deltametrics.mask.DepositMask

class deltametrics.mask.DepositMask(*args, background_value=0, elevation_tolerance=0.1, **kwargs)

Create a DepositMask from an array.

This is a Mask for where any sediment has been deposited.

Note

This class might be improved by reimplementing as a subclass of ThresholdValueMask.

Examples

Make a mask for the final time of the simulation.

(Source code, png, hires.png)

__init__(*args, background_value=0, elevation_tolerance=0.1, **kwargs)

Initialize the DepositMask

This is a straightforward mask, simply checking where the elevation is greater than the background_value, outside some tolerance:

np.abs(elevation - background_value) > elevation_tolerance

However, using the mask provides benefits of array tracking and various integrations with other masks and functions.

Parameters:

• elevation (DataArray or ndarray) – Elevation data at the time of interest, i.e., the deposit surface.

• background_value (DataArray or ndarray or float, optional) – Either a float or array-like object specifying the values to use as the background basin, i.e., the inital basin underlying the deposit. Used to determine where sediment has deposited. Default value is to use 0, which may have unexpected results for determining the deposit.

• elevation_tolerance (float, optional) – Elevation tolerance for whether a location is labeled as a deposit. Default value is 0.1.

• **kwargs – Could be background_value, if not passed as *args[1].

Methods

__init__(*args[, background_value, ...])	Initialize the DepositMask
from_array(_arr)	Create a DepositMask from an array.
show([ax, title, ticks, colorbar])	Show the mask.
trim_mask(*args[, value, axis, length])	Replace a part of the mask with a new value.

Attributes

integer_mask	Binary mask values as integer
mask	Binary mask values.
mask_type	Type of the mask (string)
shape
variables

__getitem__(var)

Implement slicing.

Return values directly from the mask. Supported variables are only ‘mask’ or ‘integer’.

static from_array(_arr)

Create a DepositMask from an array.

Note

Instantiation with from_array will attempt to any data type (dtype) to boolean. This may have unexpected results. Convert your array to a boolean before using from_array to ensure the mask is created correctly.

Parameters:

_arr (ndarray) – The array with values to set as the mask. Can be any dtype but will be coerced to boolean.

property integer_mask

Binary mask values as integer

Important

integer_mask is a boolean array as 0 and 1 (integers). It is not suitible for multidimensional array indexing; see also mask.

Read-only mask attribute.

Type:

ndarray

property mask

Binary mask values.

Important

mask is a boolean array (not integer). See also integer_mask.

Read-only mask attribute.

Type:

ndarray

property mask_type

Type of the mask (string)

show(ax=None, title=None, ticks=False, colorbar=False, **kwargs)

Show the mask.

The Mask is shown in a matplotlib axis with imshow. The mask values are accessed from integer_mask, so the display will show as 0 for False and 1 for True. Default colormap is black and white.

Hint

Passes **kwargs to matplotlib.imshow.

Parameters:

ax (matplotlib.pyplot.Axes) – Which axes object to plot into.

trim_mask(*args, value=False, axis=1, length=None)

Replace a part of the mask with a new value.

This is sometimes necessary before using a mask in certain computations. Most often, this method is used to manually correct domain edge effects.

Parameters:

• *args (BaseCube subclass, optional) – Optionally pass a Cube object to the mask, and the dimensions to trim/replace the mask by will be inferred from the cube. In this case, axis and length have no effect.

• value – Value to replace in the trim region with. Default is False.

• axis – Which edge to apply the trim of length to. Default is 1, the top domain edge.

• length – The length of the trim. Note that this is not the array index.

Examples