# Copyright (c) 2015,2017,2018 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Utilities for use in making plots."""
from datetime import datetime
import posixpath
from matplotlib.collections import LineCollection
import matplotlib.patheffects as mpatheffects
from matplotlib.pyplot import imread
import numpy as np
import pkg_resources
from ..units import concatenate
[docs]def add_timestamp(ax, time=None, x=0.99, y=-0.04, ha='right', high_contrast=False,
pretext='Created: ', time_format='%Y-%m-%dT%H:%M:%SZ', **kwargs):
"""Add a timestamp to a plot.
Adds a timestamp to a plot, defaulting to the time of plot creation in ISO format.
Parameters
----------
ax : `matplotlib.axes.Axes`
The `Axes` instance used for plotting
time : `datetime.datetime`
Specific time to be plotted - datetime.utcnow will be use if not specified
x : float
Relative x position on the axes of the timestamp
y : float
Relative y position on the axes of the timestamp
ha : str
Horizontal alignment of the time stamp string
high_contrast : bool
Outline text for increased contrast
pretext : str
Text to appear before the timestamp, optional. Defaults to 'Created: '
time_format : str
Display format of time, optional. Defaults to ISO format.
Returns
-------
`matplotlib.text.Text`
The `matplotlib.text.Text` instance created
"""
if high_contrast:
text_args = {'color': 'white',
'path_effects':
[mpatheffects.withStroke(linewidth=2, foreground='black')]}
else:
text_args = {}
text_args.update(**kwargs)
if not time:
time = datetime.utcnow()
timestr = pretext + time.strftime(time_format)
return ax.text(x, y, timestr, ha=ha, transform=ax.transAxes, **text_args)
def _add_logo(fig, x=10, y=25, zorder=100, which='metpy', size='small', **kwargs):
"""Add the MetPy or Unidata logo to a figure.
Adds an image to the figure.
Parameters
----------
fig : `matplotlib.figure`
The `figure` instance used for plotting
x : int
x position padding in pixels
y : float
y position padding in pixels
zorder : int
The zorder of the logo
which : str
Which logo to plot 'metpy' or 'unidata'
size : str
Size of logo to be used. Can be 'small' for 75 px square or 'large' for
150 px square.
Returns
-------
`matplotlib.image.FigureImage`
The `matplotlib.image.FigureImage` instance created
"""
fname_suffix = {'small': '_75x75.png',
'large': '_150x150.png'}
fname_prefix = {'unidata': 'unidata',
'metpy': 'metpy'}
try:
fname = fname_prefix[which] + fname_suffix[size]
fpath = posixpath.join('_static', fname)
except KeyError:
raise ValueError('Unknown logo size or selection')
logo = imread(pkg_resources.resource_stream('metpy.plots', fpath))
return fig.figimage(logo, x, y, zorder=zorder, **kwargs)
[docs]def add_metpy_logo(fig, x=10, y=25, zorder=100, size='small', **kwargs):
"""Add the MetPy logo to a figure.
Adds an image of the MetPy logo to the figure.
Parameters
----------
fig : `matplotlib.figure`
The `figure` instance used for plotting
x : int
x position padding in pixels
y : float
y position padding in pixels
zorder : int
The zorder of the logo
size : str
Size of logo to be used. Can be 'small' for 75 px square or 'large' for
150 px square.
Returns
-------
`matplotlib.image.FigureImage`
The `matplotlib.image.FigureImage` instance created
"""
return _add_logo(fig, x=x, y=y, zorder=zorder, which='metpy', size=size, **kwargs)
[docs]def add_unidata_logo(fig, x=10, y=25, zorder=100, size='small', **kwargs):
"""Add the Unidata logo to a figure.
Adds an image of the MetPy logo to the figure.
Parameters
----------
fig : `matplotlib.figure`
The `figure` instance used for plotting
x : int
x position padding in pixels
y : float
y position padding in pixels
zorder : int
The zorder of the logo
size : str
Size of logo to be used. Can be 'small' for 75 px square or 'large' for
150 px square.
