

if PySlice_Check(loc) or cnp.PyArray_Check(loc):
if PySlice_Check(loc) or util.is_array(loc):
arr[loc] = value
else:
util.set_value_at(arr, loc, value)
Expand Down
14 changes: 3 additions & 11 deletions pandas/_libs/src/numpy_helper.h
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Expand Up @@ -16,8 +16,6 @@ The full license is in the LICENSE file, distributed with this software.
#include "numpy/arrayscalars.h"


PANDAS_INLINE npy_int64 get_nat(void) { return NPY_MIN_INT64; }

PANDAS_INLINE int assign_value_1d(PyArrayObject* ap, Py_ssize_t _i,
PyObject* v) {
npy_intp i = (npy_intp)_i;
Expand All @@ -40,16 +38,10 @@ PANDAS_INLINE const char* get_c_string(PyObject* obj) {
#endif
}

PANDAS_INLINE PyObject* char_to_string(const char* data) {
#if PY_VERSION_HEX >= 0x03000000
return PyUnicode_FromString(data);
#else
return PyString_FromString(data);
#endif
}

void set_array_not_contiguous(PyArrayObject* ao) {
ao->flags &= ~(NPY_ARRAY_C_CONTIGUOUS | NPY_ARRAY_F_CONTIGUOUS);
// Numpy>=1.8-compliant equivalent to:
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we are numpy >= 1.9! can this be simplified?

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No. The existing implementation uses the deprecated numpy API.

// ao->flags &= ~(NPY_ARRAY_C_CONTIGUOUS | NPY_ARRAY_F_CONTIGUOUS);
PyArray_CLEARFLAGS(ao, (NPY_ARRAY_C_CONTIGUOUS | NPY_ARRAY_F_CONTIGUOUS));
}

#endif // PANDAS__LIBS_SRC_NUMPY_HELPER_H_
2 changes: 1 addition & 1 deletion pandas/_libs/tslibs/conversion.pyx
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Expand Up @@ -888,7 +888,7 @@ def tz_localize_to_utc(ndarray[int64_t] vals, object tz, object ambiguous=None,

trans, deltas, typ = get_dst_info(tz)

tdata = <int64_t*> trans.data
tdata = <int64_t*> cnp.PyArray_DATA(trans)
ntrans = len(trans)

result_a = np.empty(n, dtype=np.int64)
Expand Down
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