FlowMap
- class py_wake.flow_map.FlowMap(simulationResult, X, Y, localWind_j, WS_eff_jlk, TI_eff_jlk, plane)[source]
power_xylk
([with_wake_loss])aep_xylk
([normalize_probabilities, ...])Anual Energy Production of a potential wind turbine at all grid positions (x,y) for all wind directions (l) and wind speeds (k) in GWh.
aep_xy
([normalize_probabilities, with_wake_loss])Anual Energy Production of a potential wind turbine at all grid positions (x,y) (sum of all wind directions and wind speeds) in GWh.
plot_windturbines
([normalize_with, ax])plot_wake_map
([levels, cmap, plot_colorbar, ...])Plot effective wind speed contourf map
plot_ti_map
([levels, cmap, plot_colorbar, ...])Plot effective turbulence intensity contourf map
- aep_xy(normalize_probabilities=False, with_wake_loss=True, **wt_kwargs)[source]
Anual Energy Production of a potential wind turbine at all grid positions (x,y) (sum of all wind directions and wind speeds) in GWh.
see aep_xylk
- aep_xylk(normalize_probabilities=False, with_wake_loss=True, **wt_kwargs)[source]
Anual Energy Production of a potential wind turbine at all grid positions (x,y) for all wind directions (l) and wind speeds (k) in GWh.
- Parameters:
normalize_propabilities (Optional bool, defaults to False) –
In case only a subset of all wind speeds and/or wind directions is simulated, this parameter determines whether the returned AEP represents the energy produced in the fraction of a year where these flow cases occurs or a whole year of northern wind. If for example, wd=[0], then - False means that the AEP only includes energy from the faction of year
with northern wind (359.5-0.5deg), i.e. no power is produced the rest of the year. - True means that the AEP represents a whole year of northen wind. default is False
with_wake_loss (Optional bool, defaults to True) –
If True, wake loss is included, i.e. power is calculated using local effective wind speed
If False, wake loss is neglected, i.e. power is calculated using local free flow wind speed
wt_type (Optional arguments) – Additional required/optional arguments needed by the WindTurbines to computer power, e.g. type, Air_density
- all(dim=None, **kwargs)
Reduce this FlowMap’s data by applying all along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply all. By default all is applied over all dimensions.
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating all on this object’s data.
- Returns:
reduced – New FlowMap object with all applied to its data and the indicated dimension(s) removed.
- Return type:
- any(dim=None, **kwargs)
Reduce this FlowMap’s data by applying any along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply any. By default any is applied over all dimensions.
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating any on this object’s data.
- Returns:
reduced – New FlowMap object with any applied to its data and the indicated dimension(s) removed.
- Return type:
- count(dim=None, **kwargs)
Reduce this FlowMap’s data by applying count along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply count. By default count is applied over all dimensions.
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating count on this object’s data.
- Returns:
reduced – New FlowMap object with count applied to its data and the indicated dimension(s) removed.
- Return type:
- cumprod(dim=None, skipna=None, **kwargs)
Apply cumprod along some dimension of FlowMap.
- Parameters:
dim (str or sequence of str, optional) – Dimension over which to apply cumprod.
axis (int or sequence of int, optional) – Axis over which to apply cumprod. Only one of the ‘dim’ and ‘axis’ arguments can be supplied.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to cumprod.
- Returns:
cumvalue – New FlowMap object with cumprod applied to its data along the indicated dimension.
- Return type:
- cumsum(dim=None, skipna=None, **kwargs)
Apply cumsum along some dimension of FlowMap.
- Parameters:
dim (str or sequence of str, optional) – Dimension over which to apply cumsum.
axis (int or sequence of int, optional) – Axis over which to apply cumsum. Only one of the ‘dim’ and ‘axis’ arguments can be supplied.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to cumsum.
- Returns:
cumvalue – New FlowMap object with cumsum applied to its data along the indicated dimension.
- Return type:
- max(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying max along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply max. By default max is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating max on this object’s data.
- Returns:
reduced – New FlowMap object with max applied to its data and the indicated dimension(s) removed.
- Return type:
- mean(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying mean along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply mean. By default mean is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating mean on this object’s data.
- Returns:
reduced – New FlowMap object with mean applied to its data and the indicated dimension(s) removed.
- Return type:
- median(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying median along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply median. By default median is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating median on this object’s data.
- Returns:
reduced – New FlowMap object with median applied to its data and the indicated dimension(s) removed.
- Return type:
- min(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying min along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply min. By default min is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating min on this object’s data.
