# Intialize the camera, here we can specify different image size
# or any other parameter that Camera allows
c = Camera(bit_depth=10, width=100, height=50)
# Fill the information
data['width'] = c.width
data['height'] = c.height
# Maximum exposure for test
exposure_max = 9000000
# Find the camera parameters for the test
c.exposure = exposure_max
c.blackoffset = get_emva_blackoffset(c)
c.K = get_emva_gain(c)
# Find the radiance that will saturate the camera at our maximum exposure time
saturation_radiance = c.get_radiance_for()
# Initialize the exposure for the spatial measure
exposure_spatial = None
# Loop through the exposures
for exposure in np.linspace(c.exposure_min, exposure_max, 100):
c.exposure = exposure
data['temporal'][exposure] = {}
# For each exposure, take to measurements (bright, dark)
for radiance in (saturation_radiance, 0.0):
photons = c.get_photons(radiance)
# or any other parameter that Camera allows
c = Camera(bit_depth=10,
img_x=100,
img_y=50)
# Fill the information
data['width'] = c.img_x
data['height'] = c.img_y
# Maximum exposure for test
exposure_max = 9000000
# Find the camera parameters for the test
c.exposure = exposure_max
c.blackoffset = get_emva_blackoffset(c)
c.K = get_emva_gain(c)
# Find the radiance that will saturate the camera at our maximum exposure time
saturation_radiance = c.get_radiance_for()
# Initialize the exposure for the spatial measure
exposure_spatial = None
# Loop through the exposures
for exposure in np.linspace(c.exposure_min, exposure_max, 100):
c.exposure = exposure
data['temporal'][exposure] = {}
# For each exposure, take to measurements (bright, dark)
for radiance in (saturation_radiance, 0.0):
photons = c.get_photons(radiance)
