File: C:/Users/fred/anaconda3/Lib/site-packages/holoviews/tests/core/data/test_imageinterface.py
import datetime as dt
from unittest import SkipTest
import numpy as np
import pytest
from holoviews import HSV, RGB, Curve, Dataset, Dimension, Image, Table
from holoviews.core.data.interface import DataError
from holoviews.core.util import date_range
from .base import DatatypeContext, GriddedInterfaceTests, InterfaceTests
class ImageInterfaceTests(GriddedInterfaceTests, InterfaceTests):
"""
Tests for ImageInterface
"""
datatype = 'image'
data_type = np.ndarray
element = Image
__test__ = True
def test_canonical_vdim(self):
x = np.array([ 0. , 0.75, 1.5 ])
y = np.array([ 1.5 , 0.75, 0. ])
z = np.array([[ 0.06925999, 0.05800389, 0.05620127],
[ 0.06240918, 0.05800931, 0.04969735],
[ 0.05376789, 0.04669417, 0.03880118]])
dataset = Image((x, y, z), kdims=['x', 'y'], vdims=['z'])
canonical = np.array([[ 0.05376789, 0.04669417, 0.03880118],
[ 0.06240918, 0.05800931, 0.04969735],
[ 0.06925999, 0.05800389, 0.05620127]])
self.assertEqual(dataset.dimension_values('z', flat=False),
canonical)
def test_gridded_dtypes(self):
ds = self.dataset_grid
self.assertEqual(ds.interface.dtype(ds, 'x'), np.float64)
self.assertEqual(ds.interface.dtype(ds, 'y'), np.float64)
self.assertEqual(ds.interface.dtype(ds, 'z'), np.dtype(int))
def test_dataset_groupby_with_transposed_dimensions(self):
raise SkipTest('Image interface does not support multi-dimensional data.')
def test_dataset_dynamic_groupby_with_transposed_dimensions(self):
raise SkipTest('Image interface does not support multi-dimensional data.')
def test_dataset_slice_inverted_dimension(self):
raise SkipTest('Image interface does not support 1D data')
def test_sample_2d(self):
raise SkipTest('Image interface only supports Image type')
class BaseImageElementInterfaceTests(InterfaceTests):
"""
Tests for ImageInterface
"""
element = Image
__test__ = False
def init_grid_data(self):
self.xs = np.linspace(-9, 9, 10)
self.ys = np.linspace(0.5, 9.5, 10)
self.array = np.arange(10) * np.arange(10)[:, np.newaxis]
def init_data(self):
self.image = Image(np.flipud(self.array), bounds=(-10, 0, 10, 10))
def test_init_data_tuple(self):
xs = np.arange(5)
ys = np.arange(10)
array = xs * ys[:, np.newaxis]
Image((xs, ys, array))
def test_init_data_tuple_error(self):
xs = np.arange(5)
ys = np.arange(10)
array = xs * ys[:, np.newaxis]
with self.assertRaises(DataError):
Image((ys, xs, array))
def test_bounds_mismatch(self):
with self.assertRaises(ValueError):
Image((range(10), range(10), np.random.rand(10, 10)), bounds=0.5)
def test_init_data_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10).astype("datetime64[ns]")
Image((xs, self.ys, self.array))
def test_init_data_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10).astype("datetime64[ns]")
Image((self.xs, ys, self.array))
def test_init_bounds(self):
self.assertEqual(self.image.bounds.lbrt(), (-10, 0, 10, 10))
def test_init_bounds_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10).astype("datetime64[ns]")
bounds = (start, 0, end, 10)
image = Image((xs, self.ys, self.array), bounds=bounds)
self.assertEqual(image.bounds.lbrt(), bounds)
def test_init_bounds_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10).astype("datetime64[ns]")
bounds = (-10, start, 10, end)
image = Image((self.xs, ys, self.array))
self.assertEqual(image.bounds.lbrt(), bounds)
def test_init_densities(self):
self.assertEqual(self.image.xdensity, 0.5)
self.assertEqual(self.image.ydensity, 1)
def test_init_densities_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10).astype("datetime64[ns]")
image = Image((xs, self.ys, self.array))
self.assertEqual(image.xdensity, 1e-5)
self.assertEqual(image.ydensity, 1)
def test_init_densities_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10).astype("datetime64[ns]")
image = Image((self.xs, ys, self.array))
self.assertEqual(image.xdensity, 0.5)
self.assertEqual(image.ydensity, 1e-5)
def test_dimension_values_xs(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_ys(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_dimension_values_vdim(self):
self.assertEqual(self.image.dimension_values(2, flat=False),
self.array)
def test_index_single_coordinate(self):
self.assertEqual(self.image[0.3, 5.1], 25)
def test_slice_xaxis(self):
sliced = self.image[0.3:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 0, 6, 10))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[:, 5:8])
def test_slice_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
bounds = (start, 0, end, 10)
xs = date_range(start, end, 10).astype("datetime64[ns]")
image = Image((xs, self.ys, self.array), bounds=bounds)
sliced = image[start+np.timedelta64(530, 'ms'): start+np.timedelta64(770, 'ms')]
