What’s new in Matlab 2017a
Desktop
- Live Editor: Edit a figure interactively including title, labels, legend, and other annotations
- Live Editor: Get suggestions for mistyped commands and variables
- Live Editor: Copy live script outputs to other applications
- Live Editor: Hover over variables to see their current value
- Add-On Explorer: Discover and install File Exchange submissions hosted on GitHub in Add-On Explorer
- MATLAB Online: Use MATLAB through your web browser for teaching, learning, and convenient, lightweight access
- Startup Folder Behavior Changes: Set initial working folder using new options and behaviors
Language and Programming
- string Arrays: Create string arrays using double quotes
- String Functions: Return character arrays or cell arrays instead of string arrays
- missing Function: Assign missing values in core data types, including double, datetime, categorical, and string arrays
- issortedrows Function: Determine if matrix and table rows are sorted
- sort and sortrows Functions: Specify options for sorting complex numbers and placing missing elements
- issorted Function: Query sort order with monotonic, strictly monotonic, strictly ascending, and strictly descending options
- head and tail Functions: Return top or bottom rows of table or timetable
- table Data Containers: Use row labels when performing join, sort, and grouping operations
- Functionality being removed or changed
Graphics
- heatmap Function: Visualize table or matrix data as a heatmap
- legend Function: Create legends that update when data is added to or removed from the axes
- Categorical Plotting: Use categorical data in common plotting functions and customize axes with categorical rulers
- histogram Function: Plot histograms of datetime and duration data
- histogram Function: Sort categorical bins by bar height, and limit the number of bins displayed
- scatter Function: Create scatter plots of datetime and duration data
- Scatter Plots: Create scatter plots with varying marker sizes faster
- parula Colormap: Create plots with enhanced colors
- Functionality being removed or changed
Data Import and Export
- datastore and tabularTextDatastore Functions: Automatically detect and return date and time data in text files
- datastore Function: Work with data in Amazon S3 cloud storage
- Import Tool: Import strings and categorical arrays interactively
- detectImportOptions Function: Control import properties of fixed-width text files
- RESTful web services: Support for PUT and DELETE HTTP methods in webread, webwrite, and websave
- save Function: Save workspace variables to a MAT-file with or without compression
- writetable Function: Select preferred character encoding when writing to a file
- NetCDF Functions: Create variable names and attributes containing non-ASCII characters
- Webcam Support Package: GStreamer Upgrade on Linux
- jsondecode converts JSON null values in numeric arrays to NaN
- load and fopen Functions: Use the file separator character ('\') preceding a filename to indicate that the file is in the root folder
- Functionality being removed or changed
Data Analysis
- tall Arrays: Operate on tall arrays with more functions, including ismember, sort, conv, and moving statistics functions
- tall Arrays: Index tall arrays using sorted indices
- tall Arrays: Work with out-of-memory, time-stamped data in a timetable
- isoutlier and filloutliers Functions: Detect and replace outliers in an array or table
- smoothdata Function: Smooth noisy data in an array or table with filtering or local regression
- summary Function: Calculate summary statistics and variable information in tables and timetables
- histcounts Function: Bin datetime and duration data
- movmad and movprod Functions: Compute moving median absolute deviation and moving product of an array
- bounds Function: Simultaneously determine the smallest and largest elements of an array
- fillmissing Function: Replace missing data in an array or table using moving mean or moving median option
- Moving Statistics Functions: Supply sample points for time-stamped and nonuniform data in moving statistics functions, such as movmean
- prod and cumprod Functions: Ignore NaNs using 'omitnan'
- Functionality being removed or changed
App Building
- App Designer: Learn to build apps using an interactive tutorial
- App Designer: Zoom and pan plots
- App Designer: Configure columns of a table to automatically fill the entire width of the table
- App Designer: Manage common design-time settings using the Preferences dialog box
- App Designer: Include comet, graph, and digraph visualizations in apps
- App Designer: Write ButtonDownFcn callbacks for graphics objects displayed in UI axes
- App Designer: Edit table column headings directly in the canvas
- App Designer: Disable automatic resize behavior when writing SizeChangedFcn callbacks
Performance
- Execution Engine: Improved performance for setting MATLAB object properties
- save Function: Save MAT v7.3 files without compression for improved performance on some storage devices
