# # # This source code is subject to the license referenced at
# # # https://github.com/NRLMMD-GEOIPS.
"""Data manipulation steps for "Night_Microphy" EUMETSAT RGB product.
This algorithm expects three Infrared/Visible channels for an RGB image:
* Red SEVIRI B10BT - B09BT
* Green SEVIRI B09Bt - B04BT
* Blue SEVIRI B09BT
"""
import logging
LOG = logging.getLogger(__name__)
interface = "algorithms"
family = "xarray_to_numpy"
name = "Night_Microphys"
[docs]def call(xobj):
"""Night_Microphys product algorithm data manipulation steps.
This algorithm expects TBs from three SEVIRI channels:
* Red: B10BT - B09BT
* Green: B09Bt - B04BT
* Blue: B09BT
Parameters
----------
arrays : list of numpy.ndarray
* list of numpy.ndarray or numpy.MaskedArray of channel data,
in order of sensor "channels" list
* Unit in Degrees Kelvin and reflectance
Returns
-------
numpy.ndarray
numpy.ndarray or numpy.MaskedArray of qualitative RGBA image output
"""
bt04 = xobj["B04BT"].to_masked_array() # 3.9 um TBs, B04 SEVIRI
bt09 = xobj["B09BT"].to_masked_array() # 10.8 um reflectance, B09 SEVIRI
bt10 = xobj["B10BT"].to_masked_array() # 12.0 um reflectance, B10 SEVIRI
# Convert TB from Kevin to Celsius
from geoips.data_manipulations.conversions import unit_conversion
bt04 = unit_conversion(bt04, input_units="Kelvin", output_units="celsius")
bt09 = unit_conversion(bt09, input_units="Kelvin", output_units="celsius")
bt10 = unit_conversion(bt10, input_units="Kelvin", output_units="celsius")
from geoips.data_manipulations.corrections import apply_data_range, apply_gamma
data_range = [-4, 2]
red = apply_data_range(
bt10 - bt09,
min_val=data_range[0],
max_val=data_range[1],
min_outbounds="crop",
max_outbounds="crop",
norm=True,
inverse=False,
) # need inverse option?
red = apply_gamma(red, 1.0)
red = apply_gamma(red, 1.0)
# Note: may need additional solar correction
data_range = [0, 10]
grn = apply_data_range(
bt09 - bt04,
min_val=data_range[0],
max_val=data_range[1],
min_outbounds="crop",
max_outbounds="crop",
norm=True,
inverse=False,
)
grn = apply_gamma(grn, 1.0)
grn = apply_gamma(grn, 1.0)
# Note: may need additional solar correction
data_range = [-30, 20]
blu = apply_data_range(
bt09,
min_val=data_range[0],
max_val=data_range[1],
min_outbounds="crop",
max_outbounds="crop",
norm=True,
inverse=False,
) # create image of deep clouds in blueish color
# norm=True, inverse=False) #create image of deep clouds in yellowish color
blu = apply_gamma(blu, 1.0)
blu = apply_gamma(blu, 1.0)
from geoips.image_utils.mpl_utils import alpha_from_masked_arrays, rgba_from_arrays
alp = alpha_from_masked_arrays([red, grn, blu])
rgba = rgba_from_arrays(red, grn, blu, alp)
return rgba