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[:, 5:8])
def test_slice_yaxis(self):
sliced = self.image[:, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (-10, 1., 10, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, :])
def test_slice_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10).astype("datetime64[ns]")
image = Image((self.xs, ys, self.array))
sliced = image[:, start+np.timedelta64(120, 'ms'): start+np.timedelta64(520, 'ms')]
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, :])
def test_slice_both_axes(self):
sliced = self.image[0.3:5.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 1., 6, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 5:8])
def test_slice_x_index_y(self):
sliced = self.image[0.3:5.2, 5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 5.0, 6.0, 6.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[5:6, 5:8])
def test_index_x_slice_y(self):
sliced = self.image[3.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (2.0, 1.0, 4.0, 5.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 6:7])
def test_range_xdim(self):
self.assertEqual(self.image.range(0), (-10, 10))
def test_range_datetime_xdim(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10).astype("datetime64[ns]")
image = Image((xs, self.ys, self.array))
self.assertEqual(image.range(0), (start, end))
def test_range_ydim(self):
self.assertEqual(self.image.range(1), (0, 10))
def test_range_datetime_ydim(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10).astype("datetime64[ns]")
image = Image((self.xs, ys, self.array))
self.assertEqual(image.range(1), (start, end))
def test_range_vdim(self):
self.assertEqual(self.image.range(2), (0, 81))
def test_dimension_values_xcoords(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_datetime_xcoords(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10).astype("datetime64[ns]")
image = Image((xs, self.ys, self.array))
self.assertEqual(image.dimension_values(0, expanded=False),
date_range(start, end, 10))
def test_dimension_values_ycoords(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_sample_xcoord(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0, 7, 14, 21, 28, 35, 42, 49, 56, 63]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.image):
self.assertEqual(self.image.sample(x=5),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_sample_ycoord(self):
xs = np.linspace(-9, 9, 10)
zs = [0, 4, 8, 12, 16, 20, 24, 28, 32, 36]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.image):
self.assertEqual(self.image.sample(y=5),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_sample_coords(self):
arr = np.arange(10)*np.arange(5)[np.newaxis].T
xs = np.linspace(0.12, 0.81, 10)
ys = np.linspace(0.12, 0.391, 5)
img = Image((xs, ys, arr), kdims=['x', 'y'], vdims=['z'], datatype=[self.datatype])
sampled = img.sample([(0.15, 0.15), (0.15, 0.4), (0.8, 0.4), (0.8, 0.15)])
self.assertIsInstance(sampled, Table)
yidx = [0, 4, 4, 0]
xidx = [0, 0, 9, 9]
table = Table((xs[xidx], ys[yidx], arr[yidx, xidx]), kdims=['x', 'y'], vdims=['z'])
self.assertEqual(sampled, table)
def test_reduce_to_scalar(self):
self.assertEqual(self.image.reduce(['x', 'y'], function=np.mean),
20.25)
def test_reduce_x_dimension(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], Image):
self.assertEqual(self.image.reduce(x=np.mean),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_reduce_y_dimension(self):
xs = np.linspace(-9, 9, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], Image):
self.assertEqual(self.image.reduce(y=np.mean),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_dataset_reindex_constant(self):
with DatatypeContext([self.datatype, 'dictionary', 'dataframe', 'grid'], self.image):
selected = Dataset(self.image.select(x=0))
reindexed = selected.reindex(['y'])
data = Dataset(selected.columns(['y', 'z']),
kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_dataset_reindex_non_constant(self):
with DatatypeContext([self.datatype, 'dictionary', 'dataframe', 'grid'], self.image):
ds = Dataset(self.image)
reindexed = ds.reindex(['y'])
data = Dataset(ds.columns(['y', 'z']),
kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_aggregate_with_spreadfn(self):
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.image):
agg = self.image.aggregate('x', np.mean, np.std)
xs = self.image.dimension_values('x', expanded=False)
mean = self.array.mean(axis=0)
std = self.array.std(axis=0)
self.assertEqual(agg, Curve((xs, mean, std), kdims=['x'],
vdims=['z', 'z_std']))
class ImageElement_ImageInterfaceTests(BaseImageElementInterfaceTests):
datatype = 'image'
data_type = np.ndarray
__test__ = True
class BaseRGBElementInterfaceTests(InterfaceTests):
element = RGB
