sup3r.bias.bias_correct_means.VortexMeanPrepper

class VortexMeanPrepper(path_pattern, in_heights, out_heights, overwrite=False)[source]

Bases: object

Class for converting monthly vortex tif files for each height to a single h5 files containing all monthly means for all requested output heights.

Parameters:

path_pattern (str) – Pattern for input tif files. Needs to include {month} and {height} format keys.
in_heights (list) – List of heights for input files.
out_heights (list) – List of output heights used for interpolation
overwrite (bool) – Whether to overwrite intermediate netcdf files containing the interpolated masked monthly means.

Methods

`convert_all_tifs`()	Write netcdf files for all heights for all months.
`convert_month_height_tif`(month, height)	Get windspeed mean for the given month and hub height from the corresponding input file and write this to a netcdf file.
`convert_month_tif`(month)	Write netcdf files for all heights for the given month.
`get_all_data`()	Get interpolated monthly means for all out heights as a dictionary to use for h5 writing.
`get_height_files`(month)	Get set of netcdf files for given month
`get_input_file`(month, height)	Get vortex tif file for given month and height.
`get_lat_lon`()	Get lat lon grid
`get_month`(month)	Get interpolated means for all hub heights for the given month.
`get_output_file`(month)	Get name of netcdf file for a given month.
`interp`(data)	Interpolate data to requested output heights.
`run`(path_pattern, in_heights, out_heights, ...)	Read vortex tif files, convert these to monthly netcdf files for all input heights, interpolate this data to requested output heights, mask fill values, and write all data to h5 file.
`write_data`(fp_out, out)	Write monthly means for all heights to h5 file

Attributes

`global_attrs`	Get dictionary on how this data is prepared
`in_features`	List of features corresponding to input heights.
`input_files`	Get list of all input files used for h5 meta.
`mask`	Mask coordinates without data
`meta`	Get meta with latitude/longitude
`out_features`	List of features corresponding to output heights
`output_files`	List of output monthly output files each with windspeed for all input heights
`time_index`	Get time index so output conforms to standard format

property in_features: List of features corresponding to input heights.

property out_features: List of features corresponding to output heights

get_input_file(month, height)[source]: Get vortex tif file for given month and height.

get_height_files(month)[source]: Get set of netcdf files for given month

property input_files: Get list of all input files used for h5 meta.

get_output_file(month)[source]: Get name of netcdf file for a given month.

property output_files: List of output monthly output files each with windspeed for all input heights

convert_month_height_tif(month, height)[source]: Get windspeed mean for the given month and hub height from the corresponding input file and write this to a netcdf file.

convert_month_tif(month)[source]: Write netcdf files for all heights for the given month.

convert_all_tifs()[source]: Write netcdf files for all heights for all months.

property mask: Mask coordinates without data

get_month(month)[source]

Get interpolated means for all hub heights for the given month.

Parameters:: month (str) – Name of month to get data for
Returns:: data (xarray.Dataset) – xarray dataset object containing interpolated monthly windspeed means for all input and output heights

interp(data)[source]

Interpolate data to requested output heights.

Parameters:: data (xarray.Dataset) – xarray dataset object containing windspeed for all input heights
Returns:: data (xarray.Dataset) – xarray dataset object containing windspeed for all input and output heights

get_lat_lon()[source]: Get lat lon grid

property meta: Get meta with latitude/longitude

property time_index: Get time index so output conforms to standard format

get_all_data()[source]

Get interpolated monthly means for all out heights as a dictionary to use for h5 writing.

Returns:: out (dict) – Dictionary of arrays containing monthly means for each hub height. Also includes latitude and longitude. Spatial dimensions are flattened

property global_attrs: Get dictionary on how this data is prepared

write_data(fp_out, out)[source]: Write monthly means for all heights to h5 file

classmethod run(path_pattern, in_heights, out_heights, fp_out, overwrite=False)[source]

Read vortex tif files, convert these to monthly netcdf files for all input heights, interpolate this data to requested output heights, mask fill values, and write all data to h5 file.

Parameters:

path_pattern (str) – Pattern for input tif files. Needs to include {month} and {height} format keys.
in_heights (list) – List of heights for input files.
out_heights (list) – List of output heights used for interpolation
fp_out (str) – Name of final h5 output file to write with means.
overwrite (bool) – Whether to overwrite intermediate netcdf files containing the interpolated masked monthly means.