def main(iargs=None):
inps = cmd_line_parse(iargs)
plt.switch_backend('Agg') # Backend setting
# Read data
k = readfile.read_attribute(inps.file)['FILE_TYPE']
if k == 'timeseries' and inps.dset and '_' in inps.dset:
inps.ref_date, inps.dset = inps.dset.split('_')
else:
inps.ref_date = None
data, atr = readfile.read(inps.file, datasetName=inps.dset)
if k == 'timeseries' and inps.ref_date:
data -= readfile.read(inps.file, datasetName=inps.ref_date)[0]
# mask
mask = pp.read_mask(inps.file,
mask_file=inps.mask_file,
datasetName=inps.dset,
print_msg=True)[0]
if mask is not None:
data = np.ma.masked_where(mask == 0., data)
if inps.zero_mask:
print('masking pixels with zero value')
data = np.ma.masked_where(data == 0., data)
# Data Operation - Display Unit & Rewrapping
(data, inps.disp_unit, inps.disp_scale,
inps.wrap) = pp.scale_data4disp_unit_and_rewrap(
data,
metadata=atr,
disp_unit=inps.disp_unit,
wrap=inps.wrap,
wrap_range=inps.wrap_range)
if inps.wrap:
inps.vlim = inps.wrap_range
# Output filename
inps.fig_title = pp.auto_figure_title(inps.file,
datasetNames=inps.dset,
inps_dict=vars(inps))
if not inps.outfile:
inps.outfile = '{}.kmz'.format(inps.fig_title)
inps.outfile = os.path.abspath(inps.outfile)
# 2. Generate Google Earth KMZ
write_kmz_file(data, metadata=atr, out_file=inps.outfile, inps=inps)
return inps.outfile
def main(iargs=None):
inps = cmd_line_parse(iargs)
plt.switch_backend('Agg') # Backend setting
# Read data
data, atr = readfile.read(inps.file, datasetName=inps.dset)
# mask
mask = pp.read_mask(inps.file, mask_file=inps.mask_file, datasetName=inps.dset, print_msg=True)[0]
if mask is not None:
data = np.ma.masked_where(mask == 0., data)
# Data Operation - Display Unit & Rewrapping
(data,
inps.disp_unit,
inps.disp_scale,
inps.wrap) = pp.scale_data4disp_unit_and_rewrap(data,
metadata=atr,
disp_unit=inps.disp_unit,
wrap=inps.wrap,
wrap_range=inps.wrap_range)
if inps.wrap:
inps.vlim = inps.wrap_range
# Output filename
inps.fig_title = pp.auto_figure_title(inps.file,
datasetNames=inps.dset,
inps_dict=vars(inps))
if not inps.outfile:
inps.outfile = '{}.kmz'.format(inps.fig_title)
inps.outfile = os.path.abspath(inps.outfile)
# 2. Generate Google Earth KMZ
write_kmz_file(data,
metadata=atr,
out_file=inps.outfile,
inps=inps)
return inps.outfile
def update_data_with_plot_inps(data, metadata, inps):
# Seed Point
if inps.ref_yx: # and inps.ref_yx != [int(metadata['REF_Y']), int(metadata['REF_X'])]:
try:
ref_y = inps.ref_yx[0] - inps.pix_box[1]
ref_x = inps.ref_yx[1] - inps.pix_box[0]
except:
pass
if len(data.shape) == 2:
data -= data[ref_y, ref_x]
elif len(data.shape) == 3:
data -= np.tile(data[:, ref_y, ref_x].reshape(-1, 1, 1),
(1, data.shape[1], data.shape[2]))
vprint('set reference pixel to: {}'.format(inps.ref_yx))
else:
inps.ref_yx = None
# Convert data to display unit and wrap
(data, inps.disp_unit, inps.disp_scale,
inps.wrap) = pp.scale_data4disp_unit_and_rewrap(
data,
metadata=metadata,
disp_unit=inps.disp_unit,
wrap=inps.wrap,
wrap_range=inps.wrap_range,
print_msg=inps.print_msg)
if inps.wrap:
inps.vlim = inps.wrap_range
# 1.6 Min / Max - Data/Display
inps.dlim = [np.nanmin(data), np.nanmax(data)]
if not inps.vlim: # and data.ndim < 3:
inps.vlim = [np.nanmin(data), np.nanmax(data)]
vprint('data range: {} {}'.format(inps.dlim, inps.disp_unit))
vprint('display range: {} {}'.format(inps.vlim, inps.disp_unit))
return data, inps
def main(iargs=None):
inps = cmd_line_parse(iargs)
# 1. Read metadata and data
k = readfile.read_attribute(inps.file)['FILE_TYPE']
if k == 'timeseries' and inps.dset and '_' in inps.dset:
inps.ref_date, inps.dset = inps.dset.split('_')
else:
inps.ref_date = None
atr = readfile.read_attribute(inps.file, datasetName=inps.dset)
# pix_box
inps.pix_box = subset.subset_input_dict2box(vars(inps), atr)[0]
inps.pix_box = ut.coordinate(atr).check_box_within_data_coverage(
inps.pix_box)
data_box = (0, 0, int(atr['WIDTH']), int(atr['LENGTH']))
print('data coverage in y/x: {}'.format(data_box))
print('subset coverage in y/x: {}'.format(inps.pix_box))
atr = attr.update_attribute4subset(atr, inps.pix_box)
# read data
data = readfile.read(inps.file, datasetName=inps.dset, box=inps.pix_box)[0]
if k == 'timeseries' and inps.ref_date:
data -= readfile.read(inps.file,
datasetName=inps.ref_date,
box=inps.pix_box)[0]
# mask
mask = pp.read_mask(inps.file,
mask_file=inps.mask_file,
datasetName=inps.dset,
box=inps.pix_box)[0]
if mask is not None:
print('masking out pixels with zero value in file: {}'.format(
inps.mask_file))
data[mask == 0] = np.nan
if inps.zero_mask:
print('masking out pixels with zero value')
data[data == 0] = np.nan
del mask
# Data Operation - Display Unit & Rewrapping
(data, inps.disp_unit, inps.disp_scale,
inps.wrap) = pp.scale_data4disp_unit_and_rewrap(
data,
metadata=atr,
disp_unit=inps.disp_unit,
wrap=inps.wrap,
wrap_range=inps.wrap_range)
if inps.wrap:
inps.vlim = inps.wrap_range
# 2. Generate Google Earth KMZ
# 2.1 Common settings
# disp min/max and colormap
cmap_lut = 256
if not inps.vlim:
cmap_lut, inps.vlim = pp.auto_adjust_colormap_lut_and_disp_limit(data)
inps.colormap = pp.auto_colormap_name(atr, inps.colormap)
inps.colormap = pp.ColormapExt(inps.colormap, cmap_lut).colormap
inps.norm = colors.Normalize(vmin=inps.vlim[0], vmax=inps.vlim[1])
# Output filename
inps.fig_title = pp.auto_figure_title(inps.file,
datasetNames=inps.dset,
inps_dict=vars(inps))
if not inps.outfile:
inps.outfile = '{}.kmz'.format(inps.fig_title)
inps.outfile = os.path.abspath(inps.outfile)
# 2.2 Write KMZ file
if 'Y_FIRST' in atr.keys():
# create ground overlay KML for file in geo-coord
write_kmz_overlay(
data,
meta=atr,
out_file=inps.outfile,
inps=inps,
)
else:
# create placemark KML for file in radar-coord
write_kmz_placemark(
data,
meta=atr,
out_file=inps.outfile,
geom_file=inps.geom_file,
inps=inps,
)
return inps.outfile