A Python library for plotting hockey rinks with Matplotlib.

Overview

Hockey Rink

A Python library for plotting hockey rinks with Matplotlib.

Installation

pip install hockey_rink

Current Rinks

The following shows the custom rinks currently available for plotting.

from hockey_rink import NHLRink, IIHFRink, NWHLRink
import matplotlib.pyplot as plt

fig, axs = plt.subplots(1, 3, sharey=True, figsize=(12, 6), gridspec_kw={"width_ratios": [1, 98.4/85, 1]})
nhl_rink = NHLRink(rotation=90)
iihf_rink = IIHFRink(rotation=90)
nwhl_rink = NWHLRink(rotation=90)
axs[0] = nhl_rink.draw(ax=axs[0])
axs[1] = iihf_rink.draw(ax=axs[1])
axs[2] = nwhl_rink.draw(ax=axs[2])

The NWHL logo comes from the NWHL site.

Customization

There is also room for customization. The image at the top was created as follows:

rink = Rink(rotation=45, boards={"length": 150, "width": 150, "radius": 75})

Rinks also allow for additional features to be added. Custom features should inherit from RinkFeature and override the _get_centered_xy method. The draw method can also be overridden if the desired feature can't be drawn with a matplotlib Polygon, though _get_centered_xy should still provide the feature's boundaries. CircularImage provides an example of this by inheriting from RinkCircle.

If a custom feature is to be constrained to only display within the rink, the returned object needs to have a set_clip_path method.

Plots

There are currently wrappers available for the following Matplotlib plots:
- plot
- scatter
- arrow
- hexbin
- pcolormesh (heatmap in Hockey Rink)
- contour
- contourf

If you'd like to bypass the wrappers, you can convert coordinates to the proper scale with convert_xy:

rink = Rink()
x, y = rink.convert_xy(x, y)

When plotting to a partially drawn surface, the plot will be applied to the entire rink, not what's visible. This can be avoided by setting plot_range (or plot_xlim and plot_ylim) in the plotting functions where they're available.

It's also important to realize that the plotting functions only allow arguments to be passed without keywords for the coordinates.
ie) hexbin(x, y, values) will throw an error.

The correct call is hexbin(x, y, values=values)

Examples

Let's look at some NWHL data via the Big Data Cup.

The first game is Minnesota vs Boston, so we'll go with that and do a scatter plot of each team's shots.

from hockey_rink import NWHLRink
import pandas as pd

df = pd.read_csv("https://raw.githubusercontent.com/bigdatacup/Big-Data-Cup-2021/main/hackathon_nwhl.csv")
game_df = df.loc[(df["Home Team"] == "Minnesota Whitecaps") & (df["Away Team"] == "Boston Pride")]
shots = game_df.loc[(game_df.Event.isin(["Shot", "Goal"]))]
boston_shots = shots[shots.Team == "Boston Pride"]
minnesota_shots = shots[shots.Team == "Minnesota Whitecaps"]
rink = NWHLRink(x_shift=100, y_shift=42.5)
ax = rink.draw()
rink.scatter(boston_shots["X Coordinate"], boston_shots["Y Coordinate"])
rink.scatter(200 - minnesota_shots["X Coordinate"], 85 - minnesota_shots["Y Coordinate"])

Extending the example, let's look at all of Boston's passes.

boston_passes = game_df.loc[(game_df.Team == "Boston Pride") & (game_df.Event == "Play")]
ax.clear()
rink.draw()
arrows = rink.arrow(boston_passes["X Coordinate"], boston_passes["Y Coordinate"], 
                    boston_passes["X Coordinate 2"], boston_passes["Y Coordinate 2"], color="yellow")

For some of the other plots, let's look at some NHL shooting percentages.

To mix things up a little, binsize will take different values in each plot and the heatmap won't include shots from below the goal line. We'll also throw in a colorbar for the contour plot.

from hockey_rink import NHLRink
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

pbp = pd.read_csv("https://hockey-data.harryshomer.com/pbp/nhl_pbp20192020.csv.gz", compression="gzip")
pbp["goal"] = (pbp.Event == "GOAL").astype(int)
pbp["x"] = np.abs(pbp.xC)
pbp["y"] = pbp.yC * np.sign(pbp.xC)
shots = pbp.loc[(pbp.Ev_Zone == "Off") & ~pbp.x.isna() & ~pbp.y.isna() & (pbp.Event.isin(["GOAL", "SHOT", "MISS"]))]

fig, axs = plt.subplots(1, 3, figsize=(14, 8))
rink = NHLRink(rotation=270)
for i in range(3):
    rink.draw(ax=axs[i], display_range="ozone")
contour_img = rink.contourf(shots.x, shots.y, values=shots.goal, ax=axs[0], cmap="bwr", 
                            plot_range="ozone", binsize=10, levels=50, statistic="mean")
plt.colorbar(contour_img, ax=axs[0], orientation="horizontal")
rink.heatmap(shots.x, shots.y, values=shots.goal, ax=axs[1], cmap="magma",
             plot_xlim=(25, 89), statistic="mean", vmax=0.2, binsize=3)
rink.hexbin(shots.x, shots.y, values=shots.goal, ax=axs[2], binsize=(8, 12), plot_range="ozone", zorder=25, alpha=0.85)

Inspiration

This project was partly inspired by mplsoccer.

