Cleopatra ocean styles on real data¶

The cmocean-derived ocean DATA_STYLES. The depth styles are shown on a real global relief field — ETOPO5 bathymetry over the North Atlantic & Europe (ocean depth + land elevation), fetched from the PacIOOS ERDDAP. The remaining ocean variables (SST, salinity, chlorophyll, currents, …) each want their own gridded field; those aren't bundled here, so they're shown as their colormaps (the honest thing — colours, not stand-in data).

In [1]:

from pathlib import Path

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

import cleopatra
from cleopatra.glyphs.gridded.array_glyph import ArrayGlyph
from cleopatra.styling.colors import resolve_single_layer_style

print("cleopatra", cleopatra.__version__)

DATA = Path("../../../examples/data")
z = np.load(DATA / "etopo5_natlantic.npz")
elev = z["elevation"].astype(float)[
    ::-1
]  # fixture is lat-ascending -> flip to north-up
# metres: <0 ocean depth, >0 land
extent = [float(v) for v in z["extent"]]
depth = np.where(elev < 0, elev, np.nan)  # ocean-only depths
print(
    "ETOPO5:",
    elev.shape,
    "elevation",
    (round(np.nanmin(elev)), round(np.nanmax(elev))),
    "m",
)
from cleopatra.styling.params import DataStyle

from pathlib import Path import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np import cleopatra from cleopatra.glyphs.gridded.array_glyph import ArrayGlyph from cleopatra.styling.colors import resolve_single_layer_style print("cleopatra", cleopatra.__version__) DATA = Path("../../../examples/data") z = np.load(DATA / "etopo5_natlantic.npz") elev = z["elevation"].astype(float)[ ::-1 ] # fixture is lat-ascending -> flip to north-up # metres: <0 ocean depth, >0 land extent = [float(v) for v in z["extent"]] depth = np.where(elev < 0, elev, np.nan) # ocean-only depths print( "ETOPO5:", elev.shape, "elevation", (round(np.nanmin(elev)), round(np.nanmax(elev))), "m", ) from cleopatra.styling.params import DataStyle

cleopatra 0.45.0
ETOPO5: (433, 865) elevation (-6369, 3902) m

Depth styles on real ETOPO5 bathymetry¶

topography colours land and sea together; bathymetry colours ocean depth only. Both are the real relief field.

In [2]:

fig, axes = plt.subplots(1, 2, figsize=(13, 5.5))
gext = [extent[0], extent[2], extent[1], extent[3]]  # [xmin, ymin, xmax, ymax]
topo = ArrayGlyph(elev, extent=gext, ax=axes[0])
topo.plot(
    add_colorbar=False,
    title="topography — land & sea (real ETOPO5)",
    data_style=DataStyle(style="topography"),
)
depth_glyph = ArrayGlyph(depth, extent=gext, ax=axes[1])
depth_glyph.plot(
    add_colorbar=False,
    title="bathymetry — ocean depth (real ETOPO5)",
    data_style=DataStyle(style="bathymetry"),
)
for ax in axes:
    ax.set_xticks([])
    ax.set_yticks([])
fig.tight_layout()
plt.show()

fig, axes = plt.subplots(1, 2, figsize=(13, 5.5)) gext = [extent[0], extent[2], extent[1], extent[3]] # [xmin, ymin, xmax, ymax] topo = ArrayGlyph(elev, extent=gext, ax=axes[0]) topo.plot( add_colorbar=False, title="topography — land & sea (real ETOPO5)", data_style=DataStyle(style="topography"), ) depth_glyph = ArrayGlyph(depth, extent=gext, ax=axes[1]) depth_glyph.plot( add_colorbar=False, title="bathymetry — ocean depth (real ETOPO5)", data_style=DataStyle(style="bathymetry"), ) for ax in axes: ax.set_xticks([]) ax.set_yticks([]) fig.tight_layout() plt.show()

All ocean style colormaps¶

Every ocean DATA_STYLES preset's colormap, as a swatch. Apply any of them to your own gridded variable with ArrayGlyph(field, extent=..., ax=ax).plot(style="salinity", ...).

In [3]:

ocean = [
    "bathymetry",
    "topography",
    "sea_surface_temperature",
    "salinity",
    "water_density",
    "chlorophyll",
    "dissolved_oxygen",
    "turbidity",
    "current_speed",
    "sea_ice",
    "sea_level_anomaly",
    "vorticity",
    "phase",
    "solar_radiation",
    "rainfall",
]


def style_cmap(style):
    _, cfg = resolve_single_layer_style(style)
    c = cfg["cmap"]
    return c if hasattr(c, "N") else mpl.colormaps[c]


grad = np.linspace(0, 1, 256).reshape(1, -1)
fig, axes = plt.subplots(len(ocean), 1, figsize=(8, 0.42 * len(ocean)))
fig.subplots_adjust(left=0.26, right=0.98, top=0.99, bottom=0.02, hspace=0.5)
for ax, style in zip(axes, ocean):
    ax.imshow(grad, aspect="auto", cmap=style_cmap(style))
    ax.set_xticks([])
    ax.set_yticks([])
    ax.text(
        -0.02,
        0.5,
        style,
        transform=ax.transAxes,
        ha="right",
        va="center",
        family="monospace",
        fontsize=9,
    )
plt.show()

ocean = [ "bathymetry", "topography", "sea_surface_temperature", "salinity", "water_density", "chlorophyll", "dissolved_oxygen", "turbidity", "current_speed", "sea_ice", "sea_level_anomaly", "vorticity", "phase", "solar_radiation", "rainfall", ] def style_cmap(style): _, cfg = resolve_single_layer_style(style) c = cfg["cmap"] return c if hasattr(c, "N") else mpl.colormaps[c] grad = np.linspace(0, 1, 256).reshape(1, -1) fig, axes = plt.subplots(len(ocean), 1, figsize=(8, 0.42 * len(ocean))) fig.subplots_adjust(left=0.26, right=0.98, top=0.99, bottom=0.02, hspace=0.5) for ax, style in zip(axes, ocean): ax.imshow(grad, aspect="auto", cmap=style_cmap(style)) ax.set_xticks([]) ax.set_yticks([]) ax.text( -0.02, 0.5, style, transform=ax.transAxes, ha="right", va="center", family="monospace", fontsize=9, ) plt.show()