HYRY - 7 months ago 56

Python Question

As I understand, the

`list`

Are there any types that dynamically increase its capacity as a list, and stores the value as a NumPy array? Something like List in C#. And it's great if the type has the same interface as a NumPy array.

I can create a class which wraps a NumPy array inside, and resize this array when it's full, such as:

`class DynamicArray(object):`

def __init__(self):

self._data = np.zeros(100)

self._size = 0

def get_data(self):

return self._data[:self._size]

def append(self, value):

if len(self._data) == self._size:

self._data = np.resize(self._data, int(len(self._data)*1.25))

self._data[self._size] = value

self._size += 1

but DynamicArray can't be used as a NumPy array, and I think all the views returned by get_data() before np.resize() will hold the old array.

Edit: array type in array module is dynamic array. The following program test the increase factor of list and array:

`from array import array`

import time

import numpy as np

import pylab as pl

def test_time(func):

arrs = [func() for i in xrange(2000)]

t = []

for i in xrange(2000):

start = time.clock()

for a in arrs:

a.append(i)

t.append(time.clock()-start)

return np.array(t)

t_list = test_time(lambda:[])

t_array = test_time(lambda:array("d"))

pl.subplot(211)

pl.plot(t_list, label="list")

pl.plot(t_array, label="array")

pl.legend()

pl.subplot(212)

pl.plot(np.where(t_list>2*np.median(t_list))[0])

pl.plot(np.where(t_array>2*np.median(t_array))[0])

pl.show()

from the graph: the increase factor of list is bigger than array.

Answer

You may be interested to know that the Python standard library also includes an array module which sounds like just what you want:

This module defines an object type which can compactly represent an array of basic values: characters, integers, floating point numbers. Arrays are sequence types and behave very much like lists, except that the type of objects stored in them is constrained.