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Merge branch 'pre-master' of github.com:pytroll/mpop into pre-master
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@loerum
loerum committed Jun 24, 2016
2 parents 3fde12a + f269e48 commit 36c3e4e
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Showing 3 changed files with 73 additions and 64 deletions.
64 changes: 34 additions & 30 deletions mpop/imageo/formats/ninjotiff.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -178,7 +178,6 @@ def _eval(val):
return str(val)

filename = self._find_a_config_file()
#print "Reading Ninjo config file: '%s'" % filename
log.info("Reading Ninjo config file: '%s'" % filename)

cfg = ConfigParser()
Expand Down Expand Up @@ -263,21 +262,19 @@ def _get_satellite_altitude(filename):
return None


def _finalize(geo_image, dtype=np.uint8, value_range=None, value_range_measurement_unit=None):
def _finalize(geo_image, dtype=np.uint8, value_range_measurement_unit=None, data_is_scaled_01=True):
"""Finalize a mpop GeoImage for Ninjo. Specialy take care of phycical scale
and offset.
:Parameters:
geo_image : mpop.imageo.geo_image.GeoImage
See MPOP's documentation.
dtype : bits per sample np.unit8 or np.unit16 (default: np.unit8)
value_range: list or tuple
value_range_measurement_unit: list or tuple
Defining minimum and maximum value range. Data will be clipped into
that range. Default is no clipping and auto scale.
Input data assumes to be in physical value range.
value_range_measurement_unit: list or tuple
Defining minimum and maximum value range.
Input data assumes to be in the [0.0, 1.0] range.
data_is_scaled_01: boolean
If true (default), input data is assumed to be in the [0.0, 1.0] range.
:Returns:
image : numpy.array
Expand Down Expand Up @@ -305,7 +302,7 @@ def _finalize(geo_image, dtype=np.uint8, value_range=None, value_range_measureme
scale = 1
offset = 0
else:
if value_range_measurement_unit:
if value_range_measurement_unit and data_is_scaled_01:
# No additional scaling of the input data - assume that data is within [0.0, 1.0]
# and interpretate 0.0 as value_range_measurement_unit[0]
# and 1.0 as value_range_measurement_unit[1]
Expand All @@ -330,12 +327,12 @@ def _finalize(geo_image, dtype=np.uint8, value_range=None, value_range_measureme
scale /= scale_fill_value

else:
if value_range:
data.clip(value_range[0], value_range[1], data)
chn_min = value_range[0]
chn_max = value_range[1]
if value_range_measurement_unit:
data.clip(value_range_measurement_unit[0], value_range_measurement_unit[1], data)
chn_min = value_range_measurement_unit[0]
chn_max = value_range_measurement_unit[1]
log.debug("Scaling, using value range %.2f - %.2f" %
(value_range[0], value_range[1]))
(value_range_measurement_unit[0], value_range_measurement_unit[1]))
else:
chn_max = data.max()
chn_min = data.min()
Expand Down Expand Up @@ -387,6 +384,15 @@ def _finalize(geo_image, dtype=np.uint8, value_range=None, value_range_measureme
channels[3].filled(fill_value[3])))
return data, 1.0, 0.0, fill_value[0]

elif geo_image.mode == 'P':
fill_value = 0
data = geo_image.channels[0]
if isinstance(data, np.ma.core.MaskedArray):
data = data.filled(fill_value)
data = data.astype(dtype)
log.debug("Value range: %.2f, %.2f, %.2f" % (data.min(), data.mean(), data.max()))
return data, 1.0, 0.0, fill_value

else:
raise ValueError("Don't known how til handle image mode '%s'" %
str(geo_image.mode))
Expand All @@ -411,38 +417,36 @@ def save(geo_image, filename, ninjo_product_name=None, **kwargs):
* 8 bits grayscale with a colormap (if specified, inverted for IR channels).
* 16 bits grayscale with no colormap (if specified, MinIsWhite is set for IR).
* min value will be reserved for transparent color.
* RGB images will use mpop.imageo.image's standard finalize.
* If possible mpop.imageo.image's standard finalize will be used.
"""

dtype = np.uint8 # @UndefinedVariable
dtype = np.uint8
if 'nbits' in kwargs:
nbits = int(kwargs['nbits'])
if nbits == 16:
dtype = np.uint16 # @UndefinedVariable

try:
# TODO: don't force min and max to integers.
value_range = int(kwargs["ch_min"]), int(kwargs["ch_max"])
except KeyError:
value_range = None
dtype = np.uint16

