def test_datetime_series_binops_numpy(lhs_dtype, rhs_dtype):
pd_data_1 = pd.Series(
pd.date_range("20010101", "20020215", freq="400h", name="times"))
pd_data_2 = pd.Series(
pd.date_range("20010101", "20020215", freq="401h", name="times"))
gdf_data_1 = Series(pd_data_1).astype(lhs_dtype)
gdf_data_2 = Series(pd_data_2).astype(rhs_dtype)
np_data_1 = np.array(pd_data_1).astype(lhs_dtype)
np_data_2 = np.array(pd_data_2).astype(rhs_dtype)
np.testing.assert_equal(np_data_1, gdf_data_1.to_array())
np.testing.assert_equal(np_data_2, gdf_data_2.to_array())
np.testing.assert_equal(np.less(np_data_1, np_data_2),
(gdf_data_1 < gdf_data_2).to_array())
np.testing.assert_equal(np.greater(np_data_1, np_data_2),
(gdf_data_1 > gdf_data_2).to_array())
np.testing.assert_equal(np.equal(np_data_1, np_data_2),
(gdf_data_1 == gdf_data_2).to_array())
np.testing.assert_equal(
np.less_equal(np_data_1, np_data_2),
(gdf_data_1 <= gdf_data_2).to_array(),
)
np.testing.assert_equal(
np.greater_equal(np_data_1, np_data_2),
(gdf_data_1 >= gdf_data_2).to_array(),
)
def test_series_argsort(nelem, dtype, asc):
np.random.seed(0)
sr = Series((100 * np.random.random(nelem)).astype(dtype))
res = sr.argsort(ascending=asc)
if asc:
expected = np.argsort(sr.to_array(), kind="mergesort")
else:
expected = np.argsort(sr.to_array() * -1, kind="mergesort")
np.testing.assert_array_equal(expected, res.to_array())
def test_series_sort_index(nelem, asc):
np.random.seed(0)
sr = Series((100 * np.random.random(nelem)))
orig = sr.to_array()
got = sr.sort_values().sort_index(ascending=asc).to_array()
if not asc:
# Reverse the array for descending sort
got = got[::-1]
np.testing.assert_array_equal(orig, got)
plyreader = shapefile.Reader("NYC_boroughs.shp")
polygons = plyreader.shapes()
plys = []
for ply in polygons:
plys.append(shape(ply))
start = time.time()
bm1 = cpp_point_in_polygon_bitmap(x1, y1, NYC_gpu[0], NYC_gpu[1],
NYC_gpu[2]['x'], NYC_gpu[2]['y'])
bm2 = cpp_point_in_polygon_bitmap(x2, y2, NYC_gpu[0], NYC_gpu[1],
NYC_gpu[2]['x'], NYC_gpu[2]['y'])
end = time.time()
print("Python GPU Time in ms (end-to-end)={}".format((end - start) * 1000))
bm1a = bm1.to_array()
pntx = x1.to_array()
pnty = y1.to_array()
start = time.time()
mis_match = 0
#for i in range(len(pntx)):
for i in range(10000):
pt = Point(pntx[i], pnty[i])
res = 0
for j in range(len(plys)):
pip = plys[len(plys) - 1 - j].contains(pt)
if pip:
res |= 0x01 << (len(plys) - 1 - j)
#print("cpu={}, gpu={}".format(res,bm1a[i]))
#print("{},{},{},{}".format(pntx[i], pnty[i],bm1a[i],res))
if res != bm1a[i]:
def test_typecast_to_different_datetime_resolutions(data, dtype):
pd_data = pd.Series(data.copy())
np_data = np.array(pd_data).astype(dtype)
gdf_series = Series(pd_data).astype(dtype)
np.testing.assert_equal(np_data, gdf_series.to_array())
