Index

A

• Advanced Message Queuing Protocol (AMQP) / The custom ZeroMQ cluster
• Amazon Machine Image (AMI) / Creating a host server on EC2
• analysis of precipitation
  • about / Analysis of precipitation
• analysis of temperature
  • about / Analysis of temperature
• Apache Kafka
  • about / Distributed data
• Apache Spark
  • about / Distributed data
• Apache Storm
  • about / Distributed data
• artist layer
  • about / The current matplotlib architecture, The artist layer
  • Artist class / The artist layer
  • Artist subclasses / The artist layer
  • primitives / Primitives
  • containers / Containers
  • collections / Collections
  • view / A view of the artist layer
• Automobile Data Set
  • about / Subplots

B

• B-trees
  • about / HDF5 and PyTables
• backend layer
  • about / The current matplotlib architecture, The backend layer
  • FigureCanvasBase / FigureCanvasBase
  • RendererBase / RendererBase
  • event / Event
  • visualizing / Visualizing the backend layer
• backends
  • functional categories / The backend layer
  • user interface backends / The backend layer
  • hardcopy backends / The backend layer
• baselines
  • masteringmatplotlib/python / Configuration management
  • masteringmatplotlib/scipy / Configuration management
  • masteringmatplotlib/eros / Configuration management
• big data
  • about / Big data
• big data, on filesystem
  • about / Big data on the filesystem
  • NumPy's memmap function / Big data on the filesystem
  • PyTables / Big data on the filesystem
• Bokeh
  • about / The grammar of graphics, Bokeh, Other visualization tools
  • URL / Other visualization tools
• Bulk Download Application (BDA) / The data source
• Burr distribution / An example problem

C

• Chef / Configuration management
• clustering
  • about / Clustering and parallel programming, More clustering
• clustering, with IPython
  • about / Clustering with IPython, Getting started
  • direct view / The direct view
  • load-balanced view / The load-balanced view
  • parallel magic functions / The parallel magic functions
  • example / An example – estimating the value of π
• coding style / Coding style
• collections
  • about / Collections
• compound event handling
  • about / Compound event handling
  • navigation toolbar / The navigation toolbar
  • specialized events / Specialized events
  • interactive and zooming / Interactive panning and zooming
• compound events
  • about / Compound event handling
• configuration
  • about / Configuration
  • run control / The run control for matplotlib
  • options in IPython / Options in IPython
• containers
  • about / Containers
• controller client
  • about / Clustering with IPython
• customization
  • about / Customization
  • custom style, creating / Creating a custom style
  • subplots / Subplots
  • exploring / Further explorations in customization
• custom ZeroMQ cluster
  • about / The custom ZeroMQ cluster
  • π value, estimating / Estimating the value of π
  • ZeroMQ components, creating / Creating the ZeroMQ components
  • results, working with / Working with the results

D

• data analysis
  • about / Data analysis
  • Pandas / Pandas, SciPy, and Seaborn
  • SciPy / Pandas, SciPy, and Seaborn
  • Seaborn / Pandas, SciPy, and Seaborn
  • dataset, examining / Examining and shaping a dataset
  • dataset, shaping / Examining and shaping a dataset
  • analysis of temperature / Analysis of temperature
  • analysis of precipitation / Analysis of precipitation
• data parallelization
  • about / Clustering and parallel programming
• design patterns
  • about / The grammar of graphics
• distributed data
  • about / Distributed data
  • MapReduce / MapReduce
  • open source options / Open source options
  • example / An example – working with data on EMR
• Docker / Configuration management
• Docker container / Dockerfiles and the Docker images
• Dockerfile / Dockerfiles and the Docker images
• Docker Hub / Dockerfiles and the Docker images
• Docker image / Dockerfiles and the Docker images

