我正在循环加载以.npy格式保存的10-15MB numpy数组，在Google Colab中每次加载大约需要1.5s。那是可以接受的速度吗？到目前为止，这是我循环中最慢的部分。另外，第二次我运行循环更快（大概是因为加载的文件已保存到RAM？），但最终它又变慢了（RAM耗尽了？）。 这是我用来加载数组的代码： data = np.load('/content/drive/My Drive/Share/Daily Data/Processed/' + str(fileName)) 任何加快此速度的建议将不胜感...

我刚刚开始学习如何使用Numba和CUDA进行编程，因此此代码可能非常错误，但我不明白为什么它不起作用。我试图对N个不同的数组求和，其内容取决于另一个数组。显示代码可能比以下解释更好： import numba as nb from numba import cuda import numpy as np from math import exp, ceil t0s = np.array([2.5,6.7,8.1,9.6,10.5]) threadsperblock = 32 blockspergrid ...

考虑以下python代码： def breakpoints_to_simulated_individuals(breakpoints, SNP_count, sampled_individuals): breakpoints = np.append(breakpoints, SNP_count*np.ones((len(breakpoints), 1), dtype = np.int64), axis = 1) breakpoints_masks = np.zeros((len(breakp...

我目前正在从头开始制作神经网络，并且已经将其与mnist数据集配合使用，以使测试图像的准确性达到80％左右。到这一点需要花一些时间，所以我试图通过动量实现梯度下降。当前代码是： def backProp(self, inputs, correct_output): self.outputLayerErrors = np.subtract(self.outputNeurons, correct_output) self.hiddenLayerErrors = np.multiply(np.do...

I remember once I was writing a class and while defining the __init__ method, I attempted to set an instance belonging to the same class, as in this example: class Complex: def __init__(self, real, imag): self.real = real self.imag = imag...

I have a 2d array, where each element is a fourier transform. I'd like to split transform 'logarithmically'. For example, let's take a single one of those arrays and call it a: a = np.arange(0, 512) # I want to split a into 'bins' defined by b, below: b =...

Lets say I have an shape=(70,50,40,30) array with fancy strides, import numpy as np np.random.seed(0) X = np.random.rand(70,50,40,30) X.strides = X.strides[:3] + (0,) Note that the 0-stride is just an example to explain the problem. 和两个二维二进制掩码 mask1 = (np...

我正在尝试将scipy LinearOperator转换为Numpy数组。 对于一个方形的LinearOperator，我能够获得Numpy数组，如下所示： from scipy.sparse.linalg import aslinearoperator import numpy as np L = aslinearoperator(A) A_np = L * np.eye(L.shape[1], dtype=np.float32) My question is how to convert an n-...

One of my pandas dataframe column is a list object of m columns, each row looks like this 'List(0.42, 0.24, 0.78,...)' with a list of n elements wrapped by quote marks. Dtype for this column is Object. 我需要将此列转换为m X n np数组。到目前为止，我尝试应用np.fromstring（col conte...

我想对向量进行归一化，以使归一化向量的平均值为某个预定值。例如，在以下示例中，我希望平均值为0.1： import numpy as np from sklearn.preprocessing import normalize array = np.arange(1,11) array_norm = normalize(array[:,np.newaxis], axis=0).ravel() Of course, np.mean(array_norm) is 0.28 and not 0.1. Is t...

我有一个如下所示的python数据框。我想使用百分比计算进行交叉表/数据透视，如下所示。 owner = ['a','a','a','b','b','b','c','c','c'] user = ['a','a','a','b','b','b','c','c','c'] used_hours = [75,25,0,500,250,250,400,50,50] available_hours = [100,100,100,1000,1000,1000,500,500,500] data = {'Owner':...

我正在尝试将世界变换应用于numpy矩阵。但是，我似乎找不到一种执行Nx4向量的4x4矩阵乘法的小方法，其中N是顶点数。 我都尝试过Nx4x4 @ Nx4和4x4 @ Nx4乘法。当然，我可以明智地做到这一点，但我希望有一种更聪明的方法来做到这一点。 vertices = np.ones([VERTEX_COUNT, 4]) vertices[:, 0:3] = vertex_map[element.path_vertices] matrix = np.full([VERTEX_COUNT, 4, 4], ...

当我声明一个符号和一个像这样的数组时 t = symbols('t') v1 = np.array([[1, 2, 3, 4, 5, ]]) print( type(v1) ) 我在数组中放了一个符号 v2 = v1.dot(t) print( type(v2) ) 问题1：如果现在v2里面有一个符号，为什么它仍然是numpy.ndarray？ 当我尝试集成此数组时，我无法做到 # I1 = integrate( v2 , t ) # this cannot be integrate beca...

我有一个数据框df_ss_g作为 ent_id,WA,WB,WC,WD 123,0.045251836,0.614582906,0.225930615,0.559766482 124,0.722324239,0.057781167,,0.123603561 125,,0.361074325,0.768542766,0.080434134 126,0.085781742,0.698045853,0.763116684,0.029084545 127,0.909758657,,0.760993759,0.998...

I have an 1x1024 1-d array (flattened image). To see the image, I want to reshape its size as 32x32. I can easily achieve this by doing x.reshape(-1,32) and it works as I intended. It doesn't screw the image. It reads the 1d array with 32-width stride each...

I am wondering how to load the Endo Mondo dataset found here: https://sites.google.com/eng.ucsd.edu/fitrec-project/home 该文件是6.0 gb npy文件 我正在尝试将其加载到colab pro实例中。 我试过在gpu和jax numpy上使用大型ram实例。我认为还有一个更明显的问题使我无法自拔。 很简单的问题简直不敢相信。 最好， 爱丹

我有一个尺寸为1000 x 1000的2D numpy数组。当查看类型时，我得到 >>>print(type(arr)) <class 'numpy.ndarray'> >>>print(type(arr[0])) <class 'numpy.ndarray'> 我想将此2D数组转换为numpy数组列表，并且我需要这种转换要快速，以便它可以用于较大比例的数组。我想将其转换以便获得这些结果 >>>print(type(arr)) <class 'list'> >>>print(type(arr[0...

我今天正在做一门课程的工作，任务是创建一个井字游戏板。可能性方法将井字游戏板作为输入，并检查是否有任何值是“ 0”，这意味着它是一个开放空间。我的计划是将0的位置添加到称为位置的数组中，然后在函数末尾返回位置。但是，当我尝试将0的位置附加到locations数组时，我不断遇到此问题：“所有连接轴的输入数组维必须完全匹配，但是沿着维0，索引0处的数组的大小为2并且索引1处的数组的大小为1“。有谁知道如何解决这个问题？谢谢 import numpy as np def create_board(): ...

重构代码时，我注意到我写了一行 class_proba = np.empty_like(self.classes_, dtype=np.float64) class_proba[:] = np.NaN so I thought, it would be faster to use full_like. But since the first rule of performance is "measure everything" (and not just "don't talk about...

I first initialized an array which is a column array (new_file = zeros(1280, float) Then the problem is inside the loop when I want to put the values into "new_file" the array remains zeros. Please, can someone give a solution or any idea what the problem ...