Plotting#

emsarray can produce simple plots, to help you visualise your data quickly. Plots can be made from any supported format.

[1]:

import emsarray

Set up the environment…

[2]:

# This makes the figures nice and big for this notebook
from matplotlib import pyplot as plt
plt.rcParams['figure.dpi'] = 100
plt.rcParams['figure.figsize'] = (8, 5)
plt.rcParams['savefig.dpi'] = 100

# The coastlines used in the maps have some bad polygons,
# which cause some warnings. Lets turn those off.
import warnings
warnings.filterwarnings(
    "ignore", message="Shapefile shape has invalid polygon",
    category=UserWarning, module="shapefile")

A quick demonstration before we get started!

[3]:

gbr4 = emsarray.tutorial.open_dataset('gbr4')
gbr4

The botz variable indicates the depth of the ocean floor at a particular cell.

The data will be plotted on a map, wih coastlines overlayed. A colour ramp will be applied and automatically scaled to the range of the data.

[4]:

gbr4.ems.plot('botz', title='Depth of sea-bed')

Plotting computed data#

Any data can be plotted on the model grid, as long as the data has the same shape. To demonstrate this, let us make a plot of surface temperature for our American friends.

[11]:

farhenheit_temp = fraser_0['temp'] * 1.8 + 32
farhenheit_temp.attrs.update({
    'long_name': 'Surface temperature (°F)',
    'units': 'degrees Farhenheit'
})
fraser.ems.plot(farhenheit_temp)

Custom plots#

dataset.ems.plot() is useful for making quick plots of your data, but it does not create publication quality plots, and it does not expose any styling options. The following example shows how make a custom plot with your own styling, base layers, and titles. It uses a few tools provided by emsarray to extract the data and construct the polygons, but otherwise does all of the styling manually.

[12]:

import cartopy.crs as ccrs
import cartopy.io.img_tiles as cimgt
import emsarray
import matplotlib.pyplot as plt
import numpy as np
from emsarray.plot import polygon_to_patch, bounds_to_extent
from emsarray.utils import datetime_from_np_time
from matplotlib.collections import PatchCollection
from shapely.geometry import box

# What to plot
dataset = emsarray.tutorial.open_dataset("fraser")
dataset = dataset.isel(time=0, k=-1)
scalar = 'eta'
vector = ('u', 'v')
title = "Sea surface height and surface current velocity"
datetime_stamp = datetime_from_np_time(dataset["time"].values).strftime("%Y-%m-%d %H:%M")

# Constrain the view to this region
view_area = box(152.3, -26.8, 154, -23.5)

# What coordinate reference system the data are in
data_crs = dataset.ems.data_crs

# What coordinate reference system to plot the data in.
# You can choose any projection that you want.
view_crs = ccrs.NearsidePerspective(
    central_longitude=view_area.centroid.x, central_latitude=view_area.centroid.y)

# Set up a figure and some axes, then set view bounds
figure = plt.figure(figsize=(8, 10), dpi=100)
axes = plt.subplot(projection=view_crs)
axes.set_title(title + "\n" + datetime_stamp)
axes.set_aspect(aspect='equal', adjustable='datalim')
axes.set_extent(bounds_to_extent(view_area.bounds), crs=data_crs)

# Add some grid lines
gridlines = axes.gridlines(draw_labels=True, color=(0.1, 0.1, 0.1, 0.1))
gridlines.top_labels = False
gridlines.right_labels = False

# Add a base image layer
axes.add_image(cimgt.Stamen(style='terrain-background', desired_tile_form='RGBA'), 9)
# axes.add_image(cimgt.Stamen(style='terrain-labels', desired_tile_form='RGBA'), 9)
figure.text(
    0.5, 0, "Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL.",
    va='bottom', ha='center', fontsize=8)

# Plot the data
patches = dataset.ems.make_patch_collection(scalar, edgecolor='face', cmap='plasma')
axes.add_collection(patches)
figure.colorbar(patches, ax=axes, location='right', label='metres')

quiver = dataset.ems.make_quiver(axes, *vector)
axes.add_collection(quiver)
plt.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/IPython/core/formatters.py:339, in BaseFormatter.__call__(self, obj)
    337     pass
    338 else:
--> 339     return printer(obj)
    340 # Finally look for special method names
    341 method = get_real_method(obj, self.print_method)

