Question

我的图表为3秒,然后从上述图表中添加内容。我想从主要图表中收集轴心,以便我能够检索,并在提交分图时加以修改。我怎么能够接过这一错误?

这里的样本测试代码:

import pylibmc
cache = pylibmc.Client(["127.0.0.1"], binary=True, behaviors={"tcp_nodelay": True, "ketama": True})
import matplotlib.pyplot as plt


cache_name =  test 
fig = plt.figure(figsize=(20, 7))
ax = fig.add_axes([0, 0.15, 0.98, 0.85])
cache.set(cache_name, ax, 300)

造成以下错误:

cPickle.PicklingError: Can t pickle <type  function >: attribute lookup __builtin__.function failed

我能否做到这一点?

Answer 1

会上讨论了能否将校正数据编成序列的问题。我看不出任何报道都提到这个问题,甚至被接纳为目标。因此,如果你试图将电线上电离层,显然会失败。我在搜索时发现的讨论表明,目前使用的配对物设计很容易满足这一目标,这就要求内部进行重组。参考:rel=“nofollow”http://old.nabble.com/matplotlib-figure-serialization-td28016714.html。

为了大幅缩短执行时间,你可以做的是,将你的数据重新整理成数据集,只读到ax.bar(<>)。然后,数据集可以按你想要的任何格式(例如,以超标方式)加以分类和储存。

这里是显示你的做法与将这种做法合并成数据集的守则实例。如果你想要的话,你可以更容易地看到:。

import matplotlib.pyplot as plt
from random import randint 
from time import time 

DATA = [
    (i, randint(5,30), randint(5,30), randint(30,35), randint(1,5)) 
    for i in xrange(1, 401)
]

def mapValues(group):
    ind, open_, close, high, low = group
    if open_ > close: # if open is higher then close
        height = open_ - close # heigth is drawn at bottom+height
        bottom = close
        yerr = (open_ - low, high - open_)
        color =  r  # plot as a white barr
    else:
        height = close - open_ # heigth is drawn at bottom+height
        bottom = open_
        yerr = (close - low, high - close)
        color =  g  # plot as a black bar

    return (ind, height, bottom, yerr, color)

#
# Test 1
#
def test1():
    fig = plt.figure()
    ax = fig.add_subplot(111)

    data = map(mapValues, DATA)

    start = time()

    for group in data: 

        ind, height, bottom, yerr, color = group

        ax.bar(left=ind, height=height, bottom=bottom, yerr=zip(yerr), 
                color=color, ecolor= k , zorder=10,
                error_kw={ barsabove : False,  zorder : 0,  capsize : 0}, 
                alpha=1)

    return time()-start

#
# Test 2
#
def test2():
    fig = plt.figure()
    ax = fig.add_subplot(111)

    # plotData can be serialized
    plotData = zip(*map(mapValues, DATA))

    ind, height, bottom, yerr, color = plotData

    start = time()

    ax.bar(left=ind, height=height, bottom=bottom, yerr=zip(*yerr), 
            color=color, ecolor= k , zorder=10,
            error_kw={ barsabove : False,  zorder : 0,  capsize : 0}, 
            alpha=1)

    return time()-start


def doTest(fn):
    end = fn()
    print "%s - Sec: %0.3f, ms: %0d" % (fn.__name__, end, end*1000)



if __name__ == "__main__":
    doTest(test1)
    doTest(test2)

    # plt.show()

成果:

python plot.py 
test1 - Sec: 1.592, ms: 1592
test2 - Sec: 0.358, ms: 357

Answer 2

至于配对1.2,你应当能够收集数字和数据。

This is very much an "experimental" feature, but if you do find any issues, please let us know on the mpl mailing list or by raising an issue on github.com/matplotlib/matplotlib

HTH

Answer 3

查阅 documentation,看来fig.add_axes() 取道,作为理由,请通过名单。因此,它不退回<代码>Axes>的物体(因为其不是制造的),因此,其功能本身被分配。

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