- memoize Function: Cache results of a function to avoid rerunning when called with the same inputs
- Scripts: Improved performance of scripts with lower script overhead
- try, catch Block: Improved performance of try blocks with lower execution overhead
- App Designer: Load apps faster
- Mathematics Functions: Various performance improvements
Hardware Support
- Arduino: Read from quadrature encoders
- Arduino: Wirelessly connect to Arduino MKR1000 board over WiFi
Advanced Software Development
- Class matlab.lang.OnOffSwitchState: Represent on and off as logical values
- Object Properties: Validate object property values by their type, size, shape, or other parameters
- Validation Functions: Validate that values meet specific criteria by calling the appropriate function
- Mocking Framework: Isolate a portion of a system to test by imitating behavior of dependent components
- Unit Testing Framework: Generate screenshots and figures during testing with ScreenshotDiagnostic and FigureDiagnostic
- Unit Testing Framework: Capture screenshots and figures generated during tests using TestReportPlugin
- Unit Testing Framework: Control runtests function with debug, strict, and verbosity options
- Unit Testing Framework: Select tests by procedure name
- Unit Testing Framework: Comparator for MATLAB tables
- Performance Testing Framework: View statistics from test measurements with the sampleSummary method
- Performance Testing Framework: Apply a function across test measurements with the samplefun method
- Source Control Integration: Use Git Pull to fetch and merge in one step
- MEX builds with 64-Bit API by default
- MEX files and shared libraries: Diagnostic information displayed for failure to load
- Java: Supports string data type
- Python: Supports string data type
- Python Version 3.3: Support discontinued
- MATLAB ships with ActiveState Perl version 5.24 on Windows platforms
- Compiler support changed for building MEX files and standalone MATLAB engine and MAT-file applications
- Functionality being removed or changed
System Requirements - Release 2017a
Windows
Note: Support for Windows 8 will be discontinued as of R2017b; however, support will continue for Windows 8.1.64-Bit MATLAB, Simulink and Polyspace Product Families | ||||
Operating Systems | Processors | Disk Space | RAM | Graphics |
---|---|---|---|---|
Windows 10 Windows 8.1 Windows 8 Windows 7 Service Pack 1 Windows Server 2016 Windows Server 2012 R2 Windows Server 2012 Windows Server 2008 R2 Service Pack 1 | Any Intel or AMD x86-64 processor AVX2 instruction set support is recommended With Polyspace, 4 cores is recommended | 2 GB for MATLAB only, 4–6 GB for a typical installation | 2 GB With Simulink, 4 GB is required With Polyspace, 4 GB per core is recommended | No specific graphics card is required. Hardware accelerated graphics card supporting OpenGL 3.3 with 1GB GPU memory is recommended. |
Linux
Note:- Ubuntu 16.10 is supported as of R2017a.
- Debian 7 is not supported as of R2017a.
64-Bit MATLAB, Simulink and Polyspace Product Families | ||||
Operating Systems | Processors | Disk Space | RAM | Graphics |
---|---|---|---|---|
Qualified distributions*: Ubuntu 14.04 LTS, 16.04 LTS, and 16.10 Red Hat Enterprise Linux 6 and 7** SUSE Linux Enterprise Desktop 12*** Debian 8.x | Any Intel or AMD x86-64 processor AVX2 instruction set support is recommended With Polyspace, 4 cores is recommended | 2.2 GB for MATLAB only, 4–6 GB for a typical installation | 2 GB With Simulink, 4 GB is required With Polyspace, 4 GB per core is recommended | No specific graphics card is required. Hardware accelerated graphics card supporting OpenGL 3.3 with 1GB GPU memory is recommended. Use of vendor supplied proprietary drivers is strongly recommended. |
kernel version 2.6 or later and glibc version 2.12 or later can successfully run MathWorks products, but MathWorks will be in a limited position
to provide technical support for those distributions.
** MathWorks follows Red Hat’s support policy for minor versions of RHEL. As of MATLAB R2017a, Red Hat does not support RHEL versions 6.6
and older. Refer to the Red Hat web site for additional information.
*** MathWorks follows SUSE’s support policy for minor versions of Enterprise Desktop. As of MATLAB R2017a, SUSE supports SLED 12 SP1 and
later. Refer to the SUSE web site for additional information
Mac
Note: Support for macOS Yosemite (10.10) will be discontinued as of R2017b.64-Bit MATLAB, Simulink and Polyspace Product Families | ||||
Operating Systems | Processors | Disk Space | RAM | Graphics |
---|---|---|---|---|
macOS Sierra (10.12) macOS El Capitan (10.11) macOS Yosemite (10.10) | Any Intel or AMD x86-64 processor AVX2 instruction set support is recommended With Polyspace, 4 cores is recommended | 2.5 GB for MATLAB only, 4–6 GB for a typical installation | 2 GB With Simulink, 4 GB is required With Polyspace, 4 GB per core is recommended | No specific graphics card is required. Hardware accelerated graphics card supporting OpenGL 3.3 with 1GB GPU memory is recommended. |
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