Hopefully, it can lower a barrier for someone looking to get involved in hockey analytics.

Contact

You can find me on twitter @the_bucketless or email me at [email protected] if you'd like to get in touch.

Simulation du problème de Monty Hall avec Python et matplotlib

Le problème de Monty Hall C'est un jeu télévisé où il y a trois portes sur le plateau de jeu. Seule une de ces portes cache un trésor. Il n'y a rien d

ETCHART YANG 1 Jan 06, 2022
Visualize the training curve from the *.csv file (tensorboard format).

Training-Curve-Vis Visualize the training curve from the *.csv file (tensorboard format). Feature Custom labels Curve smoothing Support for multiple c

Luckky 7 Feb 23, 2022
paintable GitHub contribute table

githeart paintable github contribute table how to use: Functions key color select 1,2,3,4,5 clear c drawing mode mode on turn off e print paint matrix

Bahadır Araz 27 Nov 24, 2022
Runtime analysis of code with plotting

Runtime analysis of code with plotting A quick comparison among Python, Cython, and the C languages A Programming Assignment regarding the Programming

Cena Ashoori 2 Dec 24, 2021
The Spectral Diagram (SD) is a new tool for the comparison of time series in the frequency domain

The Spectral Diagram (SD) is a new tool for the comparison of time series in the frequency domain. The SD provides a novel way to display the coherence function, power, amplitude, phase, and skill sc

Mabel 3 Oct 10, 2022
A python visualization of the A* path finding algorithm

A python visualization of the A* path finding algorithm. It allows you to pick your start, end location and make obstacles and then view the process of finding the shortest path. You can also choose

Kimeon 4 Aug 02, 2022
Visualize tensors in a plain Python REPL using Sparklines

Visualize tensors in a plain Python REPL using Sparklines

Shawn Presser 43 Sep 03, 2022
Visualization Data Drug in thailand during 2014 to 2020

Visualization Data Drug in thailand during 2014 to 2020 Data sorce from ข้อมูลเปิดภาครัฐ สำนักงาน ป.ป.ส Inttroducing program Using tkinter module for

Narongkorn 1 Jan 05, 2022
Generate a roam research like Network Graph view from your Notion pages.

Notion Graph View Export Notion pages to a Roam Research like graph view.

Steve Sun 214 Jan 07, 2023
The open-source tool for building high-quality datasets and computer vision models

The open-source tool for building high-quality datasets and computer vision models. Website • Docs • Try it Now • Tutorials • Examples • Blog • Commun

Voxel51 2.4k Jan 07, 2023
nvitop, an interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management

An interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management.

Xuehai Pan 1.3k Jan 02, 2023
Seismic Waveform Inversion Toolbox-1.0

Seismic Waveform Inversion Toolbox (SWIT-1.0)

Haipeng Li 98 Dec 29, 2022
Active Transport Analytics Model (ATAM) is a new strategic transport modelling and data visualization framework for Active Transport as well as emerging micro-mobility modes

{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”) is a new strategic transport modelling and data visualization framew

Peter Stephan 0 Jan 12, 2022
Small project to recursively calculate and plot each successive order of the Hilbert Curve

hilbert-curve Small project to recursively calculate and plot each successive order of the Hilbert Curve. After watching 3Blue1Brown's video on Hilber

Stefan Mejlgaard 2 Nov 15, 2021
Log visualizer for whirl-framework

Lumberjack Log visualizer for whirl-framework Установка pip install -r requirements.txt Как пользоваться python3 lumberjack.py -l путь до лога -o

Vladimir Malinovskii 2 Dec 19, 2022
Extensible, parallel implementations of t-SNE

openTSNE openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction al

Pavlin Poličar 1.1k Jan 03, 2023
This is a super simple visualization toolbox (script) for transformer attention visualization ✌

Trans_attention_vis This is a super simple visualization toolbox (script) for transformer attention visualization ✌ 1. How to prepare your attention m

Mingyu Wang 3 Jul 09, 2022
web application for flight log analysis & review

Flight Review This is a web application for flight log analysis. It allows users to upload ULog flight logs, and analyze them through the browser. It

PX4 Drone Autopilot 145 Dec 20, 2022
Design your own matplotlib stylefile interactively

Tired of playing with font sizes and other matplotlib parameters every time you start a new project or write a new plotting function? Want all you plots have the same style? Use matplotlib configurat

yobi byte 207 Dec 08, 2022
IPython/Jupyter notebook module for Vega and Vega-Lite

IPython Vega IPython/Jupyter notebook module for Vega 5, and Vega-Lite 4. Notebooks with embedded visualizations can be viewed on GitHub and nbviewer.

Vega 335 Nov 29, 2022