E

• Elastic Compute Cloud (EC2) / Types of deployment
• Elastic MapReduce (EMR) / Open source options
• event-based systems
  • about / Event-based systems
• event handling
  • about / Event handling
  • mouse events / Mouse events
  • keyboard events / Keyboard events
  • axes and figure events / Axes and figure events
  • object picking / Object picking
  • compound event handling / Compound event handling
• event loops, matplotlib
  • about / Event loops in matplotlib, The event loop
  • event-based systems / Event-based systems
  • GUI toolkit main loops / GUI toolkit main loops
  • IPython Notebook event loops / IPython Notebook event loops
  • matplotlib event loops / matplotlib event loops
• events
  • about / Event
  • Event class / Event
  • ShowBase / Event
  • TimerBase / Event
• example, AWS and Docker
  • about / An example – AWS and Docker
  • local setup / Getting set up locally
  • requisites, for local setup / Requirements
  • Dockerfiles / Dockerfiles and the Docker images
  • Docker images / Dockerfiles and the Docker images
  • Docker image, extending / Extending a Docker image
  • new image, building / Building a new image
  • deployment, preparing for / Preparing for deployment
  • setup, obtaining on AWS / Getting the setup on AWS
  • task, running / Running the task
• execution flow
  • about / The execution flow
  • overview of script / An overview of the script
  • interactive session / An interactive session

F

• false color image / Defining a workflow
• fast Fourier transform (FFT) module
  • about / The procedural pylab API
• FigureCanvasBase
  • about / FigureCanvasBase

G

• ggplot / The intermediate matplotlib user
• ggplot2
  • about / The grammar of graphics
• Git / Prerequisites for this book
• GNU Compiler Collection (gcc) / Prerequisites for this book
• GNU make / Prerequisites for this book
• GTK+ visualization tool / A brief historical overview of matplotlib
• GUI toolkit main loops
  • about / GUI toolkit main loops

H

• hardcopy backends
  • about / The backend layer
• HDF4
  • about / HDF5 and PyTables
• HDF5
  • about / HDF5 and PyTables
• Hierarchical Data Format (HDF)
  • about / HDF5 and PyTables
• high-level plotting
  • about / High-level plotting
  • historical background / Historical background
  • matplotlib / matplotlib
  • NetworkX / NetworkX
  • Pandas / Pandas
  • grammar of graphics / The grammar of graphics
  • Bokeh / Bokeh
  • ŷhat ggplot / The ŷhat ggplot
  • new styles, in matplotlib / New styles in matplotlib
  • Seaborn / Seaborn
• ŷhat ggplot
  • about / The ŷhat ggplot

I

• interactive backend
  • setting up / Setting up the interactive backend
  • joint plots, with Seaborn / Joint plots with Seaborn
  • scatter plot matrix graphs, with Pandas / Scatter plot matrix graphs with Pandas
• intermediate matplotlib user / The intermediate matplotlib user
• IPython / The intermediate matplotlib user
  • about / An important note on IPython
  • built-in routing schemes / The load-balanced view
• IPython.parallel package
  • IPython engine / Clustering with IPython
  • IPython hub / Clustering with IPython
  • IPython schedulers / Clustering with IPython
  • controller client / Clustering with IPython
• IPython architecture
  • about / Clustering with IPython
• IPython engine
  • about / Clustering with IPython
• IPython hub
  • about / Clustering with IPython
• IPython Notebook event loops
  • about / IPython Notebook event loops
• IPython Notebooks
  • using, with matplotlib / Using IPython Notebooks with matplotlib
• IPython schedulers
  • about / Clustering with IPython

K

• keyboard events
  • handling / Keyboard events
  • key_press_event / Keyboard events
  • key_release_event / Keyboard events
• Kinesis
  • about / Distributed data

L

• Landsat 8 bands / Defining a workflow
• large data, visualizing
  • about / Visualizing large data
  • limits, finding / Finding the limits of matplotlib
  • Agg rendering, with matplotlibrc / Agg rendering with matplotlibrc
  • decimation / Decimation
  • additional techniques / Additional techniques
• large data sources
  • working with / Working with large data sources
  • example problem / An example problem
  • big data, on filesystem / Big data on the filesystem
  • distributed data / Distributed data
• LaTeX
  • about / The pyplot scripting API
• Lawrence Livermore National Laboratory (LLNL) / Estimating the value of π
• linear algebra module
  • about / The procedural pylab API
• Lisp Flavored Erlang (LFE)
  • about / MapReduce