try:
value_range_measurement_unit = (float(kwargs["ch_min_measurement_unit"]),
float(kwargs["ch_max_measurement_unit"]))
except KeyError:
value_range_measurement_unit = None

data, scale, offset, fill_value = _finalize(geo_image, dtype=dtype, value_range=value_range,
value_range_measurement_unit=value_range_measurement_unit)
data_is_scaled_01 = bool(kwargs.get("data_is_scaled_01", True))

data, scale, offset, fill_value = _finalize(geo_image, dtype=dtype, data_is_scaled_01=data_is_scaled_01,
value_range_measurement_unit=value_range_measurement_unit,)

area_def = geo_image.area
time_slot = geo_image.time_slot

# Some Ninjo tiff names
kwargs['image_dt'] = time_slot
kwargs['transparent_pix'] = fill_value
kwargs['gradient'] = scale
kwargs['axis_intercept'] = offset
kwargs['transparent_pix'] = fill_value
kwargs['image_dt'] = time_slot
kwargs['is_calibrated'] = True

write(data, filename, area_def, ninjo_product_name, **kwargs)


Expand All @@ -469,20 +473,20 @@ def write(image_data, output_fn, area_def, product_name=None, **kwargs):
See _write
"""
upper_left = area_def.get_lonlat(0, 0)
lower_right = area_def.get_lonlat(area_def.shape[0]-1, area_def.shape[1]-1)
lower_right = area_def.get_lonlat(area_def.shape[0] - 1, area_def.shape[1] - 1)

if len(image_data.shape) == 3:
if image_data.shape[2] == 4:
shape = (area_def.y_size, area_def.x_size, 4)
log.info("Will generate RGBA product '%s'" % product_name)
log.info("Will generate RGBA product")
else:
shape = (area_def.y_size, area_def.x_size, 3)
log.info("Will generate RGB product '%s'" % product_name)
log.info("Will generate RGB product")
write_rgb = True
else:
shape = (area_def.y_size, area_def.x_size)
write_rgb = False
log.info("Will generate product '%s'" % product_name)
log.info("Will generate single band product")

if image_data.shape != shape:
raise ValueError("Raster shape %s does not correspond to expected shape %s" % (
Expand Down
25 changes: 15 additions & 10 deletions mpop/imageo/formats/ninjotiff_example
View file
Original file line number Diff line number Diff line change
Expand Up @@ -33,12 +33,15 @@ Saving an image for 'chn' will then go like:
image.save(filename,
fformat='mpop.imageo.formats.ninjotiff',
physic_unit=physic_unit,
value_range=value_range,
ch_min_measurement_unit=min_value,
ch_max_measurement_unit=max_value,
**ninjotiff_config[chn])
"""
import sys
import os
from datetime import datetime, timedelta
import logging
logging.basicConfig(level=logging.DEBUG)

# Basic check.
try:
Expand Down Expand Up @@ -78,7 +81,6 @@ CHANNEL_DICT = {
}

BITS_PER_SAMPLE = 8

DO_CONVECTION = False

for area_name, area_in, area_out in AREAS:
Expand Down Expand Up @@ -106,17 +108,20 @@ for area_name, area_in, area_out in AREAS:
physic_unit = scene[chn].unit = 'C'

# Value range as DWD
value_range = None
if physic_unit in ('C', 'CELSIUS'):
# IR
value_range = [-88.5, 40]
value_range = (-88.5, 40.)
else:
# VIS
value_range = [0., 125.]
value_range = (0., 125.)


# GeoImage without any data scaling or enhancement.
img = scene.image(chn, mode="L")
#
# A GeoImage specifying a color range.
#
# If no color_range specified, MPOP will not scaled the data into the [0., 1.] range.
# In that case set the data_is_scaled_01 option to False in img.save
#
img = scene.image(chn, mode="L", crange=[value_range])
LOG.info("%s (%s, %s) %.2f %.2f %.2f" % (chn_name, physic_unit,
img.channels[0].dtype,
img.channels[0].min(),
Expand All @@ -136,8 +141,8 @@ for area_name, area_in, area_out in AREAS:
fformat='mpop.imageo.formats.ninjotiff',
physic_unit=physic_unit,
ninjo_product_name=chn_name,
ch_min=value_range[0],
ch_max=value_range[1],
ch_min_measurement_unit=value_range[0],
ch_max_measurement_unit=value_range[1],
nbits=BITS_PER_SAMPLE)

# Cleanup.
Expand Down
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