rex.multi_file_resource.MultiFileWTK
- class MultiFileWTK(h5_source, unscale=True, str_decode=True, check_files=False, use_lapse_rate=True)[source]
Bases:
MultiFileResource
,WindResource
Class to handle 5min WIND Toolkit data
See also
resource.MultiFileResource
Parent class
resource.WindResource
Parent class
Examples
MultiFileWTK automatically searches for files of the form *m.h5
>>> file = '$TESTDATADIR/wtk' >>> with MultiFileWTK(file) as res: >>> print(list(res._h5_files) >>> print(res.datasets) ['$TESTDATADIR/wtk_2010_200m.h5', '$TESTDATADIR/wtk_2010_100m.h5'] ['coordinates', 'meta', 'pressure_100m', 'pressure_200m', 'temperature_100m', 'temperature_200m', 'time_index', 'winddirection_100m', 'winddirection_200m', 'windspeed_100m', 'windspeed_200m']
MultiFileWTK, like WindResource can interpolate / extrapolate hub-heights
>>> with MultiFileWTK(file) as res: >>> wspd = res['windspeed_150m'] >>> >>> wspd [[16.19 16.25 16.305 ... 16.375 16.39 16.39 ] [16.15 16.205 16.255001 ... 16.35 16.365 16.39 ] [16.154999 16.195 16.23 ... 16.335 16.32 16.34 ] ... [10.965 11.675 12.08 ... 15.18 14.805 14.42 ] [11.66 11.91 12.535 ... 13.31 12.23 12.335 ] [12.785 13.295 14.014999 ... 12.205 11.360001 11.64 ]]
- Parameters:
h5_source (str | list) – Unix shell style pattern path with * wildcards to multi-file resource file sets. Files must have the same time index and coordinates but can have different datasets. Can also be an explicit list of complete filepaths.
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.
check_files (bool) – Check to ensure files have the same coordinates and time_index
use_lapse_rate (bool) – If a dataset is only available at a single hub-height and this flag value is set to True, pressure / temperature values will be calculated using linear lapse rate adjustment from the available hub height to the requested one. If the flag value is set to False, the value of these variables at the single available hub-height will be returned for all requested heights. This option has no effect if data is available at multiple hub-heights.
Methods
circular_interp
(ts_1, h_1, ts_2, h_2, h)Circular interpolate/extrapolate time-series data to height h
close
()Close h5 instance
df_str_decode
(df)Decode a dataframe with byte string columns into ordinary str cols.
get_SAM_df
(site, height[, require_wind_dir, ...])Get SAM wind resource DataFrame for given site
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
monin_obukhov_extrapolation
(ts_1, h_1, z0, L, h)Monin-Obukhov extrapolation
open_dataset
(ds_name)Open resource dataset
power_law_interp
(ts_1, h_1, ts_2, h_2, h[, mean])Power-law interpolate/extrapolate time-series data to height h
preload_SAM
(h5_source, sites, hub_heights[, ...])Placeholder for classmethod that will pre-load project_points for SAM
shortest_angle
(a0, a1)Calculate the shortest angle distance between a0 and a1
stability_function
(zeta)Calculate stability function depending on sign of L (negative is unstable, positive is stable)
Attributes
ADD_ATTR
INTERPOLABLE_DSETS
Air Temperature and Pressure lapse rate in C/km and Pa/km
SCALE_ATTR
UNIT_ATTR
VARIABLE_NAME
VARIABLE_UNIT
Dictionary of all dataset add offset factors
Dictionary of all dataset attributes
Dictionary of all dataset chunk sizes
(lat, lon) pairs
Get the version attribute of the data.
Datasets available
Datasets available
Dictionary of all dataset dtypes
Global (file) attributes
Groups available
Open h5py File instance.
Extract (latitude, longitude) pairs
Resource meta data DataFrame
Available resource datasets
Available resource datasets
Dictionary of all dataset scale factors
Resource shape (timesteps, sites) shape = (len(time_index), len(meta))
Dictionary of all dataset shapes
Resource DatetimeIndex
Dictionary of all dataset units
- classmethod preload_SAM(h5_source, sites, hub_heights, unscale=True, str_decode=True, time_index_step=None, means=False, require_wind_dir=False, precip_rate=False, icing=False, check_files=False)[source]
Placeholder for classmethod that will pre-load project_points for SAM
- Parameters:
h5_source (str | list) – Unix shell style pattern path with * wildcards to multi-file resource file sets. Files must have the same time index and coordinates but can have different datasets. Can also be an explicit list of complete filepaths.
sites (list) – List of sites to be provided to SAM (sites is synonymous with gids aka spatial indices)
hub_heights (int | float | list) – Hub heights to extract for 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.
