Question

我有一组表示一组节点的数据，每个节点都与一个值相关联（由图像中的颜色表示）。我想要实现的是有选择地改变这些价值观。

网格表示多孔系统（例如岩石）模型。我的系统中的压力在节点处指定。我的输入已经包含了归因于每个节点的压力，但我希望能够仅为特定节点（位于多边形内部的压力）重新分配压力的初始条件。所以我的节点的权重是该节点的压力。

我实际上想要定义一个多边形，并将值赋值给每个顶点（将其视为一个权重），并使用顶点的权重和从顶点到每个节点的距离INSIDE多边形以更正值对于那个节点。

这就是我的输出：

我正在研究一种算法，它采用[x，y，z]形式的一组值，另一种形式[value，value，value，value]。两者都有相同的行数。 e.i，第一个输入中的行是节点的位置，第二个中的行是与该节点关联的值。

我制作了一个算法，该算法接受一组形成多边形的点和一组与该多边形的每个顶点相对应的权重。

然后我扫描合并的输入并替换找到多边形内的任何节点的值。该值由此post中的算法定义。如果节点不在多边形内，则保留其值。

然后我将所有new_values写入文件。

我担心的是，如果没有MemoryError，我将无法处理几百万个节点的大量输入。目前处理9239行输入，需要9秒钟。

这是我的代码：

# for PIP problem
import shapely.geometry as shapely
# for plot
import matplotlib.pyplot as plt
# for handling data
import csv
import itertools
# for timing
import time

#=================================================================================
                # POINT IN POLYGONE PROBLEM
#=================================================================================

class MyPoly(shapely.Polygon):
    def __init__(self,points):
        closed_path = list(points)+[points[0]]
        super(MyPoly,self).__init__(closed_path)
        self.points = closed_path
        self.points_shapely = [shapely.Point(p[0],p[1]) for p in closed_path]

def convert_to_shapely_points_and_poly(poly,points):
    poly_shapely = MyPoly(poly)
    points_shapely = (shapely.Point(p[0],p[1]) for p in points)
    return poly_shapely,points_shapely    


def isBetween(a, b, c): #is c between a and b ?
    crossproduct = (c.y - a.y) * (b.x - a.x) - (c.x - a.x) * (b.y - a.y)
    if abs(crossproduct) > 0.01 : return False   # (or != 0 if using integers)

    dotproduct = (c.x - a.x) * (b.x - a.x) + (c.y - a.y)*(b.y - a.y)
    if dotproduct < 0 : return False

    squaredlengthba = (b.x - a.x)*(b.x - a.x) + (b.y - a.y)*(b.y - a.y)
    if dotproduct > squaredlengthba: return False

    return True

def get_edges(poly):
    # get edges
    edges = []
    for i in range(len(poly.points)-1):
        t = [poly.points_shapely[i],poly.points_shapely[i+1]]
        edges.append(t)
    return edges


def inPoly(poly,point, inclusive):
    if poly.contains(point) == True:
        return 1
    elif inclusive:
        for e in get_edges(poly):
            if isBetween(e[0],e[1],point):
                return 1
    return 0

def plot(poly_init,points_init, inclusive = True):
    #convert to shapely poly and points
    poly,points = convert_to_shapely_points_and_poly(poly_init,points_init)

    #plot polygon
    plt.plot(*zip(*poly.points))

    #plot points
    xs,ys,cs = [],[],[]
    for point in points:
        xs.append(point.x)
        ys.append(point.y)
        color = inPoly(poly,point, inclusive)
        cs.append(color)
        print point,":", color
    plt.scatter(xs,ys, c = cs , s = 20*4*2)

    #setting limits
    axes = plt.gca()
    axes.set_xlim([min(xs)-5,max(xs)+50])
    axes.set_ylim([min(ys)-5,max(ys)+10])

    plt.show()


# TESTS ========================================================================
#set up poly
polys = {
1 : [[10,10],[10,50],[50,50],[50,80],[100,80],[100,10]], # test rectangulary shape
2 : [[20,10],[10,20],[30,20]], # test triangle
3 : [[0,0],[0,10],[20,0],[20,10]], # test bow-tie
4 : [[0,0],[0,10],[20,10],[20,0]], # test rect clockwise
5 : [[0,0],[20,0],[20,10],[0,10]] # test rect counter-clockwise
}

