Esempio n. 1
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def load_timeseries_graph(dir_):

    from pymira import spatialgraph

    graph = []
    time = []

    for file in os.listdir(dir_):
        if file.endswith('.am'):
            #print(os.path.join("/mydir", file))
            g = spatialgraph.SpatialGraph()
            try:
                g.read(os.path.join(dir_, file))
                graph.append(g)
                t = np.float(g.get_parameter_value('Time'))
                time.append(t)
            except Exception as e:
                print(e)

    time = np.asarray(time)
    graph = np.asarray(graph)
    srtInds = time.argsort()
    time = time[srtInds]
    graph = graph[srtInds]

    return graph, time
Esempio n. 2
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def main():
    #dir_ = 'C:\\Users\\simon\\Dropbox\\Mesentery\\'
    #f = dir_ + 'Flow2AmiraPressure.am'
    # dir_ = 'C:\\Users\\simon\\Dropbox\\160113_paul_simulation_results\\LS147T\\1\\'
    # #dir_ = 'C:\\Users\\simon\\Dropbox\\160113_paul_simulation_results\\LS147T - Post-VDA\\1\\'
    
    # #dir_ = 'C:\\Users\\simon\\Dropbox\\160113_paul_simulation_results\\SW1222\\1\\'
    
    # #dir_ = 'C:\\Users\\simon\\Dropbox\\160113_paul_simulation_results\\SW1222\\1\\'
    # #f = dir_+'spatialGraph_RIN.am'
    
    #dir_ = r"C:\Users\simon\Dropbox\VDA_1_lectin\Control\SW#1"
    #f = dir_+r'\SW1_spatialGraph_scaled.am'
    # pixsize = 6.98
    # dir_ = r"G:\OPT\2015.11.VDA_1 study\VDA Colorectal cancer\Control\LS\LS#2"
    # f = dir_+r'\LS2_bg_removed_frangi_response_skeletonised_with_radius.SptGraph.am'
    # pixsize = 8.21
    # #dir_ = r"G:\OPT\2015.11.VDA_1 study\VDA Colorectal cancer\Control\LS\LS#4"
    # #pixsize = 8.21
    
    #dirs = [r"C:\Users\simon\Dropbox\VDA_1_lectin\Control\SW#2",
    #        r"C:\Users\simon\Dropbox\VDA_1_lectin\Control\SW#3"]
    #fs = [r'\SW2_spatialGraph_scaled.am',
    #      r'\SW3_spatialGraph_scaled.am']
    dirs = [r'C:\Users\simon\Dropbox\VDA_1_lectin\Treated\LS#1']
    fs = [r'\LS1t_vessel_seg_frangi_response_skel_with_radius.am']
    pixsize = [4.78]
          
    for i,dir_ in enumerate(dirs):
        
        f = fs[i]
        pix = pixsize[i]
          
        from pymira import spatialgraph
        graph = spatialgraph.SpatialGraph()
        print('Reading graph...')
        graph.read(dir_+f)
        print('Graph read')
       
        if pix is not None:
            ofile = dir_+'\spatialGraph_scaled.am'
            graph.rescale_coordinates(pix,pix,pix)
            graph.rescale_radius(pix,ofile=ofile)
        
        stats = Statistics(graph,path=dir_)    
        stats.do_stats(path=dir_)
Esempio n. 3
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# -*- coding: utf-8 -*-
"""
Created on Wed May 31 14:42:15 2017

@author: simon
"""

from pymira import spatialgraph
import os

dir_ = r'C:\Users\simon\Dropbox\Ben Vessel Networks'
f = os.path.join(dir_, 'C2M3_vessels.am')

print 'Reading graph: {}'.format(f)
graph = spatialgraph.SpatialGraph()
graph.read(f)
print 'Graph read'

editor = spatialgraph.Editor()
graph = editor.largest_graph(graph)

ofile = os.path.join(dir_, 'C2M3_vessels_largest_network.am')
graph.write(ofile)
Esempio n. 4
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def main():
    plt.close('all')

    from pymira import spatialgraph
    dir_ = 'C:\\Users\\simon\\Dropbox\\Mesentery\\'
    f = dir_ + 'ct_output.am'
    graph = spatialgraph.SpatialGraph()
    print('Reading graph...')
    graph.read(f)
    print('Graph read')

    points = graph.get_data('EdgePointCoordinates')
    npoints = points.shape[0]
    nEdgePoint = graph.get_data('NumEdgePoints')
    edgePointIndex = np.zeros(npoints, dtype='int')

    offset = 0
    edgeCount = 0
    for npCur in nEdgePoint:
        edgePointIndex[offset:offset + npCur] = edgeCount
        edgeCount += 1
        offset += npCur

    assert offset == npoints

    concFieldInds = [
        i for i, x in enumerate(graph.fieldNames) if 'Concentration' in x
    ]
    concFields = [graph.fieldNames[i] for i in concFieldInds]
    time = np.asarray(
        [float(x.replace('Concentration_', '')) for x in concFields])

    nt = len(time)
    npoint = points.shape[0]

    conc = np.zeros((nt, npoint), dtype='float')
    for ci, concField in enumerate(concFieldInds):
        field = graph.fields[concField]
        if 'data' in field:
            conc[ci, :] = field['data']
        else:
            conc[ci, :] = conc[ci - 1, :]
            print(('Data missing: {}'.format(concFields[ci])))

    #nodes = [[10.,10.,10.],
    #         [10.,20.,10.],
    #         [30.,30.,10.]]

    #import pdb
    #pdb.set_trace()

    jump = 1
    lim = -1  #jump*50
    time = time[0:lim:jump]
    conc = conc[0:lim:jump, :]

    #conc = conc[:,0:100]
    #points = points[0:100,:]
    #edgePointIndex = edgePointIndex[0:100]

    inter = Interstitium()

    try:
        inter.interstitial_diffusion(points, edgePointIndex, conc, time)
    except KeyboardInterrupt:
        print('Keyboard interrupt')
        #inter.normalise()
        #pass
    #import pdb
    #pdb.set_trace()
    #inter.display_grid(last=False)
    inter.save_grid(dir_)
Esempio n. 5
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              nodes[1],
              nodes[2],

              nodes[2],
              nodes[3],

              nodes[2],
              nodes[4] 
              ]
edgePoints = np.asarray(edgePoints,dtype='float')
              
radii = np.zeros(edgePoints.shape[0]) + 0.05
              
nedgepoints = [6,
               2,
               2,
               2]
nedgepoints = np.asarray(nedgepoints,dtype='int')               
               
graph = spatialgraph.SpatialGraph(initialise=True,scalars=['Radii'])
graph.set_definition_size('VERTEX',nodes.shape[0])
graph.set_definition_size('EDGE',edgeConn.shape[0])
graph.set_definition_size('POINT',edgePoints.shape[0])
graph.set_data(nodes,name='VertexCoordinates')
graph.set_data(edgeConn,name='EdgeConnectivity')
graph.set_data(nedgepoints,name='NumEdgePoints')
graph.set_data(edgePoints,name='EdgePointCoordinates')
graph.set_data(radii,name='Radii')
ofile = 'C:\\Anaconda2\\Lib\\site-packages\\pymira\\test_graph.am'
graph.write(ofile)