def test_pixel_intensity():
'''Test for function which determines sample temperature and plate temperature'''
pixel_frames = edge_detection.input_file(
'../musical-robot/musicalrobot/data/CHCl_CA_DES_5_31_19.tiff')
n_frames = len(pixel_frames)
img_eq = pixel_analysis.image_eq(n_frames, pixel_frames)
column_sum, row_sum = pixel_analysis.pixel_sum(img_eq)
n_columns = 12
n_rows = 8
sample_location = pixel_analysis.peak_values(column_sum, row_sum,
n_columns, n_rows, img_eq)
x_name = 'Row'
y_name = 'Column'
plate_name = 'plate_location'
pixel_sample, pixel_plate = pixel_analysis.pixel_intensity(
sample_location, pixel_frames, x_name, y_name, plate_name)
assert isinstance(pixel_sample, list), 'Output is not a list'
assert isinstance(pixel_plate, list), 'Output is not a list'
assert len(
pixel_sample
) == n_columns * n_rows, 'Temperature obtained for wrong number of samples'
assert len(
pixel_plate
) == n_columns * n_rows, 'Temperature obtained for wrong number of plate locations'
return
def test_locations():
'''Test for functin which returns a dataframe containing row and column
locations of samples and their respective plate location at which temperature
profiles are monitored'''
frames = edge_detection.input_file(
'../musical-robot/musicalrobot/data/10_17_19_PPA_Shallow_plate.tiff')
crop_frame = []
for frame in frames:
crop_frame.append(frame[35:85, 40:120])
pixel_frames = edge_detection.flip_frame(crop_frame)
img_eq = pixel_analysis.image_eq(pixel_frames)
column_sum, row_sum = pixel_analysis.pixel_sum(img_eq)
n_columns = 3
n_rows = 3
r_peaks, c_peaks = pixel_analysis.peak_values(column_sum,
row_sum,
n_columns,
n_rows,
freeze_heat=False)
sample_location = pixel_analysis.locations(r_peaks, c_peaks, img_eq)
assert isinstance(sample_location,
pd.DataFrame), 'Output is not a dataframe'
assert len(
sample_location
) == n_columns * n_rows, 'Wrong number of sample locations are present'
return
def test_pixel_intensity():
'''Test for function which determines sample temperature and plate temperature'''
frames = edge_detection.input_file(
'../musical-robot/musicalrobot/data/10_17_19_PPA_Shallow_plate.tiff')
crop_frame = []
for frame in frames:
crop_frame.append(frame[35:85, 40:120])
pixel_frames = edge_detection.flip_frame(crop_frame)
img_eq = pixel_analysis.image_eq(pixel_frames)
column_sum, row_sum = pixel_analysis.pixel_sum(img_eq)
n_columns = 3
n_rows = 3
r_peaks, c_peaks = pixel_analysis.peak_values(column_sum,
row_sum,
n_columns,
n_rows,
freeze_heat=False)
sample_location = pixel_analysis.locations(r_peaks, c_peaks, img_eq)
x_name = 'Row'
y_name = 'Column'
plate_name = 'plate_location'
pixel_sample, pixel_plate = pixel_analysis.pixel_intensity(
sample_location, pixel_frames, x_name, y_name, plate_name)
assert isinstance(pixel_sample, list), 'Output is not a list'
assert isinstance(pixel_plate, list), 'Output is not a list'
assert len(
pixel_sample
) == n_columns * n_rows, 'Temperature obtained for wrong number of samples'
assert len(
pixel_plate
) == n_columns * n_rows, 'Temperature obtained for wrong number of plate locations'
return
def test_peak_values():
'''Test for function which finds peaks from the column_sum and row_sum arrays
and return a dataframe with sample locations and plate locations.'''
pixel_frames = edge_detection.input_file(
'../musical-robot/musicalrobot/data/CHCl_CA_DES_5_31_19.tiff')
n_frames = len(pixel_frames)
img_eq = pixel_analysis.image_eq(n_frames, pixel_frames)
column_sum, row_sum = pixel_analysis.pixel_sum(img_eq)
n_columns = 12
n_rows = 8
sample_location = pixel_analysis.peak_values(column_sum, row_sum,
n_columns, n_rows, img_eq)
assert isinstance(sample_location,
pd.DataFrame), 'Output is not a dataframe'
assert len(
sample_location
) == n_columns * n_rows, 'Wrong number of sample locations are present'
return
def test_peak_values():
'''Test for function which finds peaks from the column_sum and row_sum arrays
and return a dataframe with sample locations and plate locations.'''
frames = edge_detection.input_file('../musical-robot/musicalrobot/data/10_17_19_PPA_Shallow_plate.tiff')
crop_frame = []
for frame in frames:
crop_frame.append(frame[35:85,40:120])
pixel_frames = edge_detection.flip_frame(crop_frame)
n_frames = len(pixel_frames)
img_eq = pixel_analysis.image_eq(n_frames,pixel_frames)
column_sum, row_sum = pixel_analysis.pixel_sum(img_eq)
n_columns = 3
n_rows = 3
r_peaks, c_peaks = pixel_analysis.peak_values(column_sum,row_sum,n_columns,n_rows,img_eq)
assert isinstance(r_peaks, list), 'Output is not a list'
assert isinstance(c_peaks, list), 'Output is not a list'
assert len(r_peaks) == n_rows, 'Wrong number of sample rows detected'
assert len(c_peaks) == n_columns, 'Wrong number of sample columns detected'
return