nsrdb.data_model.base_handler.AncillaryVarHandler
- class AncillaryVarHandler(name, var_meta=None, date=None, **kwargs)[source]
Bases:
object
Base class for ancillary variable source data handling.
- Parameters:
name (str) – NSRDB var name.
var_meta (str | pd.DataFrame | None) – CSV file or dataframe containing meta data for all NSRDB variables. Defaults to the NSRDB var meta csv in git repo.
date (datetime.date) – Single day to extract data for.
kwargs (dict) – Optional kwargs to overwrite relevant data in the var_meta
Methods
Perform pre-flight checks - source dir check.
scale_data
(array)Perform a safe data scaling operation on a source data array.
unscale_data
(array)Perform a safe data unscaling operation on a source data array.
Attributes
DEFAULT_DIR
NN_METHOD
Return a dictionary of dataset attributes for HDF5 dataset attrs.
Get the nearest neighbor result cache csv file for this var.
Get the variable's intended storage chunk shape.
Get the data source.
Get the date for this handler
Long variable description.
Get the day of year for this handler
Get the source dataset name for the NSRDB variable.
Get the data type attribute.
Get the elevation correction preference.
Get the file path for the target NSRDB variable name based on the glob self.pattern.
Get the source file set name for the NSRDB variable.
Get the variable's intended storage datatype.
Get a boolean mask to locate the current variable in the meta data.
Get the NSRDB variable name.
Get the date after the date for this handler.
Get the file path for the date for the target NSRDB variable name based on the glob self.next_pattern.
Check if file for next date exists
Get the next date source file pattern which is sent to glob().
Get the source file pattern which is sent to glob().
Get the variable's physical maximum value.
Get the variable's physical minimum value.
Get the variable's intended storage scale factor.
Get the source directory containing the variable data files.
Get the spatial interpolation method.
Get the temporal interpolation method.
Get the units attribute.
Return the meta data for NSRDB variables.
- property attrs
Return a dictionary of dataset attributes for HDF5 dataset attrs.
- Returns:
attrs (dict) – Namespace of attributes to define the dataset.
- property cache_file
Get the nearest neighbor result cache csv file for this var.
- Returns:
_cache_file (False | str) – False for no caching, or a string filename (no path).
- property var_meta
Return the meta data for NSRDB variables.
- Returns:
_var_meta (pd.DataFrame) – Meta data for NSRDB variables.
- property name
Get the NSRDB variable name.
- property mask
Get a boolean mask to locate the current variable in the meta data.
- property data_source
Get the data source.
- Returns:
data_source (str) – Data source.
- property elevation_correct
Get the elevation correction preference.
- Returns:
elevation_correct (bool) – Whether or not to use elevation correction for the current var.
- property spatial_method
Get the spatial interpolation method.
- Returns:
spatial_method (str) – NN or IDW
- property scale_factor
Get the variable’s intended storage scale factor.
- Returns:
scale_factor (float) – Scale factor for the current variable. Data is multiplied by this scale factor before being stored.
- property date
Get the date for this handler
- Returns:
datetime.date
- property next_date
Get the date after the date for this handler. This is used to get the data for the next date for temporal interpolation
- Returns:
datetime.date
- property doy
Get the day of year for this handler
- Returns:
int
- property dtype
Get the data type attribute.
- Returns:
dtype (str) – Intended NSRDB disk data type.
- property description
Long variable description.
- Returns:
description (str) – Description of the variable to provide more info than the sometimes opaque dset names.
- property units
Get the units attribute.
- Returns:
units (str) – NSRDB variable units.
- property pattern
Get the source file pattern which is sent to glob().
- Returns:
str | None
- property next_pattern
Get the next date source file pattern which is sent to glob().
- Returns:
str | None
- property source_dir
Get the source directory containing the variable data files.
- Returns:
source_dir (str) – Directory containing source data files (with possible sub folders).
- property file
Get the file path for the target NSRDB variable name based on the glob self.pattern.
- Returns:
str
- property next_file
Get the file path for the date for the target NSRDB variable name based on the glob self.next_pattern. The file is used to get the data for the next date for temporal interpolation
- Returns:
str
- property next_file_exists
Check if file for next date exists
- property temporal_method
Get the temporal interpolation method.
- Returns:
temporal_method (str) – linear or nearest
- property file_set
Get the source file set name for the NSRDB variable. This is typically used for MERRA source filesets such as tavg1_2d_aer_Nx or tavg1_2d_slv_Nx (for MERRA)
- Returns:
str
- property dset_name
Get the source dataset name for the NSRDB variable. This is typically the netcdf or h5 source dataset name for the variable such as T2M or TOTANGSTR (for MERRA temp and alpha)
- Returns:
str
- property final_dtype
Get the variable’s intended storage datatype.
- Returns:
dtype (str) – Data type for the current variable.
- property chunks
Get the variable’s intended storage chunk shape.
- Returns:
chunks (tuple) – Data storage chunk shape (row_chunk, col_chunk).
- property physical_min
Get the variable’s physical minimum value.
- Returns:
physical_min (float) – Physical minimum value for the variable. Variable range can be truncated at this value. Must be consistent with the final dtype and scale factor.
- property physical_max
Get the variable’s physical maximum value.
- Returns:
physical_max (float) – Physical maximum value for the variable. Variable range can be truncated at this value. Must be consistent with the final dtype and scale factor.
- pre_flight()[source]
Perform pre-flight checks - source dir check.
- Returns:
missing (str) – Look for the source dir and return the string if not found. If nothing is missing, return an empty string.
- scale_data(array)[source]
Perform a safe data scaling operation on a source data array.
- Steps:
Enforce physical range limits
Apply scale factor (mulitply)
Round if integer
Enforce dtype bit range limits
Perform dtype conversion
Return manipulated array
- Parameters:
array (np.ndarray) – Source data array with full precision (likely float32).
- Returns:
array (np.ndarray) – Source data array with final datatype.