blaylockbk

def timer(func):
    """
    A decorator to time a function execution time.

    Based on https://twitter.com/pybites/status/1387691670658068481?s=20

    Parameters
    ----------
    func : function
        The function you wish to time.

blaylockbk

import os
from pathlib import Path
import warnings

# Create a new method for Path objects called `expand`, which fully 
# expands the Path object with the given environment variables.

def _expand(self, *, strict=True):
    """
    Fully expand and resolve the Path with the given environment variables.

blaylockbk

def add_fig_letters(axes, offset=.07, facecolor='#f9ecd2', **kwargs):
    """
    Add a figure letter to top-left corner for all axes
    
    Like is done in a publication figure, all axes are labeled with a
    letter so individual axes can be referred to from the text.

    Paramters
    ---------
    axes : list

blaylockbk

# Add this to your ~/.ipython/profile_default/ipython_config.py
# file so that when you copy a matplotlib plot from JupyterLab 
# it will not copy the transparency.

c = get_config()
c.InlineBackend.print_figure_kwargs={'facecolor' : "w"}

blaylockbk

try:
    (do something)
except Exception as e:
    print(f"WARNING: {e}")

blaylockbk

import numpy as np
import xarray as xr

def to_180(lon):
    """
    Wrap longitude from degrees [0, 360] to degrees [-180, 180].

    An alternative method is
        lon[lon>180] -= 360

blaylockbk

a = np.arange(0, 3*np.pi, .1)

loops = range(5)

# Choose a colormap and create a list of colors with same length as our loop.
cmap = plt.get_cmap("YlGnBu")
colors = [cmap(i) for i in np.linspace(.15, .85, len(loops))]


fig, (ax1, ax2) = plt.subplots(1,2)

blaylockbk

## Based on https://stackoverflow.com/a/46129367/2383070

import os
import contextlib
 
def test_print(a):
    print(f'2 * {a} =')
    return 2*a
 
# Do not print the print statement in the function:

blaylockbk

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

coins = ['penny', 'nickle', 'dime', 'quarter']
worth = np.array([.01, .05, .10, .25])

values = [worth*i for i in range(1,6)]

blaylockbk

# I like this example from the matplotlib cheatsheets
# https://github.com/matplotlib/cheatsheets

X = np.random.normal(-1, 1, 10_000)
Y = np.random.normal(-1, 1, 10_000)
plt.scatter(X, Y, 50, color="0.1", lw=2)
plt.scatter(X, Y, 50, color="1.0", lw=0)
plt.scatter(X, Y, 40, 'C1', lw=0, alpha=.1)
plt.gca().set_facecolor('.95')