M

• Macsyma / Historical background
• MapReduce
  • about / MapReduce
  • applications / MapReduce
• masked array module
  • about / The procedural pylab API
• matplotlib
  • historical overview / A brief historical overview of matplotlib
  • prerequisites / Prerequisites for this book
  • installing / Installing matplotlib
  • IPython Notebooks, using with / Using IPython Notebooks with matplotlib
  • advanced plots / Advanced plots – a preview
  • original design goals / The original design goals
  • current architecture / The current matplotlib architecture
  • in other frameworks / matplotlib in other frameworks
  • event loops / Event loops in matplotlib
  • event handling / Event handling
• matplotlib 1.4
  • features / What's new in matplotlib 1.4
• matplotlib architecture
  • about / The current matplotlib architecture, The matplotlib architecture as it relates to this book
  • backend layer / The current matplotlib architecture, The backend layer
  • artist layer / The current matplotlib architecture, The artist layer
  • scripting layer / The current matplotlib architecture, The scripting layer
• matplotlib event loops
  • about / matplotlib event loops
• matplotlib in Cloud, use case
  • creating / Making a use case for matplotlib in the Cloud
  • data source / The data source
  • workflow, defining / Defining a workflow
  • technologies, selecting / Choosing technologies
  • configuration management / Configuration management
  • deployment types / Types of deployment
• matplotlib modules
  • about / matplotlib modules
  • filesystem, exploring / Exploring the filesystem
  • imports, exploring visually / Exploring imports visually
  • modulefinder module / ModuleFinder
  • ModGrapher / ModGrapher
• matplotlib object-oriented API
  • about / The matplotlib object-oriented API
  • equations / Equations
  • helper classes / Helper classes
  • Plotter class / The Plotter class
  • jobs, running / Running the jobs
• matplotlib stack
  • supporting components / The supporting components of the matplotlib stack
• matplotlib Transformations Tutorial
  • about / Further explorations in customization
• Mercator map projection
  • about / Further explorations in customization
• Message Passing Interface (MPI)
  • about / Clustering with IPython
• MIT (Massachusetts Institute of Technology) / Historical background
• ModGrapher
  • about / ModGrapher
• modulefinder module
  • about / ModuleFinder
• mouse events
  • handling / Mouse events
  • button_press_event / Mouse events
  • button_release_event / Mouse events
  • scroll_event / Mouse events
  • motion_notify_event / Mouse events
• Multiplexed Information and Computing Service (Multics) / The run control for matplotlib

N

• National Center for Supercomputing Applications (NCSA)
  • about / HDF5 and PyTables
• Near-Infrared (NIR) light / Defining a workflow
• NetworkX
  • about / matplotlib in other frameworks, NetworkX
• NumPy's memmap function
  • about / NumPy's memmap function
• nViZn
  • about / The grammar of graphics