#points to check
points = {
1 : [(10,25),(50,75),(60,10),(20,20),(20,60),(40,50)], # rectangulary shape test pts
2 : [[20,10],[10,20],[30,20],[-5,0],[20,15]] , # triangle  test pts
3 : [[0,0],[0,10],[20,0],[20,10],[10,0],[10,5],[15,5]],  # bow-tie shape test pts
4 : [[0,0],[0,10],[20,0],[20,10],[10,0],[10,5],[15,2],[30,8]],  # rect shape test pts
5 : [[0,0],[0,10],[20,0],[20,10],[10,0],[10,5],[15,2],[30,8]]  # rect shape test pts
}

for data in zip(polys.itervalues(),points.itervalues()):
    plot(data[0],data[1], True)

#================================================================================
#                           WEIGHTING FUNCTION
#================================================================================

def add_weights(poly, weights):
    poly.weights = [float(w) for w in weights]+[weights[0]] #need to add the first weight
                                                          # at the end to account for
                                                          # the first point being added to close the loop

def distance(a,b):
    dist = ( (b.x - a.x)**2 + (b.y - a.y)**2 )**0.5
    if dist == 0: dist = 0.000000001 
    return dist

def get_weighted_sum(poly, point):
    return sum([poly.weights[n]/distance(point,p) for n,p in enumerate(poly.points_shapely) if poly.weights[n] != 'nan'])

def get_weighted_dist(poly, point):
    return sum([1/distance(point,p) for n,p in enumerate(poly.points_shapely) if poly.weights[n] != 'nan'])

def get_point_weighted_value(poly, point):
    return get_weighted_sum(poly,point)/get_weighted_dist(poly,point)

#==============================================================================
    #           GETTING THE DATA inside the Polygone
#==============================================================================

'''Function Definitions'''

def data_extraction(filename,start_line,node_num,span_start,span_end):
    with open(filename, "r") as myfile:
        file_= csv.reader(myfile, delimiter=' ')  #extracts data from .txt as lines
        return (x for x in [filter(lambda a: a != '', row[span_start:span_end]) \
        for row in itertools.islice(file_, start_line, node_num)])

def merge_data(msh_data,reload_data):
    return (zip(msh_data,reload_data))


def edit_value(data, poly_init, weights):
    #make x,y coordinates of the data into points
    points_init = ([float(pair[0][0]),float(pair[0][2])]for pair in data)
    #convert to shapely poly and points
    poly,points = convert_to_shapely_points_and_poly(poly_init,points_init)
    add_weights(poly,weights)
    #fliter out points in polygon
    new_pair = []
    for n,point in enumerate(points):
        if inPoly(poly, point, True):
            value = str(get_point_weighted_value(poly, point))
            new_pair.append([value,value,value,value])
        else:
            new_pair.append(data[n][1])

    return (x for x in new_pair)


def make_file(filename,data):
    with open(filename, "w") as f:
        f.writelines('\t'.join(i) + '\n' for i in data)
        f.close()

def run(directory_path,poly_list,weight_list):
    ''' Directory and File Names'''
    msh_file = '\\nodes.txt'
    reload_file = '\\values.txt'
    new_reload_file = '\\new_values.txt'
    dir_path = directory_path
    msh_path = dir_path+msh_file
    reload_path = dir_path+reload_file

    '''Running the Code with your data'''
    mesh_data = data_extraction(msh_path,0,54,1,4)
    reload_data = data_extraction(reload_path,0,54,0,7)
    data = merge_data(mesh_data,reload_data)
    new_values = edit_value(data,poly_list,weight_list)
    make_file(dir_path+new_reload_file,new_values)        



t0 = time.time()
run("M:\\MyDocuments"
    ,([75,-800],[50,-900],[50,-1350],[90,-1000],[100,-900])
    ,(5.0e5,1e6,1e8,5.0e5,1.0e7))
t1= time.time()
print t1-t0