__test__ = False
def init_grid_data(self):
self.xs = np.linspace(-9, 9, 10)
self.ys = np.linspace(0.5, 9.5, 10)
self.rgb_array = np.random.rand(10, 10, 3)
def init_data(self):
self.rgb = RGB(self.rgb_array[::-1], bounds=(-10, 0, 10, 10))
def test_init_bounds(self):
self.assertEqual(self.rgb.bounds.lbrt(), (-10, 0, 10, 10))
def test_init_densities(self):
self.assertEqual(self.rgb.xdensity, 0.5)
self.assertEqual(self.rgb.ydensity, 1)
def test_dimension_values_xs(self):
self.assertEqual(self.rgb.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_ys(self):
self.assertEqual(self.rgb.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_dimension_values_vdims(self):
self.assertEqual(self.rgb.dimension_values(2, flat=False),
self.rgb_array[:, :, 0])
self.assertEqual(self.rgb.dimension_values(3, flat=False),
self.rgb_array[:, :, 1])
self.assertEqual(self.rgb.dimension_values(4, flat=False),
self.rgb_array[:, :, 2])
def test_slice_xaxis(self):
sliced = self.rgb[0.3:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 0, 6, 10))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.rgb_array[:, 5:8, 0])
def test_slice_yaxis(self):
sliced = self.rgb[:, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (-10, 1., 10, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.rgb_array[1:5, :, 0])
def test_slice_both_axes(self):
sliced = self.rgb[0.3:5.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 1., 6, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.rgb_array[1:5, 5:8, 0])
def test_slice_x_index_y(self):
sliced = self.rgb[0.3:5.2, 5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 5.0, 6.0, 6.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.rgb_array[5:6, 5:8, 0])
def test_index_x_slice_y(self):
sliced = self.rgb[3.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (2.0, 1.0, 4.0, 5.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.rgb_array[1:5, 6:7, 0])
def test_select_value_dimension_rgb(self):
self.assertEqual(self.rgb[..., 'R'],
Image(np.flipud(self.rgb_array[:, :, 0]), bounds=self.rgb.bounds,
vdims=[Dimension('R', range=(0, 1))], datatype=['image']))
def test_select_single_coordinate(self):
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.rgb):
self.assertEqual(self.rgb[5.2, 3.1],
self.rgb.clone([tuple(self.rgb_array[3, 7])],
kdims=[], new_type=Dataset))
def test_reduce_to_single_values(self):
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.rgb):
self.assertEqual(self.rgb.reduce(['x', 'y'], function=np.mean),
self.rgb.clone([tuple(np.mean(self.rgb_array, axis=(0, 1)))],
kdims=[], new_type=Dataset))
def test_sample_xcoord(self):
ys = np.linspace(0.5, 9.5, 10)
data = (ys,) + tuple(self.rgb_array[:, 7, i] for i in range(3))
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.rgb):
self.assertEqual(self.rgb.sample(x=5),
self.rgb.clone(data, kdims=['y'],
new_type=Curve))
def test_sample_ycoord(self):
xs = np.linspace(-9, 9, 10)
data = (xs,) + tuple(self.rgb_array[4, :, i] for i in range(3))
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.rgb):
self.assertEqual(self.rgb.sample(y=5),
self.rgb.clone(data, kdims=['x'],
new_type=Curve))
def test_dataset_reindex_constant(self):
with DatatypeContext([self.datatype, 'dictionary', 'dataframe', 'grid'], self.rgb):
ds = Dataset(self.rgb.select(x=0))
reindexed = ds.reindex(['y'], ['R'])
data = Dataset(ds.columns(['y', 'R']),
kdims=['y'], vdims=[ds.vdims[0]])
self.assertEqual(reindexed, data)
def test_dataset_reindex_non_constant(self):
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe', 'grid'], self.rgb):
ds = Dataset(self.rgb)
reindexed = ds.reindex(['y'], ['R'])
data = Dataset(ds.columns(['y', 'R']),
kdims=['y'], vdims=[ds.vdims[0]])
self.assertEqual(reindexed, data)
class RGBElement_ImageInterfaceTests(BaseRGBElementInterfaceTests):
datatype = 'image'
__test__ = True
@pytest.mark.xfail(reason="Raises DataError in ImageInterface")
def test_reduce_to_single_values(self):
super().test_reduce_to_single_values()
class BaseHSVElementInterfaceTests(InterfaceTests):
element = HSV
__test__ = False
def init_grid_data(self):
self.xs = np.linspace(-9, 9, 3)
self.ys = np.linspace(0.5, 9.5, 3)
self.hsv_array = np.zeros((3, 3, 3))
self.hsv_array[0, 0] = 1
def init_data(self):
self.hsv = HSV(self.hsv_array[::-1], bounds=(-10, 0, 10, 10))
def test_hsv_rgb_interface(self):
R = self.hsv.rgb[..., 'R'].dimension_values(2, expanded=False, flat=False)
G = self.hsv.rgb[..., 'G'].dimension_values(2, expanded=False, flat=False)
B = self.hsv.rgb[..., 'B'].dimension_values(2, expanded=False, flat=False)
self.assertEqual(R[0, 0], 1)
self.assertEqual(G[0, 0], 0)
self.assertEqual(B[0, 0], 0)
class HSVElement_ImageInterfaceTests(BaseHSVElementInterfaceTests):
datatype = 'image'
__test__ = True