Metadata-Version: 1.1
Name: swmmio
Version: 0.1.3
Summary: Tools for reading, writing, visualizing, and versioning EPA SWMM5 models.
Home-page: https://github.com/aerispaha/swmmio
Author: Adam Erispaha
Author-email: aerispaha@gmail.com
License: MIT License
Description: SWMMIO
        ======
        
        SWMMIO is a set of python tools for interacting with and visualizing
        results from EPA Stormwater Management Model input and output files
        (.inp and .rpt). These tools are being developed specifically for the
        application of flood risk management.
        
        Prerequisites
        ~~~~~~~~~~~~~
        
        | SWMMIO functions by processing .inp and .rpt (input and report) files
          produced by EPA SWMM5.
        | In order for these tools for work properly, an associated pair of .inp
          and .rpt files should be located within the same
        | directory. SWMMIO (I think) relies only on pre-installed Python 2.7
          libraries. To optionally show basemap data, arcpy is required.
        | Images2Gif was copied within this project and one line was edited to
          work herein (I need to dig to remember which).
        
        Usage:
        ~~~~~~
        
        In IDLE, add the directory holding the SWMMIO python scripts to your
        sys.path variable and import the modules:
        
        ::
        
            import sys
            sys.path.append('/path/to/swmmio directory')
            import swmmio
            import swmm_graphics as sg
            from swmmio.utils import swmm_utils as su
            import swmm_compare as scomp
        
        Instantiate some model objects by pointing SWMMIO to a directory
        containing a model’s .inp and .rpt files:
        
        ::
        
            model_a = swmmio.model('/path/to/directory with swmm files')
            model_b = swmmio.model('/path/to/other/directory with swmm files')
        
        | Create an image (.png) visualization of the model. By default, pipe
          stress and node flood duration is visualized.
        | Many options can be passed to control how and what data is visualized.
        
        ::
        
            sg.drawModel(model_a)
        
        Create an animated gif of a model’s response to a storm. Again many
        options can be passed.
        
        ::
        
            sg.animateModel(model_a, startDtime='JAN-01-1990 11:59:00', endDtime='JAN-01-1990 12:01:00')
        
        | Generate a comparison report showing changes in node flooding between
          two models. Presumably, the models
        | will represent a baseline model compared to a flood mitigation
          alternative.
        
        ::
        
            scomp.comparisonReport(model_a, model_b)
        
        Create visualization of the impact of a given alternative with respect
        to the baseline conditions.
        
        ::
        
            scomp.drawModelComparison(model_a, model_b, options={'conduitSymb':'compare_hgl'})
        
        Export organized data collected from the inp and rpt files as follows.
        By default, node data is returned; optionally, conduit data can be
        returned. As in all methods, a bounding box (bbox) option can be passed
        to spatially filter data.
        
        ::
        
            model_a.exportData()
            model_a.exportData(type='conduit')
        
            #filter data within a bounding box
            boundingBox = ((2685990, 219185), (2692678, 223831))
            model_a.exportData(bbox=boundingBox)
        
        Acknowledgments
        ~~~~~~~~~~~~~~~
        
        For use in generating animations of SWMM models, thanks to
        `images2gif.py`_
        
        .. _images2gif.py: https://gist.github.com/jonschoning/7216290
        
Platform: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
