ph_wavelength, photosensitivity = read_pindiode_photo_sensitivity()
ph_wavelength_smooth = np.linspace(ph_wavelength.min(), ph_wavelength.max(), 1000)
photosensitivity_smooth = spline(ph_wavelength, photosensitivity, ph_wavelength_smooth)
pin_diode_wavelength = ph_wavelength_smooth[68]
pin_diode_pde = photosensitivity_smooth[68]
plt.plot(ph_wavelength_smooth, photosensitivity_smooth)
plt.xlabel("wavelength [nm]")
plt.ylabel("Photosensitivity [A/W]")
x, y, current, current_std, current_time, current_timestamp = read_file(path_to_file=file_flash, scan_type='time')
systematic_err = comp.calculate_systematic_error(current)
statistic_err = comp.calculate_statistic_error(current_std)
total_err = np.sqrt(systematic_err**2 + statistic_err**2)
factor = pin_diode_pde * illuminated_area
scaling = 1e-6 # to go to micro Watts
irradiance = (current / factor) / scaling
irradiance_err = (total_err[0] / factor) / scaling
initial_bin = 80
final_bin = 350
p, cov = np.polyfit(current_time[initial_bin:final_bin], irradiance[initial_bin:final_bin], deg=1, cov=True)
error_bars = np.sqrt(np.diag(cov))
x_fit = np.linspace(current_time.min(), current_time.max(), 1000)
measured_distance = 5.6
detector_size = [30, 30]
#xx = np.array([-450., 450.])
#yy = np.array([-600., 600.])
xx = np.array([-437, 463])
yy = np.array([-681.7, 518.3])
#x_ticks = [150, 180, 210]
#y_ticks = [30, 60, 90]
extent = [-detector_size[0]/2 + xx.min(), detector_size[0]/2 + xx.max(), -detector_size[1]/2 + yy.min(), detector_size[1]/2 + yy.max()]
steps = 11
for cnt in range(0, 12):
x, y, flash_current, flash_current_std, flash_current_time, flash_current_timestamp = read_file(flash[cnt], 'space', initial_temperature_time=None)
flash_stat_err = calculate_statistic_error(flash_current_std)
flash_sys_err = calculate_systematic_error(flash_current)
flash_current_err = np.sqrt(flash_stat_err ** 2 + flash_sys_err ** 2)
x, y, dark_current, dark_current_std, dark_current_time, dark_current_timestamp = read_file(dark[cnt], 'space', initial_temperature_time=None)
dark_stat_err = calculate_statistic_error(dark_current_std)
dark_sys_err = calculate_systematic_error(dark_current)
dark_current_err = np.sqrt(dark_stat_err ** 2 + dark_sys_err ** 2)
result = flash_current - dark_current
result_err = np.sqrt(flash_current_err ** 2 + dark_current_err ** 2)
flash_current = flash_current.reshape((steps, steps)).T
flash_current_err = flash_current_err.reshape((steps, steps)).T
dark_current = dark_current.reshape((steps, steps)).T