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######################################################## |
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# |
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# Copyright (c) 2009 by University of Queensland |
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# Earth Systems Science Computational Center (ESSCC) |
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# http://www.uq.edu.au/esscc |
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# |
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# Primary Business: Queensland, Australia |
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# Licensed under the Open Software License version 3.0 |
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# http://www.opensource.org/licenses/osl-3.0.php |
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# |
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######################################################## |
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|
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__copyright__="""Copyright (c) 2009 by University of Queensland |
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Earth Systems Science Computational Center (ESSCC) |
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http://www.uq.edu.au/esscc |
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Primary Business: Queensland, Australia""" |
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__license__="""Licensed under the Open Software License version 3.0 |
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http://www.opensource.org/licenses/osl-3.0.php""" |
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__url__="https://launchpad.net/escript-finley" |
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|
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""" |
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Additional routines using matplotlib for cookbook examples. |
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Author: Antony Hallam antony.hallam@uqconnect.edu.au |
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""" |
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|
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#Please ensure that if you need to use the agg back-end that you have chosen it before |
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#calling functions in this file |
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|
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import numpy as np |
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# Calculate the location of quivers for a matplotlib plot |
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# quivshape :: [x,y] :: number of quivers in x and y direction |
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# lenxax :: length of model along x |
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# lenyax :: length of model along y |
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# qu :: gradient of escript solution ie grad(T) |
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def toQuivLocs(quivshape,lenxax,lenyax,qu): |
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numquiv = quivshape[0]*quivshape[1] # total number of quivers |
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dx = lenxax/quivshape[0]+1. # quiver x spacing |
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dy = lenyax/quivshape[1]+1. # quiver y spacing |
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qulocs=np.zeros([numquiv,2],float) # memory for quiver locations |
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# fill qulocs |
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for i in range(0,quivshape[0]-1): |
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for j in range(0,quivshape[1]-1): |
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qulocs[i*quivshape[0]+j,:] = [dx+dx*i,dy+dy*j] |
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# retreive values for quivers direction and shape from qu |
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quL = Locator(qu.getFunctionSpace(),qulocs.tolist()) |
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qu = quL(qu) #array of dx,dy for quivers |
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qu = np.array(qu) #turn into a numpy array |
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qulocs = quL.getX() #returns actual locations from data |
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qulocs = np.array(qulocs) #turn into a numpy array |
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return qu,qulocs |
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# Extract the X and Y coordinates of an array |
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# coords :: escript coordiantes from .getX function |
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def toXYTuple(coords): |
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coords = np.array(coords.toListOfTuples()) #convert to Tuple |
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coordX = coords[:,0]; coordY = coords[:,1] #X and Y components. |
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return coordX,coordY |
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def toRegGrid(grid,domain,newx,newy,width,depth): |
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import pylab as pl |
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oldspacecoords=domain.getX() |
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gridT = grid.toListOfTuples(scalarastuple=False) |
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cxy = Data(oldspacecoords, grid.getFunctionSpace()) |
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cX, cY = toXYTuple(cxy) |
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xi = np.linspace(0.0,width,newx) |
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yi = np.linspace(depth,0.0,newy) |
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# grid the data. |
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zi = pl.matplotlib.mlab.griddata(cX,cY,gridT,xi,yi) |
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return xi,yi,zi |
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|
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def gradtoRegGrid(grid,domain,newx,newy,width,depth,dim): |
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import pylab as pl |
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cxy = grid.getFunctionSpace().getX() |
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gridT = grid.toListOfTuples()#(scalarastuple=False) |
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#cxy = Data(oldspacecoords, grid.getFunctionSpace()) |
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cX, cY = toXYTuple(cxy) |
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xi = np.linspace(0.0,width,newx) |
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yi = np.linspace(depth,0.0,newy) |
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gridT = np.array(gridT) |
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gridT = gridT[:,dim] |
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# grid the data. |
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|
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zi = pl.matplotlib.mlab.griddata(cX,cY,gridT,xi,yi) |
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return xi,yi,zi |
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