Walkthrough#

import the functions

# %load_ext autoreload
# %autoreload 2
from antarctic_plots import profile
from antarctic_plots import fetch

Make a simple cross-section#

define a start and end point for a profile, in EPSG:3031 projection

a = (-1200e3, -1400e3)
b = (1000e3, 1400e3)

sample bedmap2 layers between these points, and plot the cross section

This may take a few minutes the first time it’s executed. The function calls fetch.bedmap2(), which is a function that uses the python package Pooch to handle dataset download and storage. All the functions in the antarctic_plots.fetch module use Pooch and download the data to your following local file:

  • Mac: ~/Library/Caches/<AppName>

  • Unix: ~/.cache/<AppName> or the value of the XDG_CACHE_HOME environment variable, if defined.

  • Windows: C:\Users\<user>\AppData\Local\<AppAuthor>\<AppName>\Cache

profile.plot_profile(
    method="points",
    start=a,
    stop=b,
)
_images/walkthrough_5_0.png

Instead of using a line, we can sample along a shapefile. Provide a file name, or load a shapefile with the function fetch.

Here is a path across the Ross Ice Shelf from Mulock Glacier to the ice front through Discover Deep.

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp("Disco_deep_transect"),
)
_images/walkthrough_7_0.png

Add a map#

show the profile location, background defaults to imagery

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp("Disco_deep_transect"),
    add_map=True,
)

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_images/walkthrough_9_1.png

Add a graph of data#

Show data along the profile. Default includes gravity and magnetics

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp("Disco_deep_transect"),
    add_map=True,
    data_dict="default",
    save=True,  # save the plot to use in README
    path="../cover_fig.png",
)

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_images/walkthrough_11_1.png

Change profile length#

clip the profile (either end) based on distance

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp("Disco_deep_transect"),
    data_dict="default",
    add_map=True,
    clip=True,
    min_dist=50e3,
    max_dist=200e3,
)

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_images/walkthrough_13_1.png

Change sampling resolution#

increase the resolution with the parameter “num” (defaults to 100)

# define new profile endpoints
a = (-590e3, -1070e3)
b = (-100e3, -545e3)

profile.plot_profile(
    method="points",
    start=a,
    stop=b,
    num=20,
    data_dict="default",
    add_map=True,
)

profile.plot_profile(
    method="points",
    start=a,
    stop=b,
    num=100,
    data_dict="default",
    add_map=True,
)

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_images/walkthrough_15_1.png 
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_images/walkthrough_15_3.png

or for shapefiles, with shp_num_points

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp(
        "Roosevelt_Island",
    ),
    shp_num_points=40,
    data_dict="default",
    add_map=True,
)

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp(
        "Roosevelt_Island",
    ),
    shp_num_points=200,
    data_dict="default",
    add_map=True,
)

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_images/walkthrough_17_1.png 
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_images/walkthrough_17_3.png

Alter map properies#

customize the map background; show the surface topography instead of imagery

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp("Disco_deep_transect"),
    data_dict="default",
    add_map=True,
    map_background=fetch.bedmap2("surface"),
)

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_images/walkthrough_19_1.png

change the maps colorscale

profile.plot_profile(
    method="shapefile",
    shapefile=fetch.sample_shp("Disco_deep_transect"),
    data_dict="default",
    add_map=True,
    map_background=fetch.bedmap2("surface"),
    map_cmap="viridis",
)

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_images/walkthrough_21_1.png

change the level of zoom on the map with the map_buffer argument. This is a percentage of total line distance, which defaults to 0.2 (120%) of profile length.

profile.plot_profile(
    method="points",
    start=a,
    stop=b,
    data_dict="default",
    add_map=True,
    map_buffer=0.1,
)

profile.plot_profile(
    method="points",
    start=a,
    stop=b,
    data_dict="default",
    add_map=True,
    map_buffer=0.8,
)

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_images/walkthrough_23_1.png 
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_images/walkthrough_23_3.png

Alter Cross-section properties#

Change buffer above and below cross-section layers, defaults to 0.1 (10% of data spread added above/below)

profile.plot_profile(
    method="points",
    start=a,
    stop=b,
    data_dict="default",
    add_map=True,
    layer_buffer=1.0,
)

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_images/walkthrough_25_1.png

Alter Cross-section properties#

Change buffer above and below data graph, defaults to 0.1 (10% of data spread added above/below)

profile.plot_profile(
    method="points", start=a, stop=b, data_dict="default", add_map=True, data_buffer=0.8
)

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_images/walkthrough_27_1.png

Custom layers, datasets, and colors#

The input for both the data and the layers are nested dictionaries, where each dictionary entry contains keys: ‘name’, ‘grid’, and ‘color’.

Use the function, profile.make_data_dict() to help create these dictionaries. It takes 3 inputs, which are:

  • a list of names

  • a list of grids either geotiff/netcdf file names or xarray.DataArrays

  • a list of colors.

For example, if you have a netcdf file ‘ice_velocity.nc’, you can make that into a dictionary with: profile.make_data_dict(['ice velocity'], ['ice_velocity.nc'], ['orange'])

Optionally, you can use Pooch.fetch to help download and store dataset from urls, and easily load them.

See the functions in the module antarctic_plots.fetch for examples and feel free to make a PR and add your datasets there.

WARNING - the DeepBedMap file is relatively large (0.5 Gb) and may take some time to download

# note, these datafile can be plotted at higher resolution by adding parameter 'spacing' to the 'fetch' function:
# fetch.gravity('BA', spacing=1e3) will use a 1km version of the Bouguer gravity anomaly.
data_dict = profile.make_data_dict(
    ["Bouguer gravity", "DeepBedMap"],
    [fetch.gravity("BA"), fetch.deepbedmap()],
    ["purple", "red"],
)

# get default bedmap2 layers
layers_dict = profile.default_layers()

# add dictionary entry of extra layer 'basement'
layers_dict["basement"] = {}
layers_dict["basement"]["name"] = "basement"
layers_dict["basement"]["grid"] = fetch.basement()
layers_dict["basement"]["color"] = "chocolate"

profile.plot_profile(
    "points",
    start=a,
    stop=b,
    add_map=True,
    data_dict=data_dict,
    layers_dict=layers_dict,
)

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_images/walkthrough_29_1.png

Control wheather to fill gaps in the cross-section layers. Note that the additional layer ‘basement’, doesn’t extend past the groundingline. By default, NaN’s in any layer are set equal to the layer above, causing the vertical line at ~100km.

profile.plot_profile(
    "points",
    start=a,
    stop=b,
    add_map=True,
    data_dict=data_dict,
    layers_dict=layers_dict,
    fillnans=False,
)

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_images/walkthrough_31_1.png