Metadata-Version: 1.1
Name: pybimstab
Version: 0.1.2
Summary: Application software to evaluate the stability of slopes made of Blocks-In-Matrix materials
Home-page: https://github.com/eamontoyaa/pybimstab
Author: Exneyder A. Montoya-Araque & Ludger O. Suarez-Burgoa
Author-email: eamontoyaa@gmail.com
License: BSD 2-Clause License
Description: =========
        pyBIMstab
        =========
        
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        ``pybimstab`` is an application software in **Python 3** to evaluate the factor
        of safety against sliding of slopes made of Blocks-In-Matrix (BIM) materials. 
        
        The assessment is donde by using the limit equilibrium method through the
        General Limit Equilibrium (GLE) method of
        `Fredlund & Krahn (1977) <https://doi.org/10.1139/t77-045>`_.
        
        The slip surface has a tortuous geometry and is optimally found by using the
        A-star algorithm proposed by 
        `Hart, Nilsson & Raphael (1968) <https://doi.org/10.1109/TSSC.1968.300136>`_.
        
        The following plots are the final outcome of two different analysis:
        
        **Homogeneus slope**
        
        .. figure:: https://rawgit.com/eamontoyaa/pybimstab/master/examples/figures/coverPlot1.svg
                :alt: Outcome plot example1
        
        **Slope made of BIM material**
        
        .. figure:: https://rawgit.com/eamontoyaa/pybimstab/master/examples/figures/coverPlot2.svg
                :alt: Outcome plot example2
        
        
        Features
        --------
        
        * `Documentation <https://pybimstab.readthedocs.io>`_
        * `PyPI <https://pypi.org/project/pybimstab>`_
        * `GitHub <https://github.com/eamontoyaa/pybimstab>`_
        * Open source and free software: `BSD-2-Clause <https://opensource.org/licenses/BSD-2-Clause>`_.
        
        
        Requirements
        ------------
        
        The code was written in Python 3. The packages `numpy <http://www.numpy.org/>`_,
        `scipy <https://www.scipy.org/>`_, `matplotlib <https://matplotlib.org/>`_
        and `shapely <https://pypi.org/project/Shapely/>`_ are
        required for using ``pybimstab``. All of them are
        downloadable from the PyPI repository by opening a terminal and typing the
        following code lines:
        
        
        ::
        
            pip install numpy
            pip install scipy
            pip install matplotlib
            pip install shapely
        
        
        Installation
        ------------
        
        
        To install ``pybimstab`` open a terminal and type:
        
        ::
        
            pip install pybimstab
        
        
        Example
        -------
        
        To produce the plot shown above execute the following script
        
        ::
        
            from numpy import array
            from pybimstab.slope import NaturalSlope
            from pybimstab.watertable import WaterTable
            from pybimstab.bim import BlocksInMatrix
            from pybimstab.slipsurface import CircularSurface, TortuousSurface
            from pybimstab.slices import MaterialParameters, Slices
            from pybimstab.slopestabl import SlopeStabl
            terrainCoords = array(
                [[-2.49, 0.1, 1.7, 3.89, 5.9, 8.12, 9.87, 13.29, 20.29,
                  21.43, 22.28, 23.48, 24.65, 25.17],
                 [18.16, 17.88, 17.28, 15.73, 14.31, 13.58, 13, 3.61, 3.61,
                  3.32, 2.71, 2.23, 1.21, 0.25]])
            slope = NaturalSlope(terrainCoords)
            bim = BlocksInMatrix(slopeCoords=slope.coords, blockProp=0.25,
                                 tileSize=0.4, seed=12345)
            watertabDepths = array([[0, 5, 10, 15],
                                    [8, 7, 3, 0]])
            watertable = WaterTable(slopeCoords=slope.coords,
                                    watertabDepths=watertabDepths,
                                    smoothFactor=3)
            preferredPath = CircularSurface(
                slopeCoords=slope.coords, dist1=5, dist2=15.78, radius=20)
            surface = TortuousSurface(
                bim, dist1=4, dist2=15.78, heuristic='euclidean',
                reverseLeft=False, reverseUp=False, smoothFactor=2,
                preferredPath=preferredPath.coords, prefPathFact=2)
            material = MaterialParameters(
                cohesion=15, frictAngle=23, unitWeight=17,
                blocksUnitWeight=21, wtUnitWeight=9.8)
            slices = Slices(
                material=material, slipSurfCoords=surface.coords,
                slopeCoords=slope.coords, numSlices=15,
                watertabCoords=watertable.coords, bim=bim)
            stabAnalysis = SlopeStabl(slices, seedFS=1, Kh=0, maxLambda=1)
            fig = stabAnalysis.plot()
        
        
        References
        ----------
        D. G. Fredlund and J. Krahn. Comparison of slope stability methods of analysis.
        Canadian Geotechnical Journal, 14(3)(3):429–439, 1977.
        
        P. Hart, N. Nilsson, and B. Raphael. A formal basis for the heuristic
        determination of minimum cost path. IEEE Transactions of Systems Science and
        Cybernetics, ssc-4(2):100–107, 1968.
        
        
        
        =======
        History
        =======
        
        0.1.0 (2018-07-15)
        ------------------
        
        * First release on PyPI.
        
        0.1.1 (2018-07-22)
        ------------------
        
        * Solving some issues related to the definition of the slices structure.
        
        0.1.2 (2018-08-04)
        ------------------
        
        * Adjusting the interpolations in the convergence plot and appending a parameter to control the number of lambda values.
        
Keywords: slope stability,GLE,bimsoil,bimrock,tortuosity,A-star,Python,application software
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