P

• Pandas / The intermediate matplotlib user
  • used, for scatter plot matrix graphs / Scatter plot matrix graphs with Pandas
  • about / Scatter plot matrix graphs with Pandas, matplotlib in other frameworks, Pandas
• Pandas data Series / Analysis of temperature
• parallelization
  • problems / Clustering and parallel programming
• parallel programming
  • about / Clustering and parallel programming
  • data parallelization / Clustering and parallel programming
  • task parallelization / Clustering and parallel programming
• ParaView
  • about / Other visualization tools
  • URL / Other visualization tools
• pattern language
  • about / The grammar of graphics
• PEP 8 / Coding style
• PEP 3107 / Coding style
• primitives
  • about / Primitives
• problems, parallelization
  • N-body problems / Clustering and parallel programming
  • structured grid problems / Clustering and parallel programming
  • Monte Carlo simulation / Clustering and parallel programming
  • combinational logic / Clustering and parallel programming
  • graph traversal / Clustering and parallel programming
  • dynamic programming / Clustering and parallel programming
  • Bayesian networks / Clustering and parallel programming
• procedural pylab API
  • about / The procedural pylab API
  • drawbacks / The procedural pylab API
  • motivating factors / The procedural pylab API
  • interface / The procedural pylab API
• Pub-Sub synchronization / Creating the ZeroMQ components
• Puppet / Configuration management
• PyData
  • about / HDF5 and PyTables
• pylab interface
  • about / The scripting layer
• pyplot interface
  • about / The scripting layer
  • plot() function / The scripting layer
  • title() function / The scripting layer
  • savefig() function / The scripting layer
  • draw() function / The scripting layer
  • gcf() function / The scripting layer
  • gca() function / The scripting layer
  • get_current_fig_manager() function / The scripting layer
  • figure() function / The scripting layer
  • switch_backend() function / The scripting layer
• pyplot scripting API
  • about / The pyplot scripting API
• PyTables
  • about / HDF5 and PyTables
• Python 2 and Python 3
  • syntactical differences / Python 3
• Python 3
  • about / Python 3
• Python Imaging Library (PIL) / Configuration management

Q

• Qt5 backend / What's new in matplotlib 1.4

R

• read-eval-print loop (REPL)
  • about / IPython Notebook event loops
• RendererBase
  • about / RendererBase
• run control, for matplotlib
  • file and directory locations / File and directory locations
  • matplotlibrc file, using / Using the matplotlibrc file
  • values, matplotlibrc file / Using the matplotlibrc file
  • settings, updating dynamically / Updating the settings dynamically

S

• scikit-learn
  • about / matplotlib in other frameworks
• scripting layer
  • about / The current matplotlib architecture, The scripting layer
  • pyplot interface / The scripting layer
  • pylab interface / The scripting layer
• Seaborn / The intermediate matplotlib user
  • about / Joint plots with Seaborn, matplotlib in other frameworks, Seaborn
• Secure Shell (SSH) / Creating a host server on EC2
• setup, on AWS
  • about / Getting the setup on AWS
  • source data, pushing to S3 / Pushing the source data to S3
  • host server, creating on EC2 / Creating a host server on EC2
  • Docker, using on EC2 / Using Docker on EC2
  • reading, with S3 / Reading and writing with S3
  • writing, with S3 / Reading and writing with S3
• Short-Wavelength Infrared (SWIR) light / Defining a workflow
• Singh-Maddala distribution / An example problem
• spline interpolation / Analysis of temperature
• StarCluster / The intermediate matplotlib user
• StarCluster project / More clustering
• Stereonets
  • about / Further explorations in customization
• subplots
  • about / Subplots
  • Pandas, revisiting / Revisiting Pandas
  • individual plots / Individual plots
  • implementing / Bringing everything together
• Superhero Bootstrap theme / Creating a custom style
• supporting components, matplotlib stack
  • about / The supporting components of the matplotlib stack

T

• task, Docker
  • running / Running the task
  • environment variables, setting / Environment variables and Docker
  • Python module, updating / Changes to the Python module
  • execution / Execution
• task parallelization
  • about / Clustering and parallel programming
• Tornado / Event

U

• UCI Machine Learning Repository
  • about / Subplots
• United States Geological Survey (USGS) / Making a use case for matplotlib in the Cloud
• United States Historical Climatology Network (USHCN)
  • about / Examining and shaping a dataset
• user interface backends
  • about / The backend layer

V

• VisIt
  • about / Other visualization tools
  • URL / Other visualization tools
• Vispy
  • about / Other visualization tools
  • URL / Other visualization tools
• visualization tools
  • about / Other visualization tools
  • ParaView / Other visualization tools
  • VisIt / Other visualization tools
  • Bokeh / Other visualization tools
  • Vispy / Other visualization tools

W

• Wulff net
  • about / Further explorations in customization

Z

• ZeroMQ components
  • creating / Creating the ZeroMQ components