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- 来自专栏CreateAMind
高维概率 High-Dimensional Probability
High-Dimensional Probability 高维概率 https://www.math.uci.edu/~rvershyn/papers/HDP-book/HDP-2.pdf 注记 本节我们举例说明概率方法
10510编辑于 2026-03-11 - 来自专栏饶文津的专栏
【hihocoder 1628】K-Dimensional Foil（线性代数）
施密特正交化可证明如果有解则存在下三角矩阵的解。距离平方和先减去前3维的距离平方和，这样就相当于去掉了3维。然后依次考虑每个点，看当前维度能不能满足答案，不能则加一维，再根据距离确定新加一维的值。
32820发布于 2020-06-02 【CodeForces】567D - One-Dimensional Battle Ships & 【51Nod】1521 - 一维战舰（STL - set & 二分）
One-Dimensional Battle Ships time limit per test 1 second memory limit per test input standard input output standard output Alice and Bob love playing one-dimensional
33610编辑于 2025-08-26- 来自专栏GEE数据专栏，GEE学习专栏，GEE错误集等专栏
NASA数据集——Two-Dimensional Video Disdrometer (2DVD)二维视频测距仪 (2DVD)数据集
简介 Two-Dimensional Video Disdrometer (2DVD) 测距仪是一种安装在固定地面站平台上的光学设备，用于测量不同类型水文流星（降水）的特性，如雨滴、雪花和冰雹。 Berne (2014): Hydrometeor classification from two-dimensional video disdrometer data. Atmospheric Measurement Techniques, 7, 2869-2882. doi: AMT - Hydrometeor classification from two-dimensional Krajewski (2002): Two-Dimensional Video Disdrometer: A Description, Journal of Atmospheric and Oceanic Technology, 19, 602-617. doi: Two-Dimensional Video Disdrometer: A Description in: Journal of Atmospheric
41010编辑于 2024-03-10 - 来自专栏GPUS开发者
DAY43:阅读纹理之Texture Object API
tex1Dfetch(cudaTextureObject_t texObj, int x); fetches from the region of linear memory specified by the one-dimensional class T> T tex1D(cudaTextureObject_t texObj, float x); fetches from the CUDA array specified by the one-dimensional cudaTextureObject_t texObj, float x, float level); fetches from the CUDA array specified by the one-dimensional float x, float y); fetches from the CUDA array or the region of linear memory specified by the two-dimensional z, float level); fetches from the CUDA array or the region of linear memory specified by the three-dimensional
1.2K10发布于 2018-08-01 - 来自专栏GPUS开发者
DAY45：阅读Surface Object API
reads the CUDA array specified by the one-dimensional surface object surfObj using coordinate x. reads the CUDA array specified by the two-dimensional surface object surfObj using coordinates x and reads the CUDA array specified by the three-dimensional surface object surfObj using coordinates x, y writes value data to the CUDA array specified by the three-dimensional object surfObj at coordinate x reads the CUDA array specified by the one-dimensional layered surface object surfObj using coordinate
84120发布于 2018-08-01 - 来自专栏计算机视觉理论及其实现
torch.nn.init
values drawn from the uniform distribution U(a,b)\mathcal{U}(a, b)U(a,b) .Parameters tensor – an n-dimensional Parameters tensor – an n-dimensional torch.Tensor mean – the mean of the normal distribution std – Also known as Glorot initialization.Parameters tensor – an n-dimensional torch.Tensor gain – an optional Also known as Glorot initialization.Parameters tensor – an n-dimensional torch.Tensor gain – an optional Also known as He initialization.Parameters tensor – an n-dimensional torch.Tensor a – the negative slope
1.1K31编辑于 2022-09-03 - 来自专栏云开发小程序1