Returns
-------
`matplotlib.image.FigureImage`
The `matplotlib.image.FigureImage` instance created
"""
return _add_logo(fig, x=x, y=y, zorder=zorder, which='unidata', size=size, **kwargs)
# Not part of public API
def colored_line(x, y, c, **kwargs):
"""Create a multi-colored line.
Takes a set of points and turns them into a collection of lines colored by another array.
Parameters
----------
x : array-like
x-axis coordinates
y : array-like
y-axis coordinates
c : array-like
values used for color-mapping
kwargs : dict
Other keyword arguments passed to :class:`matplotlib.collections.LineCollection`
Returns
-------
The created :class:`matplotlib.collections.LineCollection` instance.
"""
# Mask out any NaN values
nan_mask = ~(np.isnan(x) | np.isnan(y) | np.isnan(c))
x = x[nan_mask]
y = y[nan_mask]
c = c[nan_mask]
# Paste values end to end
points = concatenate([x, y])
# Exploit numpy's strides to present a view of these points without copying.
# Dimensions are (segment, start/end, x/y). Since x and y are concatenated back to back,
# moving between segments only moves one item; moving start to end is only an item;
# The move between x any moves from one half of the array to the other
num_pts = points.size // 2
final_shape = (num_pts - 1, 2, 2)
final_strides = (points.itemsize, points.itemsize, num_pts * points.itemsize)
segments = np.lib.stride_tricks.as_strided(points, shape=final_shape,
strides=final_strides)
# Create a LineCollection from the segments and set it to colormap based on c
lc = LineCollection(segments, **kwargs)
lc.set_array(c)
return lc
[docs]def convert_gempak_color(c, style='psc'):
"""Convert GEMPAK color numbers into corresponding Matplotlib colors.
Takes a sequence of GEMPAK color numbers and turns them into
equivalent Matplotlib colors. Various GEMPAK quirks are respected,
such as treating negative values as equivalent to 0.
Parameters
----------
c : int or sequence of ints
GEMPAK color number(s)
style : str, optional
The GEMPAK 'device' to use to interpret color numbers. May be 'psc'
(the default; best for a white background) or 'xw' (best for a black background).
Returns
-------
List of strings of Matplotlib colors, or a single string if only one color requested.
"""
def normalize(x):
"""Transform input x to an int in range 0 to 31 consistent with GEMPAK color quirks."""
x = int(x)
if x < 0 or x == 101:
x = 0
else:
x = x % 32
return x
# Define GEMPAK colors (Matplotlib doesn't appear to like numbered variants)
cols = ['white', # 0/32
'black', # 1
'red', # 2
'green', # 3
'blue', # 4
'yellow', # 5
'cyan', # 6
'magenta', # 7
'#CD6839', # 8 (sienna3)
'#FF8247', # 9 (sienna1)
'#FFA54F', # 10 (tan1)
'#FFAEB9', # 11 (LightPink1)
'#FF6A6A', # 12 (IndianRed1)
'#EE2C2C', # 13 (firebrick2)
'#8B0000', # 14 (red4)
'#CD0000', # 15 (red3)
'#EE4000', # 16 (OrangeRed2)
'#FF7F00', # 17 (DarkOrange1)
'#CD8500', # 18 (orange3)
'gold', # 19
'#EEEE00', # 20 (yellow2)
'chartreuse', # 21
'#00CD00', # 22 (green3)
'#008B00', # 23 (green4)
'#104E8B', # 24 (DodgerBlue4)
'DodgerBlue', # 25
'#00B2EE', # 26 (DeepSkyBlue2)
'#00EEEE', # 27 (cyan2)
'#8968CD', # 28 (MediumPurple3)
'#912CEE', # 29 (purple2)
'#8B008B', # 30 (magenta4)
'bisque'] # 31
if style != 'psc':
if style == 'xw':
cols[0] = 'black'
cols[1] = 'bisque'
cols[31] = 'white'
else:
raise ValueError('Unknown style parameter')
try:
c_list = list(c)
res = [cols[normalize(x)] for x in c_list]
except TypeError:
res = cols[normalize(c)]
return res