def test_peak_area():
df = pd.read_csv(get_path('test_data.csv'), header=[0, 1])
df = df[df[('meta', 'LIBS ID')] == 'LIB00041']
expected_peaks = np.array([
586.723, 588.746, 589.42, 590.767, 591.216, 592.114, 592.787, 593.46,
593.909, 594.357
])
expected_mins = np.array([
585.374, 587.173, 589.195, 590.543, 590.992, 591.89, 592.338, 593.236,
593.685, 594.133, 594.582
])
expected_areas = np.array([
7248.48, 43986.54, 25421.36, 1843.12, 3593.24, 1661.12, 3316.24,
1679.12, 1690.12, 1739.12
])
pa_df = pd.DataFrame(expected_areas).T
pa_df.columns = pd.MultiIndex.from_tuples([('peak_area', i)
for i in expected_peaks])
df_result, peaks_result, mins_result = pa.peak_area(df,
peaks_mins_file=None)
np.testing.assert_array_almost_equal(np.array(peaks_result, dtype=float),
expected_peaks)
np.testing.assert_array_almost_equal(np.array(mins_result, dtype=float),
expected_mins)
np.testing.assert_array_almost_equal(
np.squeeze(np.array(df_result['peak_area'])), expected_areas)
def test_peak_area_from_file():
df = pd.read_csv(get_path('test_data.csv'), header=[0, 1])
df = df[df[('meta', 'LIBS ID')] == 'LIB00041']
peaks_mins_file = get_path('peaks_mins.csv')
df_result, peaks_result, mins_result = pa.peak_area(
df, peaks_mins_file=peaks_mins_file)
expected_peaks = [588.072, 592.338]
expected_mins = [586.273, 589.195, 594.133]
expected_areas = [47938.78, 39204.32]
np.testing.assert_array_almost_equal(expected_peaks, peaks_result)
np.testing.assert_array_almost_equal(expected_mins, mins_result)
np.testing.assert_array_almost_equal(
expected_areas,
np.array(df_result['peak_area'])[0, :])
def peak_area(self, peaks_mins_file):
self.df, self.peaks, self.mins = peak_area.peak_area(
self.df, peaks_mins_file=peaks_mins_file)