rex.resource.BaseResource

class BaseResource(h5_file, mode='r', unscale=True, str_decode=True, group=None, hsds=False, hsds_kwargs=None)[source]

Bases: BaseDatasetIterable

Abstract Base class to handle resource .h5 files

Parameters:

h5_file (str) – Path to .h5 resource file
mode (str, optional) – Mode to instantiate h5py.File instance, by default ‘r’
unscale (bool, optional) – Boolean flag to automatically unscale variables on extraction, by default True
str_decode (bool, optional) – Boolean flag to decode the bytestring meta data into normal strings. Setting this to False will speed up the meta data read, by default True
group (str, optional) – Group within .h5 resource file to open, by default None
hsds (bool, optional) – Boolean flag to use h5pyd to handle .h5 ‘files’ hosted on AWS behind HSDS, by default False
hsds_kwargs (dict, optional) – Dictionary of optional kwargs for h5pyd, e.g., bucket, username, password, by default None

Methods

`close`()	Close h5 instance
`df_str_decode`(df)	Decode a dataframe with byte string columns into ordinary str cols.
`get_SAM_df`(site)	Placeholder for get_SAM_df method that it resource specific
`get_attrs`([dset])	Get h5 attributes either from file or dataset
`get_dset_properties`(dset)	Get dataset properties (shape, dtype, chunks)
`get_meta_arr`(rec_name[, rows])	Get a meta array by name (faster than DataFrame extraction).
`get_scale_factor`(dset)	Get dataset scale factor
`get_units`(dset)	Get dataset units
`open_dataset`(ds_name)	Open resource dataset
`preload_SAM`(h5_file, sites, tech[, unscale, ...])	Pre-load project_points for SAM

Attributes

`ADD_ATTR`
`SCALE_ATTR`
`UNIT_ATTR`
`adders`	Dictionary of all dataset add offset factors
`attrs`	Dictionary of all dataset attributes
`chunks`	Dictionary of all dataset chunk sizes
`coordinates`	(lat, lon) pairs
`data_version`	Get the version attribute of the data.
`datasets`	Datasets available
`dsets`	Datasets available
`dtypes`	Dictionary of all dataset dtypes
`global_attrs`	Global (file) attributes
`groups`	Groups available
`h5`	Open h5py File instance.
`lat_lon`	Extract (latitude, longitude) pairs
`meta`	Resource meta data DataFrame
`res_dsets`	Available resource datasets
`resource_datasets`	Available resource datasets
`scale_factors`	Dictionary of all dataset scale factors
`shape`	Resource shape (timesteps, sites) shape = (len(time_index), len(meta))
`shapes`	Dictionary of all dataset shapes
`time_index`	Resource DatetimeIndex
`units`	Dictionary of all dataset units

property h5

Open h5py File instance. If _group is not None return open Group

Returns:: h5 (h5py.File | h5py.Group)

property datasets

Datasets available

Returns:: list

property dsets

Datasets available

Returns:: list

property resource_datasets

Available resource datasets

Returns:: list

property res_dsets

Available resource datasets

Returns:: list

property groups

Groups available

Returns:: groups (list) – List of groups

property shape

Resource shape (timesteps, sites) shape = (len(time_index), len(meta))

Returns:: shape (tuple)

property meta

Resource meta data DataFrame

Returns:: meta (pandas.DataFrame)

property time_index

Resource DatetimeIndex

Returns:: time_index (pandas.DatetimeIndex)

property coordinates

(lat, lon) pairs

Returns:: lat_lon (ndarray)
Type:: Coordinates

property lat_lon

Extract (latitude, longitude) pairs

Returns:: lat_lon (ndarray)

property data_version

Get the version attribute of the data. None if not available.

Returns:: version (str | None)

property global_attrs

Global (file) attributes

Returns:: global_attrs (dict)

property attrs

Dictionary of all dataset attributes

Returns:: attrs (dict)

property shapes

Dictionary of all dataset shapes

Returns:: shapes (dict)

property dtypes

Dictionary of all dataset dtypes

Returns:: dtypes (dict)

property chunks

Dictionary of all dataset chunk sizes

Returns:: chunks (dict)

property adders

Dictionary of all dataset add offset factors

Returns:: adders (dict)

property scale_factors

Dictionary of all dataset scale factors

Returns:: scale_factors (dict)

property units

Dictionary of all dataset units

Returns:: units (dict)

static df_str_decode(df)[source]

Decode a dataframe with byte string columns into ordinary str cols.

Parameters:: df (pd.DataFrame) – Dataframe with some columns being byte strings.
Returns:: df (pd.DataFrame) – DataFrame with str columns instead of byte str columns.

open_dataset(ds_name)[source]

Open resource dataset

Parameters:: ds_name (str) – Dataset name to open
Returns:: ds (ResourceDataset) – Resource for open resource dataset

get_attrs(dset=None)[source]

Get h5 attributes either from file or dataset

Parameters:: dset (str) – Dataset to get attributes for, if None get file (global) attributes
Returns:: attrs (dict) – Dataset or file attributes

get_dset_properties(dset)[source]

Get dataset properties (shape, dtype, chunks)

Parameters:

dset (str) – Dataset to get scale factor for

Returns:

shape (tuple) – Dataset array shape
dtype (str) – Dataset array dtype
chunks (tuple) – Dataset chunk size

get_scale_factor(dset)[source]

Get dataset scale factor

Parameters:: dset (str) – Dataset to get scale factor for
Returns:: float – Dataset scale factor, used to unscale int values to floats

get_units(dset)[source]

Get dataset units

Parameters:: dset (str) – Dataset to get units for
Returns:: str – Dataset units, None if not defined

get_meta_arr(rec_name, rows=slice(None, None, None))[source]

Get a meta array by name (faster than DataFrame extraction).

Parameters:

rec_name (str) – Named record from the meta data to retrieve.
rows (slice) – Rows of the record to extract.

Returns:

meta_arr (np.ndarray) – Extracted array from the meta data record name.

get_SAM_df(site)[source]

Placeholder for get_SAM_df method that it resource specific

Parameters:: site (int) – Site to extract SAM DataFrame for

close()[source]: Close h5 instance

classmethod preload_SAM(h5_file, sites, tech, unscale=True, str_decode=True, group=None, hsds=False, hsds_kwargs=None, time_index_step=None, means=False)[source]

Pre-load project_points for SAM

Parameters:

h5_file (str) – h5_file to extract resource from
sites (list) – List of sites to be provided to SAM (sites is synonymous with gids aka spatial indices)
tech (str) – Technology to be run by SAM
unscale (bool) – Boolean flag to automatically unscale variables on extraction
str_decode (bool) – Boolean flag to decode the bytestring meta data into normal strings. Setting this to False will speed up the meta data read.
group (str) – Group within .h5 resource file to open
hsds (bool, optional) – Boolean flag to use h5pyd to handle .h5 ‘files’ hosted on AWS behind HSDS, by default False
hsds_kwargs (dict, optional) – Dictionary of optional kwargs for h5pyd, e.g., bucket, username, password, by default None
time_index_step (int, optional) – Step size for time_index, used to reduce temporal resolution, by default None
means (bool, optional) – Boolean flag to compute mean resource when res_array is set, by default False

Returns:

SAM_res (SAMResource) – Instance of SAMResource pre-loaded with Solar resource for sites in project_points