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import unittest
import numpy as np
import copy
from mcstasscript.data.data import McStasDataBinned
from mcstasscript.data.data import McStasMetaData
from mcstasscript.jb_interface.simulation_interface import add_data
def set_dummy_MetaDataBinned_1d():
"""
Sets up simple McStasMetaData object with dimension, 1d case
"""
meta_data = McStasMetaData()
meta_data.component_name = "component for 1d"
meta_data.filename = "data.dat"
meta_data.dimension = 50
meta_data.info = {"Ncount" : 40}
return meta_data
def set_dummy_McStasDataBinned_1d():
"""
Sets up simple McStasData object, 1d case
"""
meta_data = set_dummy_MetaDataBinned_1d()
intensity = np.ones(20)
error = np.ones(20)
ncount = np.ones(20)
axis = np.arange(20)*5.0
return McStasDataBinned(meta_data, intensity, error, ncount, xaxis=axis)
def set_dummy_MetaDataBinned_2d():
"""
Sets up simple McStasMetaData object with dimensions, 2d case
"""
meta_data = McStasMetaData()
meta_data.component_name = "test a component"
meta_data.filename = "data.dat"
meta_data.dimension = [50, 100]
meta_data.info = {"Ncount": 40}
return meta_data
def set_dummy_McStasDataBinned_2d():
"""
Sets up simple McStasData object, 2d case
"""
meta_data = set_dummy_MetaDataBinned_2d()
intensity = np.ones(20).reshape(4, 5)
error = np.ones(20).reshape(4, 5)
ncount = np.ones(20).reshape(4, 5)
return McStasDataBinned(meta_data, intensity, error, ncount)
class Test_add_data(unittest.TestCase):
def test_1d_updates_correctly(self):
"""
Test that adding 1d dataset modifies only the intended dataset
"""
data1 = set_dummy_McStasDataBinned_1d()
data1_original = copy.deepcopy(data1)
data2 = set_dummy_McStasDataBinned_1d()
data2_original = copy.deepcopy(data2)
add_data([data1], [data2])
# Data 2 should not be touched
self.assertTrue(np.array_equal(data2.Intensity, data2_original.Intensity))
self.assertTrue(np.array_equal(data2.Error, data2_original.Error))
self.assertTrue(np.array_equal(data2.Ncount, data2_original.Ncount))
# Data 1 Intensity should be unchanged, as data1 and data2 equal
self.assertTrue(np.array_equal(data1.Intensity, data1_original.Intensity))
# Data 1 should be updated
self.assertFalse(np.array_equal(data1.Error, data1_original.Error))
self.assertFalse(np.array_equal(data1.Ncount, data1_original.Ncount))
def test_1d_updates_different(self):
"""
Test that adding 1d datasets work as expected when different
"""
data1 = set_dummy_McStasDataBinned_1d()
data1.Intensity *= 2.0
data1.Intensity[10:] *= 2.0
data1.Error *= 1.5
data1.Ncount *= 4.0
data1.metadata.info["Ncount"] *= 4.0
data1_original = copy.deepcopy(data1)
data2 = set_dummy_McStasDataBinned_1d()
data2.Intensity *= 3.0
data2.Error *= 1.5
data2_original = copy.deepcopy(data2)
add_data([data1], [data2])
# Data 2 should not be touched
self.assertTrue(np.array_equal(data2.Intensity, data2_original.Intensity))
self.assertTrue(np.array_equal(data2.Error, data2_original.Error))
self.assertTrue(np.array_equal(data2.Ncount, data2_original.Ncount))
# 4 times more weight on data1, intensity 2 and 3
expected_low_intensity = 4/5*2.0 + 1/5*3.0
# 4 times more weight on data1, intensity 4 and 3
expected_high_intensity = 4/5*2.0*2.0 + 1/5*3.0
expected_error = np.sqrt((4 / 5) ** 2 * 1.5 ** 2 + (1 / 5) ** 2 * 1.5 ** 2)
for index in range(len(data1_original.Intensity)):
if index < 10:
self.assertEqual(data1.Intensity[index], expected_low_intensity)
else:
self.assertEqual(data1.Intensity[index], expected_high_intensity)
self.assertEqual(data1.Error[index], expected_error)
self.assertEqual(data1.Ncount[index], 5.0)
self.assertEqual(data1.metadata.info["Ncount"], 40*4+40)
def test_fail(self):
"""
Test that adding datasets fail when they dont have the same monitors
Both 1d and 2d cases included.
