utils

This module contains various i/o and utility functions

Functions

add_polyline(track, gdf)	Updates a geopandas dataframe with a polyline.
calculate_hillshade(img[, az, elev_angle])	Calculates hillshade
plot_map(raster[, loc, title, figsize, …])	Basic raster plot.
plot_network(df[, save])	Plots network
pt2rc(pts, profile)	Returns row and column.
rc2pt(rc, profile)	Returns the center x, y coordinates of cells at (row, column) locations.
read_raster(fn)	Reads raster into a 2D numpy array.

read_raster(fn)

Reads raster into a 2D numpy array.

Parameters:fn (string) – path to raster image (assume geotiff) Returns:

• ras (2D numpy array) – raster
• profile (dictionary) – raster geospatial information

add_polyline(track, gdf)

Updates a geopandas dataframe with a polyline.

Parameters:

• track (list of tuples) – list of coordinates representing a polyline
• gdf (geodataframe) –

Returns:

gdf – Updated geodataframe

Return type:

geodataframe

rc2pt(rc, profile)

Returns the center x, y coordinates of cells at (row, column) locations.

Parameters:

• rc (list) – list of rows and column pairs
• profile (dictionary) – raster geospatial information

Returns:

pts – list of tuples representing (x,y) coordinates

Return type:

list

pt2rc(pts, profile)

Returns row and column.

Parameters:

• pts (shapely point) – points
• profile (dictionary) – raster geospatial information

Returns:

r,c – rows and columns

Return type:

tuple of numpy arrays

Notes

Expects the point column of a geopandas dataframe and returns the rows and columns for each point. No checks on whether points are within bounding box.

plot_map(raster, loc=None, title=None, figsize=(5, 5), cmap='viridis', cbar=False, save=None, **kwother)

Basic raster plot.

Parameters:

• raster (dictionary) –

  dictionary must have at least two entries:

  • ’ras’: 2D numpy array representing a raster
  • **’profile’: raster information (as derived from rasterio)
  • Optional entries are:
    • ’bground’: a 2D numpy array representing a background raster. Typically a hillshade.
    • ’paths’: dataframe representing a network of paths as obtained from calculate_paths()
• loc (dictionary or geodataframe, optional) –

  used to identify point locations. if dictionary then it must have at least two entries:

  • ’df’: geopandas framework holding point data.
  • ’label’: name of the column in ‘df’ used to label points.
• title (string, optional) – if not empty then title to be used when displaying ras
• figsize (tuple) – Size of figure. Default: (5,5)
• cmap (string) – name of the matplotlib colormap. Default: ‘viridis’
• cbar (boolean) – if True colorbar is displayed. Default: False
• save (string, optional) – if not empty then name of the output image. Default: None

calculate_hillshade(img, az=135, elev_angle=40)

Calculates hillshade

Parameters:

• img (2D numpy array) – array with elevation values
• az (float) – Horizontal direction of the source of light (degrees). Default: 135 degrees
• elev_angle (float) – elevation angle of the source of light (degrees). Default: 40 degrees

plot_network(df, save=None)

Plots network

Parameters:

• df (dataframe) – contains the ids of origin and destination of each path in the network
• save (string) – filename (‘.png’ added). Default: None

Notes

The dataframe above is the output from running generate.network_layout(). To save output user must supply filename. An image file with ‘.png’ extension will be saved to local directory.