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/IPython/core/pylabtools.py:151, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    148     from matplotlib.backend_bases import FigureCanvasBase
    149     FigureCanvasBase(fig)
--> 151 fig.canvas.print_figure(bytes_io, **kw)
    152 data = bytes_io.getvalue()
    153 if fmt == 'svg':

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/matplotlib/backend_bases.py:2290, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2284     renderer = _get_renderer(
   2285         self.figure,
   2286         functools.partial(
   2287             print_method, orientation=orientation)
   2288     )
   2289     with getattr(renderer, "_draw_disabled", nullcontext)():
-> 2290         self.figure.draw(renderer)
   2292 if bbox_inches:
   2293     if bbox_inches == "tight":

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/matplotlib/artist.py:73, in _finalize_rasterization.<locals>.draw_wrapper(artist, renderer, *args, **kwargs)
     71 @wraps(draw)
     72 def draw_wrapper(artist, renderer, *args, **kwargs):
---> 73     result = draw(artist, renderer, *args, **kwargs)
     74     if renderer._rasterizing:
     75         renderer.stop_rasterizing()

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/matplotlib/artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/matplotlib/figure.py:2803, in Figure.draw(self, renderer)
   2800         # ValueError can occur when resizing a window.
   2802 self.patch.draw(renderer)
-> 2803 mimage._draw_list_compositing_images(
   2804     renderer, self, artists, self.suppressComposite)
   2806 for sfig in self.subfigs:
   2807     sfig.draw(renderer)

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/matplotlib/image.py:132, in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    130 if not_composite or not has_images:
    131     for a in artists:
--> 132         a.draw(renderer)
    133 else:
    134     # Composite any adjacent images together
    135     image_group = []

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/matplotlib/artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/cartopy/mpl/geoaxes.py:553, in GeoAxes.draw(self, renderer, **kwargs)
    550     for factory, factory_args, factory_kwargs in self.img_factories:
    551         img, extent, origin = factory.image_for_domain(
    552             self._get_extent_geom(factory.crs), factory_args[0])
--> 553         self.imshow(img, extent=extent, origin=origin,
    554                     transform=factory.crs, *factory_args[1:],
    555                     **factory_kwargs)
    556 self._done_img_factory = True
    558 return matplotlib.axes.Axes.draw(self, renderer=renderer, **kwargs)

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/cartopy/mpl/geoaxes.py:318, in _add_transform.<locals>.wrapper(self, *args, **kwargs)
    313     raise ValueError(f'Invalid transform: Spherical {func.__name__} '
    314                      'is not supported - consider using '
    315                      'PlateCarree/RotatedPole.')
    317 kwargs['transform'] = transform
--> 318 return func(self, *args, **kwargs)

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/cartopy/mpl/geoaxes.py:1374, in GeoAxes.imshow(self, img, *args, **kwargs)
   1370 regrid_shape = self._regrid_shape_aspect(regrid_shape,
   1371                                          target_extent)
   1372 # Lazy import because scipy/pykdtree in img_transform are only
   1373 # optional dependencies
-> 1374 from cartopy.img_transform import warp_array
   1375 original_extent = extent
   1376 img, extent = warp_array(img,
   1377                          source_proj=transform,
   1378                          source_extent=original_extent,
   (...)
   1382                          mask_extrapolated=True,
   1383                          )

File ~/checkouts/readthedocs.org/user_builds/emsarray/conda/v0.1.0/lib/python3.9/site-packages/cartopy/img_transform.py:14, in <module>
     12 import numpy as np
     13 try:
---> 14     import pykdtree.kdtree
     15     _is_pykdtree = True
     16 except ImportError:

File pykdtree/kdtree.pyx:1, in init pykdtree.kdtree()

ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject

<Figure size 800x1000 with 2 Axes>

emsarray 0.1.0 documentation

Plotting

Contents

Plotting#

Selecting what to plot#

Plotting vectors#

Plotting computed data#

Custom plots#