import numpy as np import unittest from pylst.temperature import ( BrightnessTemperatureLandsat, SplitWindowJiminezMunozLST, SplitWindowKerrLST, SplitWindowMcMillinLST, SplitWindowPriceLST, SplitWindowSobrino1993LST, ) # Test class for SplitWindowSobrino1993LST class TestSplitWindowSobrino1993LST(unittest.TestCase): # Sample data initialization sample_band_10 = np.zeros((5, 5)) # Sample Band 10 data mask = np.random.randint(0, high=2, size=(5, 5), dtype=int) == 1 # Random mask data # Test for output and input size equality def test_output_and_input_size_equal(self): # Running the SplitWindowSobrino1993LST algorithm output = SplitWindowSobrino1993LST()( emissivity_10=self.sample_band_10, emissivity_11=self.sample_band_10, brightness_temperature_10=self.sample_band_10, brightness_temperature_11=self.sample_band_10, mask=self.mask, ) self.assertEqual(self.sample_band_10.shape, output.shape) # Checking if output size matches input size # Test for ensuring maximum temperature is within the acceptable range def test_max_temp_less_than_or_equal_max_earth_temp(self): lst_algorithm = SplitWindowSobrino1993LST() # Checking if the maximum earth temperature matches the expected value self.assertEqual(lst_algorithm.max_earth_temp, 273.15 + 56.7) # Test class for SplitWindowJiminezMunozLST functionality class TestSplitWindowJiminezMunozLST(unittest.TestCase): # Creating sample data for testing purposes sample_band_10 = np.zeros((5, 5)) # Sample data for band 10 mask = np.random.randint(0, high=2, size=(5, 5), dtype=int) == 1 # Generating a random mask # Test to ensure the output size matches the input size def test_output_and_input_size_equal(self): # Calling the SplitWindowJiminezMunozLST function with sample data output = SplitWindowJiminezMunozLST()( emissivity_10=self.sample_band_10, emissivity_11=self.sample_band_10, brightness_temperature_10=self.sample_band_10, brightness_temperature_11=self.sample_band_10, mask=self.mask, ) # Asserting that the input and output shapes match self.assertEqual(self.sample_band_10.shape, output.shape) # Test to ensure the maximum temperature is within a certain range def test_max_temp_less_than_or_equal_max_earth_temp(self): # Creating an instance of the SplitWindowJiminezMunozLST class lst_algorithm = SplitWindowJiminezMunozLST() # Asserting that the maximum earth temperature is within a specific range self.assertEqual(lst_algorithm.max_earth_temp, 273.15 + 56.7) class TestSplitWindowKerrLST(unittest.TestCase): # Sample data setup for testing purposes sample_band_10 = np.zeros((5, 5)) mask = np.random.randint(0, high=2, size=(5, 5), dtype=int) == 1 # Test to verify output size matches input size def test_output_and_input_size_equal(self): # Call the method being tested with sample input data output = SplitWindowKerrLST()( brightness_temperature_10=self.sample_band_10, brightness_temperature_11=self.sample_band_10, ndvi=self.sample_band_10, mask=self.mask, ) # Assert that the output size matches the input size self.assertEqual(self.sample_band_10.shape, output.shape) # Test to ensure maximum temperature doesn't exceed maximum Earth temperature def test_max_temp_less_than_or_equal_max_earth_temp(self): # Create an instance of the tested class lst_algorithm = SplitWindowKerrLST() # Assert that the maximum calculated Earth temperature is within limits self.assertEqual(lst_algorithm.max_earth_temp, 273.15 + 56.7) # Test class for SplitWindowMcMillinLST class TestSplitWindowMcMillinLST(unittest.TestCase): # Sample data for testing sample_band_10 = np.zeros((5, 5)) # Creating a sample Band 10 data mask = np.random.randint(0, high=2, size=(5, 5), dtype=int) == 1 # Generating a random mask # Testing whether the output size matches the input size def test_output_and_input_size_equal(self): # Running the SplitWindowMcMillinLST algorithm output = SplitWindowMcMillinLST()( brightness_temperature_10=self.sample_band_10, brightness_temperature_11=self.sample_band_10, mask=self.mask, ) # Checking if the output size matches the input size self.assertEqual(self.sample_band_10.shape, output.shape) # Testing if the maximum calculated temperature is less than or equal to the maximum Earth temperature def test_max_temp_less_than_or_equal_max_earth_temp(self): # Creating an instance of the SplitWindowMcMillinLST algorithm lst_algorithm = SplitWindowMcMillinLST() # Checking if the maximum calculated temperature matches the expected maximum Earth temperature self.assertEqual(lst_algorithm.max_earth_temp, 273.15 + 56.7) # Create a test class inheriting from unittest.TestCase class TestSplitWindowPriceLST(unittest.TestCase): # Sample data for testing sample_band_10 = np.zeros((5, 5)) mask = np.random.randint(0, high=2, size=(5, 5), dtype=int) == 1 # Test case to ensure output and input sizes are equal def test_output_and_input_size_equal(self): # Create an instance of the class or method being tested output = SplitWindowPriceLST()( # Provide sample data to the method emissivity_10=self.sample_band_10, emissivity_11=self.sample_band_10, brightness_temperature_10=self.sample_band_10, brightness_temperature_11=self.sample_band_10, mask=self.mask, ) # Assert that the output shape matches the input shape self.assertEqual(self.sample_band_10.shape, output.shape) # Test case to verify maximum temperature constraints def test_max_temp_less_than_or_equal_max_earth_temp(self): # Create an instance of the class being tested lst_algorithm = SplitWindowPriceLST() # Assert that the maximum earth temperature is as expected self.assertEqual(lst_algorithm.max_earth_temp, 273.15 + 56.7) # Run the tests if this file is executed directly if __name__ == "__main__": unittest.main()