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
require_wind_dir (bool) – Boolean flag as to whether wind direction will be loaded.
precip_rate (bool) – Boolean flag as to whether precipitationrate_0m will be preloaded
icing (bool) – Boolean flag as to whether icing is analyzed. This will preload relative humidity.
check_files (bool) – Check to ensure files have the same coordinates and time_index
- Returns:
SAM_res (SAMResource) – Instance of SAMResource pre-loaded with Solar resource for sites in project_points
- LAPSE_RATES = {'pressure': 11109, 'temperature': 6.56}
Air Temperature and Pressure lapse rate in C/km and Pa/km
- property adders
Dictionary of all dataset add offset factors
- Returns:
adders (dict)
- property attrs
Dictionary of all dataset attributes
- Returns:
attrs (dict)
- property chunks
Dictionary of all dataset chunk sizes
- Returns:
chunks (dict)
- classmethod circular_interp(ts_1, h_1, ts_2, h_2, h)
Circular interpolate/extrapolate time-series data to height h
- Parameters:
ts_1 (ndarray) – Time-series array at height h_1
h_1 (int | float) – Height corresponding to time-seris ts_1
ts_2 (ndarray) – Time-series array at height h_2
h_2 (int | float) – Height corresponding to time-seris ts_2
h (int | float) – Height of desired time-series
- Returns:
out (ndarray) – Time-series array at height h
- close()
Close h5 instance
- property coordinates
(lat, lon) pairs
- Returns:
lat_lon (ndarray)
- Type:
Coordinates
- property data_version
Get the version attribute of the data. None if not available.
- Returns:
version (str | None)
- property datasets
Datasets available
- Returns:
list
- static df_str_decode(df)
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.
- property dsets
Datasets available
- Returns:
list
- property dtypes
Dictionary of all dataset dtypes
- Returns:
dtypes (dict)
- get_SAM_df(site, height, require_wind_dir=False, icing=False, add_header=False)
Get SAM wind resource DataFrame for given site
- Parameters:
site (int) – Site to extract SAM DataFrame for
height (int) – Hub height to extract SAM variables at
require_wind_dir (bool, optional) – Boolean flag as to whether wind direction will be loaded, by default False
icing (bool, optional) – Boolean flag to include relativehumitidy for icing calculation, by default False
add_header (bool, optional) – Add units and hub_height below variable names, needed for SAM .csv, by default False
- Returns:
res_df (pandas.DataFrame) – time-series DataFrame of resource variables needed to run SAM
- get_attrs(dset=None)
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)
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_meta_arr(rec_name, rows=slice(None, None, None))
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_scale_factor(dset)
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)
Get dataset units
- Parameters:
dset (str) – Dataset to get units for
- Returns:
str – Dataset units, None if not defined
- property global_attrs
Global (file) attributes
- Returns:
global_attrs (dict)
- property groups
Groups available
- Returns:
groups (list) – List of groups
- property h5
Open h5py File instance. If _group is not None return open Group
- Returns:
h5 (h5py.File | h5py.Group)
- property lat_lon
Extract (latitude, longitude) pairs
- Returns:
lat_lon (ndarray)
- property meta
Resource meta data DataFrame
- Returns:
meta (pandas.DataFrame)
- classmethod monin_obukhov_extrapolation(ts_1, h_1, z0, L, h)
Monin-Obukhov extrapolation
- Parameters:
ts_1 (ndarray) – Time-series array at height h_1
- h_1int | float
Height corresponding to time-seris ts_1
- z0: int | float | ndarray
Roughness length
- Lndarray
time-series of Obukhov length (m; measure of stability)
- hint | float
Desired height
- Returns:
ndarray – new wind speed from MO extrapolation.
- open_dataset(ds_name)
Open resource dataset
- Parameters:
ds_name (str) – Dataset name to open
- Returns:
ds (ResourceDataset) – Resource for open resource dataset
- static power_law_interp(ts_1, h_1, ts_2, h_2, h, mean=True)
Power-law interpolate/extrapolate time-series data to height h
- Parameters:
ts_1 (ndarray) – Time-series array at height h_1
h_1 (int | float) – Height corresponding to time-seris ts_1
ts_2 (ndarray) – Time-series array at height h_2
h_2 (int | float) – Height corresponding to time-seris ts_2
h (int | float) – Height of desired time-series
mean (bool) – Calculate average alpha versus point by point alpha
- Returns:
out (ndarray) – Time-series array at height h
- property res_dsets
Available resource datasets
- Returns:
list
- property resource_datasets
Available resource datasets
- Returns:
list
- property scale_factors
Dictionary of all dataset scale factors
- Returns:
scale_factors (dict)
- property shape
Resource shape (timesteps, sites) shape = (len(time_index), len(meta))
- Returns:
shape (tuple)
- property shapes
Dictionary of all dataset shapes
- Returns:
shapes (dict)
- static shortest_angle(a0, a1)
Calculate the shortest angle distance between a0 and a1
- Parameters:
a0 (int | float) – angle 0 in degrees
a1 (int | float) – angle 1 in degrees
- Returns:
da (int | float) – shortest angle distance between a0 and a1
- static stability_function(zeta)
Calculate stability function depending on sign of L (negative is unstable, positive is stable)
- Parameters:
zeta (ndarray) – Normalized length
- Returns:
numpy.ndarray – stability measurements.
- property time_index
Resource DatetimeIndex
- Returns:
time_index (pandas.DatetimeIndex)
- property units
Dictionary of all dataset units
- Returns:
units (dict)