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Merged
merged 5 commits into from
May 21, 2020
Merged

Finalize fixes on WIndows test suite for v0.1.1 #441

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590a523
Fix test due to different mount paths on WIndows
weiji14 May 20, 2020
db8f54f
Merge branch 'master' into fix-win-tests
weiji14 May 21, 2020
6d804d7
Use to_numpy() to convert pd.Series to np.array
weiji14 May 21, 2020
efe35ec
Just use numpy.asarray to convert a vector to numpy array
weiji14 May 21, 2020
9202941
Change ctypes.c_int to ctypes.c_long since they're the same
weiji14 May 21, 2020
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48 changes: 3 additions & 45 deletions pygmt/clib/conversion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -156,7 +156,7 @@ def vectors_to_arrays(vectors):
True

"""
arrays = [as_c_contiguous(_as_array(i)) for i in vectors]
arrays = [as_c_contiguous(np.asarray(i)) for i in vectors]
return arrays


Expand Down Expand Up @@ -203,48 +203,6 @@ def as_c_contiguous(array):
return array


def _as_array(vector):
"""
Convert a vector (pandas.Series, tuple, list or numpy array) to a numpy
array.

If vector is already an array, do nothing.

Parameters
----------
vector : tuple, list, pandas.Series or numpy 1d array
The vector to convert.

Returns
-------
array : numpy array

Examples
--------

>>> import pandas as pd
>>> x_series = pd.Series(data=[1, 2, 3, 4])
>>> x_array = _as_array(x_series)
>>> type(x_array)
<class 'numpy.ndarray'>
>>> x_array
array([1, 2, 3, 4])
>>> import numpy as np
>>> type(_as_array(np.array([5, 6, 7])))
<class 'numpy.ndarray'>
>>> type(_as_array([3, 4, 5]))
<class 'numpy.ndarray'>
>>> type(_as_array((6, 7, 8)))
<class 'numpy.ndarray'>
>>> type(_as_array(range(15)))
<class 'numpy.ndarray'>

"""
if isinstance(vector, pandas.Series):
return vector.values
return np.asarray(vector)


def kwargs_to_ctypes_array(argument, kwargs, dtype):
"""
Convert an iterable argument from kwargs into a ctypes array variable.
Expand All @@ -268,9 +226,9 @@ def kwargs_to_ctypes_array(argument, kwargs, dtype):
--------

>>> import ctypes as ct
>>> value = kwargs_to_ctypes_array('bla', {'bla': [10, 10]}, ct.c_int*2)
>>> value = kwargs_to_ctypes_array('bla', {'bla': [10, 10]}, ct.c_long*2)
>>> type(value)
<class 'pygmt.clib.conversion.c_int_Array_2'>
<class 'pygmt.clib.conversion.c_long_Array_2'>
Comment on lines -271 to +231
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c_int is just an alias for c_long according to https://docs.python.org/3/library/ctypes.html#ctypes-tutorial. Changing it to c_long should make this test pass in a cross-platform way.

>>> should_be_none = kwargs_to_ctypes_array(
... 'swallow', {'bla': 1, 'foo': [20, 30]}, ct.c_int*2)
>>> print(should_be_none)
Expand Down
2 changes: 1 addition & 1 deletion pygmt/tests/test_sphinx_gallery.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ def test_pygmtscraper():
assert len(SHOWED_FIGURES) == 1
assert SHOWED_FIGURES[0] is fig
scraper = PyGMTScraper()
with TemporaryDirectory() as tmpdir:
with TemporaryDirectory(dir=os.getcwd()) as tmpdir:
conf = {"src_dir": "meh"}
fname = os.path.join(tmpdir, "meh.png")
block_vars = {"image_path_iterator": (i for i in [fname])}
Expand Down