![]() ![]() See compress_by_merging, compress_by_deletion, and compress_by_simplification in class Compress for the valid keyword arguments when compression_type = ‘merge’, ‘delete’, and ‘simplify’ respectively.Ĭompressed svg in the directory given by outputfile or in the code directory with the name ‘originalname_compressed.svg’. Kwargs - Depending on the compression type and the pre-selection criteria, additional key word arguments may be required. See optimize_tothe_max in vector_utils.optimize_svg for default name, value pairs. Optimize_options (dict) - if optimize = True, use optimize_options to pass args to vector_utils.optimize_svg. remove redundant nodes, delete id attributes). Optimize (bool) - If True, use package Scour to optimize/sanitize compressed svg (e.g. Selection_tuple (tuple) - If pre_select = True, the selection tuple (‘criteria’, threshold) determines the criteria for selection (‘bboxarea’ for the area of the bounding box of a polygon, or ‘circumference’ for its circumference) and the threshold size (e.g. Pre_select (bool) - If True, will perform the compression only on a subset of the polygons in the svg that are below a certain size threshold. Optional, defaults to ‘originalname_compressed.svg’ The larger the number, the more computation the code will need to perform. curve_fidelity sets the number of coordinates to use to interpolate a curve. those that are simplified) need to first be linearized so as to convert smooth curves into a set of discrete coordinates. Options are ‘delete’ (remove polygons by size), ‘simplify’ (simplify polygons), and ‘merge’ (merge neighboring or overlapping polygons).Ĭurve_fidelity (int) - All polygons affected by compression (e.g. ‘test_vector.svg’Ĭompression_type (str) - how to carry out the compression. compress_by_method API:Ĭonvenience function for 1-step compression of svg files.įilename (str) - Path to svg file to compress, e.g. The function svg_compress.test contains usage examples demonstrating all of the compression methods with compress_by_method. ![]() In addition, a scripting interface to Scour is accessible through the function optimize_svg. Usage of SVGCompress is through the class Compress, or through the convenience function compress_by_method. For non-Windows users, the most convenient way of installing the GEOS framework is through a program such as Canopy (free with academic license) or similar IDLE with an included package manager. If you operate on Windows, pip will install the required files along with Shapely, but this will NOT happen with other operating systems (you will see the error OSError: Could not find library geos_c or load any of its variants when you try to run). SVGCompress depends upon Shapely, which requires the GEOS framework ( ). Requires the following non-standard libraries: Step 2: Install SVGCompress through pip: $ pip install SVGCompress Please make sure you have these installed through whatever means works for you ( Numpy can be installed through pip or through their website, Shapely can be installed through pip if you run a Windows OS or through an application such as Canopy). As a result, I’ve placed these two libraries outside of the install_requires list. SVGCompress has only been tested in Python 2.7ĭepending on your environment, pip may have issues installing Numpy and Shapely (See Important below). Optimizing with Scour - SVG compress provides a scripting interface for the package Scour, which can optimize/sanitize an svg by removing redundant nodes, deleting comments, simplifying node ids and more. Merging adjacent or overlapping shapes - Merging can be accomplished by taking the union of overlapping polygons or through the construction of a minimum convex hull. Simplifying shapes - Reduce the complexity of your polygons using the Ramer–Douglas–Peucker algorithm. The size threshold can be based on polygon area or circumference. Removing tiny polygons - Reduce the number of polygons in your image by removing those below a small threshold size. Have you ever tried to output a plot in vector format (pdf, svg, eps, etc.) and been surprised that your file weighs 10 or 20MB? Needed to submit a vector figure for publication but ran up against the file size limit? Before you try to get away with the old standby of embedding a raster image in your vector and hoping the journal doesn’t notice, try SVGCompress! SVGCompress can help pare down your file size by: SVGcompress is a pure python module for simplifying/compressing svg (Scalable Vector Graphics) files.
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