def br_caller(df, method, params, expected, expected_baseline):
df = norm(df, [[580, 600]])
result, result_baseline = remove_baseline(df, method, params=params)
np.testing.assert_array_almost_equal(expected,
np.array(result['wvl'].iloc[5, 0:5]))
np.testing.assert_array_almost_equal(
expected_baseline, np.array(result_baseline['wvl'].iloc[5, 0:5]))
def run(self):
method = self.chooseAlgorithmComboBox.currentText()
datakey = self.chooseDataComboBox.currentText()
# return method parameters and parameters that changed
methodParameters, _changed = self.getMethodParams(self.chooseAlgorithmComboBox.currentIndex())
datakey_new = datakey + '-Baseline Removed-' + method + str(_changed)
datakey_baseline = datakey + '-Baseline-' + method + str(_changed)
self.datakeys.append(datakey_new)
self.datakeys.append(datakey_baseline)
self.data[datakey_new] = self.data[datakey].df.copy(deep=True)
df, df_baseline = remove_baseline(self.data[datakey_new],method, segment=True, params=methodParameters)
self.data[datakey_new] = spectral_data(df)
self.data[datakey_baseline] = spectral_data(df_baseline)
def test_KK():
#test case where bottom width is too small
df = pd.read_csv(get_path('test_data.csv'), header=[0, 1])
methodParameters = {
'top_width': 10,
'bottom_width': 0,
'exponent': 2,
'tangent': False
}
result, result_baseline = remove_baseline(df,
'KK',
params=methodParameters)
assert np.isnan(result['wvl'].iloc[0, 0])
#test case using top and bottom widths and tangent
df = pd.read_csv(get_path('test_data.csv'), header=[0, 1])
methodParameters = {
'top_width': 10,
'bottom_width': 50,
'exponent': 2,
'tangent': True
}
expected = [-0.119923, -0.117072, -0.114455, -0.120391, -0.122455]
expected_baseline = [0.130102, 0.130128, 0.130152, 0.130174, 0.130194]
br_caller(df, 'KK', methodParameters, expected, expected_baseline)
#test using just bottom width
df = pd.read_csv(get_path('test_data.csv'), header=[0, 1])
methodParameters = {
'top_width': 0,
'bottom_width': 50,
'exponent': 2,
'tangent': False
}
expected = [0.002431, 0.005307, 0.007949, 0.002039, 0.]
expected_baseline = [0.007748, 0.007749, 0.007748, 0.007745, 0.00774]
br_caller(df, 'KK', methodParameters, expected, expected_baseline)
# test ranges
expected_ranges = {
'top_width': (0, 100, 'integer'),
'bottom_width': (0, 100, 'integer')
}
br_obj = kajfosz_kwiatek.KajfoszKwiatek()
assert br_obj.param_ranges() == expected_ranges
def remove_baseline(self, method, segment, params):
self.df = remove_baseline.remove_baseline(self.df,
method=method,
segment=segment,
params=params)
def test_not_recognized():
df = pd.read_csv(get_path('test_data.csv'), header=[0, 1])
result = remove_baseline(df, 'foo', params=None)
assert result == 0
