smos package

Subpackages

• smos.smos_ic package
  • Submodules
  • smos.smos_ic.download module
  • smos.smos_ic.interface_ic module
    • SMOS_IC_Ds
      • SMOS_IC_Ds.default_fname_template
    • SMOS_IC_Img
  • smos.smos_ic.reshuffle_ic module
    • main()
    • reshuffle()
    • run()
  • Module contents
• smos.smos_l2 namespace
  • Submodules
  • smos.smos_l2.cli module
  • smos.smos_l2.download module
    • SmosDissEoFtp
      • SmosDissEoFtp.exec()
      • SmosDissEoFtp.last_available_day()
      • SmosDissEoFtp.list()
      • SmosDissEoFtp.list_all_available_days()
      • SmosDissEoFtp.sync()
      • SmosDissEoFtp.sync_period()
      • SmosDissEoFtp.verify_lftp_installed()
    • load_dotrc()
  • smos.smos_l2.reshuffle module
    • extend_ts()
    • swath2ts()
• smos.smos_l3 namespace
  • Submodules
  • smos.smos_l3.download module
• smos.smos_l4 package
  • Submodules
  • smos.smos_l4.interface_l4 module
    • SMOS_L4_Ds
      • SMOS_L4_Ds.default_fname_template
    • SMOS_L4_Img
  • smos.smos_l4.reshuffle_l4 module
    • main()
    • reshuffle()
    • run()
  • Module contents

Submodules

smos.grid module

class smos.grid.EASE25CellGrid(bbox=None, only_land=False)

Bases: CellGrid

CellGrid version of EASE25 Grid as used in SMOS IC

cut() → CellGrid

smos.interface module

class smos.interface.SMOSDs(data_path, ioclass, parameters=None, flatten=False, grid=<smos.grid.EASE25CellGrid object>, filename_templ=None, read_flags=(0, 1), float_fillval=nan, additional_kws=None)

Bases: MultiTemporalImageBase

Class for reading SMOS images in nc format. Images are orgnaised in subdirs for each year.

Parameters:

• data_path (str) – Path to the nc files

• parameter (str or list, optional (default: None)) – one or list of parameters to read, see SMOS documentation for more information (default: ‘Soil_Moisture’).

• flatten (bool, optional (default: False)) – If set then the data is read into 1D arrays. This is used to e.g reshuffle the data.

• grid (pygeogrids.CellGrid, optional (default: EASE25CellGrid)) – Grid that the image data is organised on, by default the global EASE25 grid is used.

• read_flags (tuple or None, optional (default: (0, 1))) – Filter values to read based on the selected QUALITY_FLAGS. Values for locations that are not assigned any of the here passed flags are replaces with NaN (by default only the missing-data, i.e. flag=2, locations are filtered out).

• float_fillval (float or None, optional (default: np.nan)) – Fill Value for masked pixels, this is only applied to float variables. Therefore e.g. mask variables are never filled but use the fill value as in the data.

read(timestamp, **kwargs)

Return an image for a specific timestamp.

Parameters:

timestamp (datetime.datetime) – Time stamp.

Returns:

image – pygeobase.object_base.Image object

Return type:

object

tstamps_for_daterange(start_date, end_date)

return timestamps for daterange, :param start_date: start of date range :type start_date: datetime.datetime :param end_date: end of date range :type end_date: datetime.datetime

Returns:

timestamps – list of datetime objects of each available image between start_date and end_date

Return type:

list

write_multiple(root_path, start_date, end_date, stackfile='stack.nc', **kwargs)

Create multiple netcdf files or a netcdf stack in the passed directoy for a range of time stamps. Note that stacking gets slower when the stack gets larger. Empty images (if no original data can be loaded) are excluded here as well.

Parameters:

• root (str) – Directory where the files / the stack are/is stored

• start_date (datetime) – Start date of images to write down

• end_date – Last date of images to write down

• stackfile (str, optional (default: 'stack.nc')) – Name of the stack file to create in root_path. If no name is passed we create single images instead of a stack with the same name as the original images (faster).

• kwargs – kwargs that are passed to the image reading function

class smos.interface.SMOSImg(filename, mode='r', parameters=None, flatten=False, grid=<smos.grid.EASE25CellGrid object>, read_flags=(0, 1), float_fillval=nan)

Bases: ImageBase

Class for reading one SMOS netcdf image file.

Parameters:

• filename (str) – filename of the SMOS nc image file

• mode (str, optional (default: 'r')) – mode of opening the file, only ‘r’ is implemented at the moment

• parameters (str or list, optional (default: None)) – one or list of parameters to read. We add ‘Quality_Flags’ if ‘read_flags’ is not None. All parameters are described in docs/varnames.rst. If None are passed, all parameters are read.

• flatten (bool, optional (default: False)) – If set then the data is read into 1D arrays. This is used to e.g reshuffle the data.

• grid (pygeogrids.CellGrid, optional (default: EASE25CellGrid)) – Grid that the image data is organised on, by default the global EASE25 grid is used.

• read_flags (tuple or None, optional (default: (0, 1))) – Filter values to read based on the selected QUALITY_FLAGS. Values for locations that are not assigned any of the here passed flags are replaces with NaN (by default only the missing-data, i.e. flag=2, locations are filtered out). If None is passed, no flags are considered.

• float_fillval (float or None, optional (default: np.nan)) – Fill Value for masked pixels, this is only applied to float variables. Therefore e.g. mask variables are never filled but use the fill value as in the data.

close()

Close file.

flush()

Flush data.

get_global_attrs(exclude=('history', 'NCO', 'netcdf_version_id', 'contact', 'institution', 'creation_time'))

read(timestamp)

Read a single SMOS image, if it exists, otherwise fill an empty image

Parameters:

timestamp (datetime) – Time stamp for the image to read.

read_masked_data(**kwargs)

Read data of an image file and mask the data according to specifications.

Returns:

image – pygeobase.object_base.Image object

Return type:

object

write(image, **kwargs)

Write the image to a separate output path. E.g. after reading only a subset of the parameters, or when reading a spatial subset (with a subgrid). If there is already a file, the new image is appended along the time dimension.

Parameters:

• image (str) – Path to netcdf file to create.

• kwargs – Additional kwargs are given to netcdf4.Dataset

class smos.interface.SMOSTs(ts_path, grid_path=None, index_add_time=False, drop_missing=True, **kwargs)

Bases: GriddedNcOrthoMultiTs

read(*args, **kwargs)

Read time series by grid point index, or by lonlat. Convert columns to ints if possible (if there are no Nans in it).

Parameters:

• lon (float) – Location longitude

• lat (float) – Location latitude

• OR (..)

• gpi (int) – Grid point Index

Returns:

df – Time Series data at the selected location

Return type:

pd.DataFrame

smos.misc module

smos.misc.get_first_last_day_images(img_path: str)

smos.misc.read_summary_yml(path: str) → dict

Read image summary and return fields as dict.

smos.reshuffle module

smos.reshuffle.firstfile(input_root)

Find the first file and read lat and lon and all variables

Parameters:

input_root (str) – Path to the root dir of image files

Returns:

• firstfile (str) – Path to the first found image file in the input_root

• vars (list) – List of variables in the file

smos.reshuffle.mkdate(datestring)

Create date string. :param datestring: Date string. :type datestring: str

Returns:

datestr – Date string as datetime.

Return type:

datetime

smos.reshuffle.parse_args(args)

Parse command line parameters for recursive download.

Parameters:

args (list of str) – Command line parameters as list of strings.

Returns:

args – Command line arguments.

Return type:

argparse.Namespace

smos.reshuffle.str2bool(val)

Module contents