这是您可以使用的示例数据（您需要将其保存为感兴趣的文件夹中的values.txt）：

1.067896706746556e+006  8.368595971460000e+006  1.068728658407457e+006  8.368595971460000e+006  
2.844581459224940e+005  8.613334125294963e+006  2.846631849296530e+005  8.613337865004616e+006  
1.068266636556349e+006  8.368595971460000e+006  1.069097067800019e+006  8.368595971460000e+006  
2.844306728256134e+005  8.613334269264592e+006  2.846366503960088e+005  8.613338015263893e+006  
2.646871122251647e+003  9.280390372578276e+006  2.647124079593603e+003  9.279361848151272e+006  
2.645513962411728e+003  9.280388336827532e+006  2.645732877622660e+003  9.279359747270351e+006  
1.067996132697676e+006  8.368595971460000e+006  1.068827019510901e+006  8.368595971460000e+006  
1.068040363056876e+006  8.368595971460000e+006  1.068870797759632e+006  8.368595971460000e+006  
1.068068562573701e+006  8.368595971460000e+006  1.068898735336173e+006  8.368595971460000e+006  
1.068088894288788e+006  8.368595971460000e+006  1.068918905897983e+006  8.368595971460000e+006  
1.068104407561180e+006  8.368595971460000e+006  1.068934323713974e+006  8.368595971460000e+006  
1.068116587634527e+006  8.368595971460000e+006  1.068946455001944e+006  8.368595971460000e+006  
1.068126287610437e+006  8.368595971460000e+006  1.068956140100951e+006  8.368595971460000e+006  
1.068134059350058e+006  8.368595971460000e+006  1.068963921144020e+006  8.368595971460000e+006  
1.068140293705664e+006  8.368595971460000e+006  1.068970181121935e+006  8.368595971460000e+006  
1.068145286907994e+006  8.368595971460000e+006  1.068975209852979e+006  8.368595971460000e+006  
1.068149274285654e+006  8.368595971460000e+006  1.068979237556288e+006  8.368595971460000e+006  
1.068152448234754e+006  8.368595971460000e+006  1.068982452745734e+006  8.368595971460000e+006  
1.068154968237062e+006  8.368595971460000e+006  1.068985012157432e+006  8.368595971460000e+006  
1.068156966832556e+006  8.368595971460000e+006  1.068987046589365e+006  8.368595971460000e+006  
1.068158553584154e+006  8.368595971460000e+006  1.068988664694503e+006  8.368595971460000e+006  
1.068159818109515e+006  8.368595971460000e+006  1.068989955820237e+006  8.368595971460000e+006  
1.068160832713088e+006  8.368595971460000e+006  1.068990992449035e+006  8.368595971460000e+006  
1.068161654841110e+006  8.368595971460000e+006  1.068991832481593e+006  8.368595971460000e+006  
1.068162329417389e+006  8.368595971460000e+006  1.068992521432464e+006  8.368595971460000e+006  
1.068162891039026e+006  8.368595971460000e+006  1.068993094522149e+006  8.368595971460000e+006  
1.068163365980015e+006  8.368595971460000e+006  1.068993578612505e+006  8.368595971460000e+006  
1.068163773959426e+006  8.368595971460000e+006  1.068993993936813e+006  8.368595971460000e+006  
1.068164129647837e+006  8.368595971460000e+006  1.068994355591033e+006  8.368595971460000e+006  
1.068164443906155e+006  8.368595971460000e+006  1.068994674772899e+006  8.368595971460000e+006  
1.068164724771358e+006  8.368595971460000e+006  1.068994959776965e+006  8.368595971460000e+006  
1.068164978220522e+006  8.368595971460000e+006  1.068995216771951e+006  8.368595971460000e+006  
1.068165208742598e+006  8.368595971460000e+006  1.068995450386572e+006  8.368595971460000e+006  
1.068165419759155e+006  8.368595971460000e+006  1.068995664143054e+006  8.368595971460000e+006  
1.068165613928702e+006  8.368595971460000e+006  1.068995860772074e+006  8.368595971460000e+006  
1.068165793358832e+006  8.368595971460000e+006  1.068996042433189e+006  8.368595971460000e+006  
1.068165959755557e+006  8.368595971460000e+006  1.068996210870328e+006  8.368595971460000e+006  
1.068166114528858e+006  8.368595971460000e+006  1.068996367521690e+006  8.368595971460000e+006  
1.068166258863683e+006  8.368595971460000e+006  1.068996513593785e+006  8.368595971460000e+006  
1.068166393771001e+006  8.368595971460000e+006  1.068996650114520e+006  8.368595971460000e+006  
1.068166520124043e+006  8.368595971460000e+006  1.068996777970799e+006  8.368595971460000e+006  
1.068166638684427e+006  8.368595971460000e+006  1.068996897935547e+006  8.368595971460000e+006  
1.068166750121474e+006  8.368595971460000e+006  1.068997010687638e+006  8.368595971460000e+006  
1.068166855027363e+006  8.368595971460000e+006  1.068997116827437e+006  8.368595971460000e+006  
1.068166953929060e+006  8.368595971460000e+006  1.068997216889020e+006  8.368595971460000e+006  
1.068167047297063e+006  8.368595971460000e+006  1.068997311349124e+006  8.368595971460000e+006  
1.068167135553131e+006  8.368595971460000e+006  1.068997400635036e+006  8.368595971460000e+006  
1.068167219077452e+006  8.368595971460000e+006  1.068997485131862e+006  8.368595971460000e+006  
1.068167298214444e+006  8.368595971460000e+006  1.068997565188462e+006  8.368595971460000e+006  
1.068167373276848e+006  8.368595971460000e+006  1.068997641121696e+006  8.368595971460000e+006  
1.068167444552389e+006  8.368595971460000e+006  1.068997713223352e+006  8.368595971460000e+006  
1.068167512315698e+006  8.368595971460000e+006  1.068997781772706e+006  8.368595971460000e+006  
1.068167576851623e+006  8.368595971460000e+006  1.068997847061655e+006  8.368595971460000e+006  
1.068167638524622e+006  8.368595971460000e+006  1.068997909469268e+006  8.368595971460000e+006  
1.068167697990453e+006  8.368595971460000e+006  1.068997969688582e+006  8.368595971460000e+006

