Question

我目前正在学习SciPy，我希望与pylab和matplotlib进行一些练习，以便我尝试将Reddit的{{1}视觉化}} function。

当然这段代码不起作用，我无法弄清楚如何谷歌我想要的东西。

hot

编辑：不工作就意味着它给了我以下错误消息：

from pylab import *
import numpy as np

def f(t,v):
    y = lambda a : 1 if a > 0 else (-1 if a < 0 else 0)

    z = lambda a : log10(abs(a)) if abs(a) >= 1 else log10(1)

    return map(z,v)*map(y,v) + t

n = 256
x = np.linspace(0,100,n)
y = np.linspace(-50,+50,n)
X,Y = np.meshgrid(x,y)

contourf(X, Y, f(X,Y), 15, alpha=.75, cmap='jet')
C = contour(X, Y, f(X,Y), 15, colors='black', linewidth=.5)
show()

Answer 1

错误来自if a > 0，因为错误表示a的真值，这将是一个NumPy数组是不明确的。

NumPy ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
NumPy ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() leastsq

为什么a是NumPy数组而不是单个条目？ Python的map不会遍历数组的每个元素，它只会迭代一个维度而你的输入是多维的：

>>> a = np.arange(12).reshape(3, 4)
>>> a
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
>>> f = lambda x : x
>>> map(f, a)
[array([0, 1, 2, 3]), array([4, 5, 6, 7]), array([ 8,  9, 10, 11])]

你可以使用np.vectorize而不是map，它可以按你的需要工作，但是你应该在NumPy数组上使用向量化的NumPy函数，迭代将在由快速本机代码处理。以下是如何以这种方式编写代码：

import numpy as np
from pylab import *

def f(t,v):
    # reproduce "y" with vectorized functions
    temp_a = np.sign(v)

    # reproduce "z" with vectorized functions
    temp_b = np.log10(np.maximum(np.abs(v), 1.0))

    # could also do something like
    # abs_v = np.abs(v)
    # temp_b = np.where(abs_v >= 1, np.log10(abs_v), np.log10(1))

    return temp_a * temp_b + t

n = 256
x = np.linspace(0,100,n)
y = np.linspace(-50,+50,n)
X,Y = np.meshgrid(x,y)

contourf(X, Y, f(X,Y), 15, alpha=.75, cmap='jet')
C = contour(X, Y, f(X,Y), 15, colors='black', linewidth=.5)
show()

SciPy条件函数

1 个答案: