def deserialize_result(serialized):
return deserialize_exp_result(serialized)
def deserialize_result(serialized):
return deserialize_exp_result(serialized)
ip.calibrate({0: 0, 1: 0, 2: 0, 3: 0, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8})
ip.categoryMap = {4: 'fred', 5: 'fred', 6: 'fred', 8: 'henry', 9: 'henry'}
result = ip.measure()
print('calibration data: ', result.calibration_data)
print('concentrations: ', result.concentrations)
print('categorized: ', result.categorized)
print('negative controls', result.negative_controls_indices)
print('background intensity: ', result.background_intensity)
print('background concentration: ',
result.intensity_to_concentration(result.background_intensity))
print('LoD', result.limit_of_detection)
print('LoQ', result.limit_of_quantification)
print(
'fitted curve',
result._intensity_to_concentration(1) -
result._intensity_to_concentration(0),
result._intensity_to_concentration(0))
ser = result.serialize
result = deserialize_exp_result(ser)
print(result.asCSV)
fig = plot.plot_overview(result, encoding=None)
print(fig)
#plot.plot_standard_curve(result, encoding=None, show=True)
#plot.plot_signal_to_noise(result, encoding=None, show=True)
# calibration with dict
ip.calibrate({0: 0, 1: 0, 2: 0, 3: 0, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8})
ip.categoryMap = {4: "fred", 5: "fred", 6: "fred", 8: "henry", 9: "henry"}
result = ip.measure()
print("calibration data: ", result.calibration_data)
print("concentrations: ", result.concentrations)
print("categorized: ", result.categorized)
print("negative controls", result.negative_controls_indices)
print("background intensity: ", result.background_intensity)
print("background concentration: ", result.intensity_to_concentration(result.background_intensity))
print("LoD", result.limit_of_detection)
print("LoQ", result.limit_of_quantification)
print(
"fitted curve",
result._intensity_to_concentration(1) - result._intensity_to_concentration(0),
result._intensity_to_concentration(0),
)
ser = result.serialize
result = deserialize_exp_result(ser)
print(result.asCSV)
fig = plot.plot_overview(result, encoding=None)
print(fig)
# plot.plot_standard_curve(result, encoding=None, show=True)
# plot.plot_signal_to_noise(result, encoding=None, show=True)