- Returns:
reduced – New FlowMap object with min applied to its data and the indicated dimension(s) removed.
- Return type:
- plot(data, clabel, levels=100, cmap=None, plot_colorbar=True, plot_windturbines=True, normalize_with=1, ax=None)[source]
Plot data as contouf map
- Parameters:
data (array_like) – 2D data array to plot
clabel (str) – colorbar label
levels (int or array-like, default 100) – Determines the number and positions of the contour lines / regions. If an int n, use n data intervals; i.e. draw n+1 contour lines. The level heights are automatically chosen. If array-like, draw contour lines at the specified levels. The values must be in increasing order.
cmap (str or Colormap, defaults 'Blues_r'.) – A Colormap instance or registered colormap name. The colormap maps the level values to colors.
plot_colorbar (bool, default True) – if True (default), colorbar is drawn
plot_windturbines (bool, default True) – if True (default), lines/circles showing the wind turbine rotors are plotted
ax (pyplot or matplotlib axes object, default None) –
- plot_ti_map(levels=100, cmap=None, plot_colorbar=True, plot_windturbines=True, ax=None)[source]
Plot effective turbulence intensity contourf map
- Parameters:
levels (int or array-like, default 100) – Determines the number and positions of the contour lines / regions. If an int n, use n data intervals; i.e. draw n+1 contour lines. The level heights are automatically chosen. If array-like, draw contour lines at the specified levels. The values must be in increasing order.
cmap (str or Colormap, defaults 'Blues'.) – A Colormap instance or registered colormap name. The colormap maps the level values to colors.
plot_colorbar (bool, default True) – if True (default), colorbar is drawn
plot_windturbines (bool, default True) – if True (default), lines/circles showing the wind turbine rotors are plotted
ax (pyplot or matplotlib axes object, default None) –
- plot_wake_map(levels=100, cmap=None, plot_colorbar=True, plot_windturbines=True, normalize_with=1, ax=None)[source]
Plot effective wind speed contourf map
- Parameters:
levels (int or array-like, default 100) – Determines the number and positions of the contour lines / regions. If an int n, use n data intervals; i.e. draw n+1 contour lines. The level heights are automatically chosen. If array-like, draw contour lines at the specified levels. The values must be in increasing order.
cmap (str or Colormap, defaults 'Blues_r'.) – A Colormap instance or registered colormap name. The colormap maps the level values to colors.
plot_colorbar (bool, default True) – if True (default), colorbar is drawn
plot_windturbines (bool, default True) – if True (default), lines/circles showing the wind turbine rotors are plotted
ax (pyplot or matplotlib axes object, default None) –
- prod(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying prod along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply prod. By default prod is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
min_count (int, default: None) – The required number of valid values to perform the operation. If fewer than min_count non-NA values are present the result will be NA. Only used if skipna is set to True or defaults to True for the array’s dtype. New in version 0.10.8: Added with the default being None. Changed in version 0.17.0: if specified on an integer array and skipna=True, the result will be a float array.
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating prod on this object’s data.
- Returns:
reduced – New FlowMap object with prod applied to its data and the indicated dimension(s) removed.
- Return type:
- std(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying std along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply std. By default std is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating std on this object’s data.
- Returns:
reduced – New FlowMap object with std applied to its data and the indicated dimension(s) removed.
- Return type:
- sum(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying sum along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply sum. By default sum is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
min_count (int, default: None) – The required number of valid values to perform the operation. If fewer than min_count non-NA values are present the result will be NA. Only used if skipna is set to True or defaults to True for the array’s dtype. New in version 0.10.8: Added with the default being None. Changed in version 0.17.0: if specified on an integer array and skipna=True, the result will be a float array.
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating sum on this object’s data.
- Returns:
reduced – New FlowMap object with sum applied to its data and the indicated dimension(s) removed.
- Return type:
- var(dim=None, skipna=None, **kwargs)
Reduce this FlowMap’s data by applying var along some dimension(s).
- Parameters:
dim (str or sequence of str, optional) – Dimension(s) over which to apply var. By default var is applied over all dimensions.
skipna (bool, optional) – If True, skip missing values (as marked by NaN). By default, only skips missing values for float dtypes; other dtypes either do not have a sentinel missing value (int) or skipna=True has not been implemented (object, datetime64 or timedelta64).
keep_attrs (bool, optional) – If True, the attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
**kwargs (dict) – Additional keyword arguments passed on to the appropriate array function for calculating var on this object’s data.
- Returns:
reduced – New FlowMap object with var applied to its data and the indicated dimension(s) removed.
- Return type: