deltametrics.mask.FlowMask

class deltametrics.mask.FlowMask(*args, flow_threshold, cube_key='velocity', **kwargs)

Flow field mask.

This mask implements a binarization of a raster based on flow field values, and can work for velocity, depth, discharge, etc.

If you pass a cube, we will try the ‘velocity’ field. To use a different field from the cube, specify the cube_key argument.

Examples

Initialize one FlowMask from velocity data and one from discharge data:

golfcube = dm.sample_data.golf()
fvmsk = dm.mask.FlowMask(
    golfcube['velocity'][-1, :, :],
    flow_threshold=0.3)
fdmsk = dm.mask.FlowMask(
    golfcube['discharge'][-1, :, :],
    flow_threshold=4)

fig, ax = plt.subplots(1, 2)
fvmsk.show(ax=ax[0])
fdmsk.show(ax=ax[1])
plt.show()

(png, hires.png)

__init__(*args, flow_threshold, cube_key='velocity', **kwargs)

Initialize the FlowMask.

Note

Needs docstring!

Methods

__init__(*args, flow_threshold[, cube_key])	Initialize the FlowMask.
from_array(_arr)	Create an ElevationMask 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

flow_threshold
integer_mask	Binary mask values as integer
mask	Binary mask values.
mask_type	Type of the mask (string)
shape
threshold	Generic property for ThresholdValueMask threshold.
variables

__getitem__(var)

Implement slicing.

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

static from_array(_arr)

Create an ElevationMask 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.

property threshold

Generic property for ThresholdValueMask threshold.

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