10

我正在尝试读取包含线段的 XY 端点和与线段关联的值的文件，然后绘制由给定值着色的线段。我遇到的问题是可能有数十万到数百万个线段，当我尝试读取这些较大的文件时，我遇到了内存错误。有没有更高效的内存方式来做到这一点？

import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
import sys
import csv

if len(sys.argv) > 1:
    flofile = sys.argv[1]
else:
    flofile = "GU3\GU3.flo"

fig = plt.figure()
ax = fig.add_subplot(111)
jet = cm = plt.get_cmap('jet')
cNorm = colors.Normalize(vmin=0)
scalarMap = cmx.ScalarMappable(norm=cNorm,cmap=jet)
with open(flofile) as FLO:
    title = FLO.readline()
    limits = [float(tp) for tp in FLO.readline().split()]
    FLO.readline()#headers
    for line in FLO:
        if 'WELLS' in line: break        
        frac = ([float(tp) for tp in line.split()])
        ax.plot([frac[0],frac[2]],[frac[1],frac[3]],color=colorVal)


#ax.plot(*call_list)
scalarMap._A = []
plt.colorbar(scalarMap)
plt.xlim([0,limits[0]])
plt.ylim([0,limits[1]])

plt.show()

此代码适用于小文件。谢谢。

4

2 回答 2

12

我会调查LineCollection (doc)。

import matplotlib
import matplotlib.pyplot as plt    
import random


s = (600,400)
N = 100000

segs = []
colors = []
my_cmap = plt.get_cmap('jet')
for i in range(N):
    x1 = random.random() * s[0]
    y1 = random.random() * s[1]
    x2 = random.random() * s[0]
    y2 = random.random() * s[1]
    c  = random.random()
    colors.append(my_cmap(c))
    segs.append(((x1, y1), (x2, y2)))

ln_coll = matplotlib.collections.LineCollection(segs, colors=colors)

ax = plt.gca()
ax.add_collection(ln_coll)
ax.set_xlim(0, 600)    
ax.set_ylim(0, 400)
plt.draw()

它还将为第一次争论获取一个 numpy 数组列表。

于 2013-04-02T20:04:59.267 回答
5

您可能会考虑先在没有内存问题的位图图像上进行绘图，然后使用 matplotlib 微调绘图/图像。举个例子：

from PIL import Image
from PIL import ImageDraw
import random
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg

s = (500,500)
N = 100000

im = Image.new('RGBA', s, (255,255,255,255))
draw = ImageDraw.Draw(im)

for i in range(N):
    x1 = random.random() * s[0]
    y1 = random.random() * s[1]
    x2 = random.random() * s[0]
    y2 = random.random() * s[1]
    c  = random.random() * 256
    draw.line(((x1,y1),(x2,y2)), fill=(0, 255 - int(c), int(c), 255), width=1)

plt.imshow(np.asarray(im), extent=(-1,1,-1,1), aspect='equal', origin='lower')
plt.show()
于 2013-04-02T18:45:23.057 回答