和节点数据的示例（需要保存为nodes.txt）：

0 0.26 0 -800.0
1 0.26 0 -1062.5
2 143.0 0 -800.0
3 143.0 0 -1062.5
4 0.26 0 -1150.0
5 143.0 0 -1150.0
6 1.17057404659 0 -800.0
7 2.10837283486 0 -800.0
8 3.07421037484 0 -800.0
9 4.06892500937 0 -800.0
10 5.0933801161 0 -800.0
11 6.14846485319 0 -800.0
12 7.23509501358 0 -800.0
13 8.35421377171 0 -800.0
14 9.50679247207 0 -800.0
15 10.6938315019 0 -800.0
16 11.9163611811 0 -800.0
17 13.1754426445 0 -800.0
18 14.472168711 0 -800.0
19 15.8076649025 0 -800.0
20 17.1830903981 0 -800.0
21 18.59963901 0 -800.0
22 20.0585402542 0 -800.0
23 21.5610604197 0 -800.0
24 23.1085036396 0 -800.0
25 24.7022130583 0 -800.0
26 26.3435719675 0 -800.0
27 28.0340049986 0 -800.0
28 29.7749793906 0 -800.0
29 31.5680062618 0 -800.0
30 33.4146418792 0 -800.0
31 35.3164890883 0 -800.0
32 37.2751986287 0 -800.0
33 39.2924705661 0 -800.0
34 41.3700558588 0 -800.0
35 43.5097577902 0 -800.0
36 45.7134335243 0 -800.0
37 47.9829957969 0 -800.0
38 50.3204145133 0 -800.0
39 52.7277184748 0 -800.0
40 55.2069971476 0 -800.0
41 57.7604024715 0 -800.0
42 60.3901507176 0 -800.0
43 63.0985244223 0 -800.0
44 65.8878743782 0 -800.0
45 68.7606216458 0 -800.0
46 71.7192596577 0 -800.0
47 74.7663564153 0 -800.0
48 77.904556725 0 -800.0
49 81.1365844387 0 -800.0
50 84.4652448319 0 -800.0
51 87.8934270922 0 -800.0
52 91.4241067682 0 -800.0
53 95.0603483625 0 -800.0
54 98.8053080549 0 -800.0
55 102.662236327 0 -800.0

Answer 1

我试图回答，但不确定这是否足够：

您可以通过在List中替换此部分来保存列表创建：

edit_values

通过

for n,point in enumerate(points):
    if inPoly(poly, point, True):
        value = str(get_point_weighted_value(poly, point))
        new_pair.append([value,value,value,value])
    else:
        new_pair.append(data[n][1])

return (x for x in new_pair)

您保存for n,point in enumerate(points): if inPoly(poly, point, True): value = str(get_point_weighted_value(poly, point)) yield [value,value,value,value] else: yield data[n][1]列表和相关内存的创建。

使用多边形选择性地替换具有＆gt; 1e6输入的网格中的节点值

1 个答案: