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import numpy as np
from glue.core.component import Component, CategoricalComponent
from glue.core.data import Data
def test_histogram_data():
data = Data(label="Test Data")
comp_a = Component(np.random.uniform(size=500))
comp_b = Component(np.random.normal(size=500))
data.add_component(comp_a, 'uniform')
data.add_component(comp_b, 'normal')
return data
def test_data():
data = Data(label="Test Data 1")
data2 = Data(label="Teset Data 2")
comp_a = Component(np.array([1, 2, 3]))
comp_b = Component(np.array([1, 2, 3]))
comp_c = Component(np.array([2, 4, 6]))
comp_d = Component(np.array([1, 3, 5]))
data.add_component(comp_a, 'a')
data.add_component(comp_b, 'b')
data2.add_component(comp_c, 'c')
data2.add_component(comp_d, 'd')
return data, data2
def test_categorical_data():
data = Data(label="Test Cat Data 1")
data2 = Data(label="Teset Cat Data 2")
comp_x1 = CategoricalComponent(np.array(['a', 'a', 'b']))
comp_y1 = Component(np.array([1, 2, 3]))
comp_x2 = CategoricalComponent(np.array(['c', 'a', 'b']))
comp_y2 = Component(np.array([1, 3, 5]))
data.add_component(comp_x1, 'x1')
data.add_component(comp_y1, 'y1')
data2.add_component(comp_x2, 'x2')
data2.add_component(comp_y2, 'y2')
return data, data2
def test_image():
data = Data(label="Test Image")
comp_a = Component(np.ones((25, 25)))
data.add_component(comp_a, 'test_1')
comp_b = Component(np.zeros((25, 25)))
data.add_component(comp_b, 'test_2')
return data
def test_cube():
data = Data(label="Test Cube")
comp_a = Component(np.ones((16, 16, 16)))
data.add_component(comp_a, 'test_3')
return data
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