disc

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Get the above error when the execute immediate is called in a loop Update CustomersPriceGroups set 1AO00=:disc Where cuno=:cuno Parameters: disc=66 cuno=000974 Update CustomersPriceGroups set 1AP00=:disc Where cuno=:cuno Parameters: disc=70.5 cuno=000974 Update CustomersPriceGroups set 1AQ00=:disc Where cuno=:cuno Parameters: disc=66 cuno=000974 Update CustomersPriceGroups set 1ZA00=:disc Where cuno=:cuno Parameters: disc=60 cuno=000974 What does this mean ? Here is the code fragment c:=PriceWorx.frcPriceListCustomers('020','221'); LOOP

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Seems that requirements on safety do not seem to like systems that use AI for safety-related requirements (particularly where large potential risks of destruction/death are involved). Can anyone suggest why ? I always thought that, provided you program your logic properly, the more intelligence you put in an algorithm, the more likely this algorithm is capable of preventing a dangerous situation. Are things different in practice? 回答1: Most AI algorithms are fuzzy -- typically learning as they go along. For items that are of critical safety

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: On the client side I need to know when/if my socket connection has been broken. However the Socket.Connected property always returns true, even after the server side has been disconnected and I've tried sending data through it. Can anyone help me figure out what's going on here. I need to know when a socket has been disconnected. Socket serverSocket = null ; TcpListener listener = new TcpListener ( 1530 ); listener . Start (); listener . BeginAcceptSocket ( new AsyncCallback ( delegate ( IAsyncResult result ) { Debug . WriteLine (

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I have an array like this: >>> np.ones((8,8)) array([[ 1., 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1., 1.]]) I'm creating a disc shaped mask with radius 3 thus: y,x = np.ogrid[-3: 3+1, -3: 3+1] mask = x**2+y**2 This gives: >> mask array([[False, False, False, True, False, False, False], [False, True, True, True, True,

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: This seems like it ought to be ridiculously easy, but I'm having trouble figuring it out. I want to replicate the function so the disc image appears to the left, but applied to a tag I have this, but it does not show the disc image. .list { margin-top: 15px; margin-bottom: 15px; list-style:disc outside none; display:inline; } And Much, Much More! I want to avoid using any graphics to simulate the bullet if at all possible. Thanks for the help 回答1: Answer: display: list-item; Display must be set to list-item - not inline, and not list! .list

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I am looking to calculate occupancy in emergency department (ED) with tidyverse. Occupancy is understood here in this particular problem as Admitted but did not leave the hospital within the same hour they were admitted. A clearer example would be: if I came at ED at 12:00:00 and did not leave within the hour I was admitted, then I am occupying the bospital. So for this I need to create a new column Occupancy. (A little insight to give - I want to plot occupancy by hour of the day. Yet I know how to plot this, but do not know how

from datetime import datetime import os import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from six.moves import xrange data = np.load('final37.npy') data = data[:,:,0:60] #显示原始数据图像 def Show_images(data,show_nums,save=False): index = 0 for n in range(show_nums): show_images = data[index:index+100] show_images = show_images.reshape(100,3,60,1) r,c = 10,10 fig,axs = plt.subplots(r,c) cnt = 0 for i in range(r): for j in range(c): xy = show_images[cnt] for k in range(len(xy)): x = xy[k][0:30] y = xy[k][30:60] if k == 0 : axs[i,j].plot(x,y,color='blue',linewidth=2) if k == 1

一个函数是一组在一起执行任务的语句。 在MATLAB中，函数在单独的文件中定义。文件的名称和函数的名称应该是一样的。 函数在自己的工作空间内的变量上运行，这个变量也称为本地工作空间，与在MATLAB命令提示符下访问的工作区(称为 基本工作区 )不同。 函数可以接受多个输入参数，并可能返回多个输出参数。 函数语句的语法是 - function [ out1 , out2 , ... , outN ] = myfun ( in1 , in2 , in3 , ... , inN ) MATLAB 示例 以下名称为 mymax 的函数应写入名称为 mymax.m 的文件中。它需要五个数字作为参数，并返回参数数字值的最大值。 创建名为 mymax.m 的函数文件，从左上角菜单中点击 新建 -> 函数 ，并在其中键入以下代码 - function max = mymax ( n1 , n2 , n3 , n4 , n5 ) % This function calculates the maximum of the % five numbers given as input max = n1 ; if ( n2 > max ) max = n2 ; end if ( n3 > max ) max = n3 ; end if ( n4 > max ) max = n4 ; end if ( n5

感觉，都统一了，pytorch tensorflow mxnet，大家都差不多了 import tensorflow as tf from tensorflow.keras import Model,layers import numpy as np from tensorflow.keras.datasets import mnist num_features = 784 lr_generator = 0.0002 lr_descriminator = 0.0002 training_steps = 20000 batch_size = 128 display_step = 500 noise_dim = 500 def getDataset(): (x_train,y_train),(x_test,y_test) = mnist.load_data() x_train,x_test = np.array(x_train,np.float32),np.array(x_test,np.float32) x_train,x_test = x_train/255.0,x_test/255.0 return x_train,y_train,x_test,y_test x_train,y_train,x_test,y_test = getDataset() # n轴拆分 train

15.1 【出题思路】 熟悉理解虚函数、虚成员的定义。 【解答】 在类中被声明为 virtual 的成员，基类希望这种成员在派生类中重定义。除了构造函数外，任意非 static 成员都可以为虚成员。 15.2 【出题思路】 区分 protected 和 private 的访问权限控制的不同之处。 【解答】 protected 为受保护的访问说明符。protected 成员可以被该类的成员、友元和派生类成员（非友元）访问，而不可以被该类类型的普通用户访问。而 private 成员只能被基类的成员和友元访问，派生类不能直接访问。 15.3 【出题思路】 书中示例，作为基类用于后续练习题。 【解答】 Quote.h #ifndef TEST_QUOTE_H #define TEST_QUOTE_H #include <string> #include <iostream> class Quote { public: Quote() = default; Quote(const std::string &book, double sales_price) : bookNo(book), price(sales_price) { } std::string isbn() const { return bookNo; } // 返回给定数量的书籍的销售总额 //