#!/bin/env python
# -*coding: UTF-8 -*-
#
# We try to import dependencies and catch missing module errors in order to avoid to load argopy just because
# Matplotlib is not installed.
#
# Decorator warnUnless is mandatory
#
import pandas as pd
from .utils import STYLE, has_seaborn, has_mpl, has_cartopy, has_ipython, has_ipywidgets
from .utils import axes_style, discrete_coloring, latlongrid, land_feature
from ..utilities import warnUnless, check_wmo
if has_mpl:
import matplotlib.pyplot as plt
if has_seaborn:
STYLE["axes"] = "dark"
import seaborn as sns
if has_cartopy:
import cartopy.crs as ccrs
if has_ipython:
from IPython.display import Image, display
if has_ipywidgets:
import ipywidgets
[docs]@warnUnless(has_ipython, "requires IPython to work as expected, only URLs are returned otherwise")
def open_sat_altim_report(WMO=None, embed="dropdown"):
""" Insert the CLS Satellite Altimeter Report figure in notebook cell
This is the method called when using the facade fetcher methods ``plot``:
>>> DataFetcher().float(6902745).plot('qc_altimetry')
Parameters
----------
WMO: int or list
The float WMO to display. By default, this is set to None and will insert the general dashboard.
embed: {'list', 'slide', 'dropdown'}, default: 'dropdown'
Set the embedding method. If set to None, simply return the list of urls to figures.
"""
WMOs = check_wmo(WMO)
urls = []
urls_dict = {}
for this_wmo in WMOs:
url = (
"https://data-argo.ifremer.fr/etc/argo-ast9-item13-AltimeterComparison/figures/%i.png"
% this_wmo
)
if embed == "list":
urls.append(Image(url, embed=True))
else:
urls.append(url)
urls_dict[this_wmo] = url
if embed == "list" and has_ipython:
return display(*urls)
elif embed == "slide" and has_ipython and has_ipywidgets:
def f(Float):
return Image(url=urls[Float])
return ipywidgets.interact(
f, Float=ipywidgets.IntSlider(min=0, max=len(urls) - 1, step=1)
)
elif embed == "dropdown" and has_ipython and has_ipywidgets:
def f(Float):
return Image(url=urls_dict[int(Float)])
return ipywidgets.interact(f, Float=[str(wmo) for wmo in WMOs])
else:
return urls_dict
@warnUnless(has_mpl, "requires matplotlib installed")
def plot_trajectory(
df: pd.core.frame.DataFrame,
style: str = STYLE["axes"],
add_legend: bool = True,
palette: str = STYLE["palette"],
set_global: bool = False,
with_cartopy: bool = has_cartopy,
with_seaborn: bool = has_seaborn,
**kwargs
):
""" Plot trajectories for an Argo index dataframe
This function is called by the Data and Index fetchers method 'plot' with the 'trajectory' option::
from argopy import IndexFetcher as ArgoIndexFetcher
from argopy import DataFetcher as ArgoDataFetcher
obj = ArgoIndexFetcher().float([6902766, 6902772, 6902914, 6902746])
# OR
obj = ArgoDataFetcher().float([6902766, 6902772, 6902914, 6902746])
fig, ax = obj.plot('trajectory')
Parameters
----------
df: Pandas DataFrame
Input data with columns: 'wmo','longitude','latitude'.
style: str
Define the axes style: 'white', 'darkgrid', 'whitegrid', 'dark', 'ticks'. Only used if Seaborn is available.
add_legend: bool
Add a box legend with list of floats. True by default for a maximum of 15 floats, otherwise no legend.
palette: str
Define colors to be used for floats: 'Set1' (default) or any other matplotlib colormap or name of
a Seaborn palette (deep, muted, bright, pastel, dark, colorblind).
set_global: bool
Plot trajectories on a global world map or not. False by default.
Returns
-------
fig: :class:`matplotlib.figure.Figure`
ax: :class:`matplotlib.axes.Axes`
"""
with axes_style(style):
# Set-up the figure and axis:
defaults = {"figsize": (10, 6), "dpi": 90}
if with_cartopy:
subplot_kw = {"projection": ccrs.PlateCarree()}
fig, ax = plt.subplots(**{**defaults, **kwargs}, subplot_kw=subplot_kw)
ax.add_feature(land_feature, edgecolor="black")
else:
fig, ax = plt.subplots(**{**defaults, **kwargs})
# How many float in this dataset ?
nfloat = len(df.groupby("wmo").first())
# Let's do the plot:
if with_seaborn:
mypal = sns.color_palette(palette, nfloat)
sns.lineplot(
x="longitude",
y="latitude",
hue="wmo",
data=df,
sort=False,
palette=mypal,
legend=False,
)
sns.scatterplot(
x="longitude", y="latitude", hue="wmo", data=df, palette=mypal
)
else:
mypal = discrete_coloring(palette, N=nfloat).cmap
for k, [name, group] in enumerate(df.groupby("wmo")):
group.plot.line(
x="longitude",
y="latitude",
ax=ax,
color=mypal(k),
legend=False,
label="_nolegend_",
)
group.plot.scatter(
x="longitude", y="latitude", ax=ax, color=mypal(k), label=name
)
if with_cartopy:
if set_global:
ax.set_global()
latlongrid(ax, dx="auto", dy="auto", fontsize="auto")
if not has_seaborn:
ax.get_yaxis().set_visible(False)
else:
if set_global:
ax.set_xlim(-180, 180)
ax.set_ylim(-90, 90)
ax.grid(visible=True, linewidth=1, color="gray", alpha=0.7, linestyle=":")
if add_legend and nfloat <= 15:
handles, labels = ax.get_legend_handles_labels()
# if has_seaborn:
# handles, labels = handles[1:], labels[1:]
plt.legend(
handles,
labels,
loc="upper right",
bbox_to_anchor=(1.25, 1),
title="Floats WMO",
)
else:
ax.get_legend().remove()
return fig, ax
@warnUnless(has_mpl, "requires matplotlib installed")
def bar_plot(
df: pd.core.frame.DataFrame,
by: str = "institution",
style: str = STYLE["axes"],
with_seaborn: bool = has_seaborn,
**kwargs
):
""" Create a bar plot for an Argo index dataframe
Parameters
----------
df: Pandas DataFrame
As returned by a fetcher index property
by: str
The profile property to plot. Default is 'institution'
style: str
Define the axes style: 'white', 'darkgrid', 'whitegrid', 'dark', 'ticks'. Only used if Seaborn is available.
Returns
-------
fig: :class:`matplotlib.figure.Figure`
ax: :class:`matplotlib.axes.Axes`
"""
if by not in df:
raise ValueError("'%s' is not a valid field for a bar plot" % by)
with axes_style(style):
defaults = {"figsize": (10, 6), "dpi": 90}
fig, ax = plt.subplots(**{**defaults, **kwargs})
if with_seaborn:
mind = df.groupby(by).size().sort_values(ascending=False).index
sns.countplot(y=by, data=df, order=mind)
else:
df.groupby(by).size().sort_values(ascending=True).plot.barh(ax)
ax.set_xlabel("Number of profiles")
ax.set_ylabel("")
return fig, ax