小程序cloudbase之管理员发布二维码，登录用户实时获二维码（携带每个用户的openid、用户信息），管理员通过扫描来重新入库筛选已领取的用户（用户的二维码每一段时间刷新一次）
var DATE = util.formatTime(new Date()); wx.cloud.database().collection('GLY_Two_dimensional_code ，如果没有就把获取到的发布的二维码参数与本机用户信息参数结合添加到Two_dimensional_code数据库中，并将每一个加入数据库Two_dimensional_code的数据条中加入一个"控制开关 /user_Two_dimensional_code_XQ/user_Two_dimensional_code_XQ?user_Two_dimensional_code_XQ_id={{item. 先根据上个页面跳转传递过来的_id使用生命钩子函数访问Two_dimensional_code数据库，将获取到的数据渲染到页面，然后用户点击"生成我的二维码"时，先获取GLY_Two_dimensional_code 然后去Two_dimensional_code数据库中寻找该条用户二维码信息，并将数据中的zhuangtai关键字改为false，完成整个流程！！！
60330编辑于 2023-10-14 - 来自专栏帮你学MatLab
强化学习第-1步
这是环境类 classdef one_dimensional_env %一维宝藏环境类 properties len actions fresh_time (env.agent); env = env.step(A); % 采取动作获得状态和奖励 q_predict = one_dimensional_rl.q_table (env.agent, A); if env.done ~= 1 q_target = env.reward + one_dimensional_rl.gamma ; % 一局结束了 is_terminated = 1; % 更新标记 end one_dimensional_rl=one_dimensional_rl.update_q_table (env.agent, A,q_predict,q_target); % 更新 % disp(one_dimensional_rl.q_table) env.agent
64810发布于 2019-07-10 - 来自专栏Python联盟
全网最完整的Python操作Excel数据封装函数
写入xls格式文件 ''' 写入xls格式文件 参数： url:文件路径 sheet_name:表名 two_dimensional_data：将要写入表格的数据（二维列表） ' '' def write_xls_excel(url,sheet_name,two_dimensional_data): # 创建工作簿对象 workbook = xlwt.Workbook sheet.write(i,j,two_dimensional_data[i][j]) # 保存 workbook.save(url) print("写入成功") 3.1.3. （第几个工作表，传入参数从1开始数） ''' def write_xls_excel_add(url, two_dimensional_data, index): # 打开指定的工作簿 写入xlsx格式文件 ''' 写入xlsx格式文件 参数： url:文件路径 sheet_name:表名 two_dimensional_data：将要写入表格的数据（二维列表）
2.3K30编辑于 2022-01-27 - 来自专栏帮你学MatLab
matlab强化学习Q-Learning与Sarsa对比
Sarsa 实践派, 说到做到, 在这一步估算的动作也是接下来要做的动作， 在环境中每走一步, 更新一次自己的行为准则 % 强化学习Sarsa ccc rng('default'); env=two_dimensional_env (4,4,0.01); two_dimensional_rl=rl_q_table(env.actions,0.9,0.1,0.9); % pause(2) for episode =1:env.max_episodes env = env.reset(); env.render(); A = two_dimensional_rl.choose_action(env.agent); while 1 env = env.step(A); % 采取动作获得状态和奖励 A_ = two_dimensional_rl.choose_action(env.observation ); two_dimensional_rl=two_dimensional_rl.learn(env, A, A_); % 更新 two_dimensional_rl.dump
1.6K20发布于 2019-09-05 - 来自专栏GPUS开发者
DAY2:阅读CUDA C Programming Guide之编程模型
, two-dimensional, or three-dimensional thread index, forming a one-dimensional, two-dimensional, or three-dimensional block of threads, called a thread block【线程块】. Blocks are organized into a one-dimensional, two-dimensional, or three-dimensional grid of thread blocks Two-dimensional blocks or grids can be specified as in the example above. Each block within the grid can be identified by a one-dimensional, two-dimensional, or three-dimensional
1.2K40发布于 2018-06-25 - 来自专栏腾讯云容器专家服务的专栏
I have proved P=NP problem from math
Since time is considered as the one-dimensional world, the problem can be transformed: it doesn’t matter In 3-dimensional Euclidean space, the shortest path between two points is a straight line. In N-dimensional space, the length of a segment is measured based on time, not distance. An N-dimensional line segment is a special case at t = 0 in 3D space. In my n-dimensional math hypothesis , t constantly shifts, so n = 1 and n ≠ 1 hold at once.