"""
data11 = set_dummy_McStasDataBinned_1d()
data11.name = "first monitor"
data11.filename = "first_monitor.dat"
data12 = set_dummy_McStasDataBinned_2d()
data12.name = "second monitor"
data12.filename = "second_monitor.dat"
data13 = set_dummy_McStasDataBinned_1d()
data13.name = "third monitor"
data13.filename = "third_monitor.dat"
data21 = set_dummy_McStasDataBinned_1d()
data21.name = "first monitor"
data21.filename = "first_monitor.dat"
data22 = set_dummy_McStasDataBinned_2d()
data22.name = "second monitor"
data22.filename = "second_monitor.dat"
data23 = set_dummy_McStasDataBinned_1d()
data23.name = "third monitor"
data23.filename = "third_monitor.dat"
# Should succeed, monitors match
add_data([data11, data12, data13], [data21, data22, data23])
# Should succeed, all monitors needed to update first argument present
add_data([data11, data12], [data21, data22, data23])
# Should fail if a monitor is missing
with self.assertRaises(NameError):
add_data([data11, data12, data13], [data21, data22])
data23.name = "different monitor"
# Should fail if name mismatch
with self.assertRaises(NameError):
add_data([data11, data12, data13], [data21, data22, data23])
def test_2d_updates_correctly(self):
"""
Test that adding 1d dataset modifies only the intended dataset
"""
data1 = set_dummy_McStasDataBinned_2d()
data1_original = copy.deepcopy(data1)
data2 = set_dummy_McStasDataBinned_2d()
data2_original = copy.deepcopy(data2)
add_data([data1], [data2])
# Data 2 should not be touched
self.assertTrue(np.array_equal(data2.Intensity, data2_original.Intensity))
self.assertTrue(np.array_equal(data2.Error, data2_original.Error))
self.assertTrue(np.array_equal(data2.Ncount, data2_original.Ncount))
# Data 1 Intensity should be unchanged, as data1 and data2 equal
self.assertTrue(np.array_equal(data1.Intensity, data1_original.Intensity))
# Data 1 should be updated
self.assertFalse(np.array_equal(data1.Error, data1_original.Error))
self.assertFalse(np.array_equal(data1.Ncount, data1_original.Ncount))
def test_2d_updates_different(self):
"""
Test that adding 2d datasets work as expected when different
"""
data1 = set_dummy_McStasDataBinned_2d()
data1.Intensity *= 2.0
data1.Intensity[1,:] *= 2.0
data1.Error *= 1.5
data1.Ncount *= 4.0
data1.metadata.info["Ncount"] *= 4.0
data1_original = copy.deepcopy(data1)
data2 = set_dummy_McStasDataBinned_2d()
data2.Intensity *= 3.0
data2.Error *= 1.5
data2_original = copy.deepcopy(data2)
add_data([data1], [data2])
# Data 2 should not be touched
self.assertTrue(np.array_equal(data2.Intensity, data2_original.Intensity))
self.assertTrue(np.array_equal(data2.Error, data2_original.Error))
self.assertTrue(np.array_equal(data2.Ncount, data2_original.Ncount))
# 4 times more weight on data1, intensity 2 and 3
expected_low_intensity = 4/5*2.0 + 1/5*3.0
# 4 times more weight on data1, intensity 4 and 3
expected_high_intensity = 4/5*2.0*2.0 + 1/5*3.0
expected_error = np.sqrt((4 / 5) ** 2 * 1.5 ** 2 + (1 / 5) ** 2 * 1.5 ** 2)
for index1 in range(len(data1_original.Intensity[:,0])):
for index2 in range(len(data1_original.Intensity[0, :])):
if index1 == 1:
self.assertEqual(data1.Intensity[index1, index2], expected_high_intensity)
else:
self.assertEqual(data1.Intensity[index1, index2], expected_low_intensity)
self.assertEqual(data1.Error[index1, index2], expected_error)
self.assertEqual(data1.Ncount[index1, index2], 5.0)
self.assertEqual(data1.metadata.info["Ncount"], 40*4+40)
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