51890编辑于 2025-06-16 - 来自专栏技术汇总专栏
Python数据维度解析：从基础到高阶的全面指南
以下是一个示例，演示如何创建和操作NumPy数组中的不同维度：import numpy as np# 创建一个一维数组one_dimensional = np.array([1, 2, 3, 4, 5 ])print("一维数组:", one_dimensional)# 创建一个二维数组two_dimensional = np.array([[1, 2, 3], [4, 5, 6]])print(" 二维数组:")print(two_dimensional)# 创建一个三维数组three_dimensional = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])print("三维数组:")print(three_dimensional)PandasPandas是Python中用于数据分析和处理的库，它提供了强大的数据结构，如Series和DataFrame import numpy as np# 创建一个4维数组four_dimensional = np.random.rand(2, 3, 4, 5)print("四维数组:")print(four_dimensional
79410编辑于 2024-06-24 - 来自专栏GPUS开发者
DAY46:阅读Surface Reference API
reads the CUDA array bound to the one-dimensional surface reference surfRef using coordinate x. writes value data to the CUDA array bound to the one-dimensional surface reference surfRef at coordinate reads the CUDA array bound to the two-dimensional surface reference surfRef using coordinates x and y reads the CUDA array bound to the three-dimensional surface reference surfRef using coordinates x, y, reads the CUDA array bound to the one-dimensional layered surface reference surfRef using coordinate
1.3K50发布于 2018-08-01 - 来自专栏单细胞天地
Seurat3教程: 自定义降维方法MDS
Seurat - Dimensional Reduction Vignette 我们知道单细胞转录组数据一个主要的特点就是数据稀疏，维度较高。基于此，Seurat提供了不少降维的方法： ? 今天我们就带大家走一走，Seurat对象的【multi-dimensional scaling (MDS)】降维方法。 若要求原始空间中样本之间的距离在低维空间中得以保持，即得到"多维缩放" (Multiple Dimensional Scaling，简称 MDS)，基于此，来探究降维的一般方法以及进一步了解Seurat reduction object with key PC_ Number of dimensions: 19 Projected dimensional reduction calculated ---- References [1] 数量生态学笔记||非约束排序|NMDS: https://www.jianshu.com/p/39021ec7d1dd [2] Dimensional Reduction
2.1K30发布于 2020-07-01 - 来自专栏火丁笔记
监控Netstat数据
php function one_dimensional_array($values, $prefix = 'netstat') { $result = array(); foreach is_string($value)) { $result[$key] = $value; } else { $result += one_dimensional_array ($value, $key); } } return $result; } function multi_dimensional_array($values, $indent prev($values); break; } } $v = multi_dimensional_array php exec('netstat -s', $values); $values = multi_dimensional_array($values); $values = one_dimensional_array
60430编辑于 2021-12-14 - 来自专栏帮你学MatLab
matlab强化学习Sarsa与Sarsa(lambda)对比
所以每一步在下回合被选中的几率又高了一些 当 lambda 取0, 就变成了 Sarsa 的单步更新 % 强化学习Sarsa lambda ccc % rng('default'); env=two_dimensional_env (4,4,0.01); two_dimensional_rl=rl_q_table(env.actions,0.9,0.1,0.9,0.9); % pause(2) for episode =1:env.max_episodes (env.agent); two_dimensional_rl = two_dimensional_rl.reset(); while 1 env = env.step( A); % 采取动作获得状态和奖励 A_ = two_dimensional_rl.choose_action(env.observation); two_dimensional_rl =two_dimensional_rl.learn(env, A, A_); % 更新 two_dimensional_rl.dump(); env.agent=env.observation
1.1K10发布于 2019-09-16 - 来自专栏气象学家
JuliaCon2021 | ClimateModels.jl：一个基于Julia开发的气候模式简单接口
Models that range from low dimensional to whole Earth System models are ran and analyzed via this simple Three examples illustrate this framework as applied to: - a stochastic path (zero-dimensional, Julia function) - a shallow water model (two-dimensional, Julia package) - a general circulation model Models that range from low dimensional to whole Earth System models can be run and/or analyzed via this
36810编辑于 2022-01-18 - 来自专栏GPUS开发者
DAY44：阅读Texture Reference API
fetches from the region of linear memory bound to the one-dimensional texture reference texRef using fetches from the CUDA array bound to the one-dimensional texture reference texRef using texture coordinate readMode> texRef, float x, float level); fetches from the CUDA array bound to the one-dimensional readMode> texRef, float x, float dx, float dy); fetches from the CUDA array bound to the one-dimensional texRef, float x, float y, float level); fetches from the CUDA array bound to the two-dimensional
63820发布于 2018-08-01
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