multidimensional-array

问题 I have a form that submits a report about checkpoints. Each checkpoint has a "status" and a "comment". The form is set up so it returns a multi-dimensional array with the key being the checkpoint ID like this: array(3) { ["status"]=> array(2) { ["000046"]=> string(1) "S" ["000047"]=> string(1) "S" } ["comment"]=> array(2) { ["000046"]=> string(6) "Flarg." ["000047"]=> string(0) "" } ["submit"]=> string(13) "SUBMIT REPORT" } In the above, checkpoint 000046 has a status of "S" and a comment of

问题 I have some output data from an ocean circulation model (MITgcm). It is an idealised channel (Cartesian) so the geometry is not confusing, luckily. I'd like to plot some of the fields (velocity, temperature etc.) in the y-z plane. The simulation domain involves 30 vertical layers where each layer is an 800x400 y-x grid. I have each of the fields stored in numpy arrays with shape (30, 800, 400) going z,y,x respectively. I can easily plot x-y plane slices for the 30 vertical levels. I can do

问题 I'm loading user information from a database for a telegram bot. I fetch the chatid, car number, and a timer value. An array is created to hold the different cars with their users. Subsequently, I check for each database result/user if their car is present in the array. If not, a new array is pushed into the array. If the car is present, the current user is added to as an array into the array of users. However, this doesn't seem to work. Note: to check if the value exists in the array, I'm

问题 How to select array_agg(ARRAY[f1_date,ARRAY[f2_int,f3_decimal]]) ? There is an error about combining date and integer in ARRAY. upd: added picture explaining where and how I plan to use array. The issue is db size. After transforming 3 colunms to multidimensional array I can save plenty of space. It will be 4M rows instead of 200M. Each row will have array with maximum 500 elements inside. 回答1: Arrays in Postgres share the same base element across all dimensions. Array of anonymous records

问题 I would like to multiply one of the elements from the 2D list by an integer. However, once I execute the code I get the following: I was expecting the outcome to be just a tuple, rather than a list, and would like for it to be a tuple rather than a list. [3, 3, 3] [6, 6, 3, 3, 3, 3] This is my code: list = [[0.5],[0.3],[0.1]] def funcOne(juv): newAd = juv * list[0] return newAd def funcTwo(ad,sen): newSen = (ad* list[1]) + (sen* list[2]) return newSen print(funcOne(3)) print(funcTwo(2,4)) My

问题 I'm a c++ noob trying to build a personal finance websocket server that tracks all of my assets and liabilities in real-time. I've found that I can make map s of map s to have a multi-dimensional system of key-value pairs. I've also found that boost::any and boost::variant can be used to store multiple types for a values. My problem is that some levels aren't very complex compared to others. For example, a bank account will only have a value, the amount in the account, while a brokerage

问题 this relates to my previous post. how to create a collection of multi dimensional arrays and not overwrite origional values when new ones are pushed i am thinking my problem has to do with how i am creating the array. what i'm trying to do is make an array that looks like this Array ( [10] => Array ( [0] => 29 [1] => 36 ) ) into something like this Array ( [10] => Array ( [0] => 29 [1] => 36 ) [20] => Array ( [0] => 29 [1] => 36 ) [25] => Array ( [0] => 29 [1] => 36 ) ) the 10, 20, and 25 is

问题 Is there a way in JavaScript to select a element of a multidimential array. Where the depth/rank/dimensionality is variable and the keys are given by a array of indices. Such that i don't have handle every possible dimentional depth separately. concretely speaking i want do get rid of switch cases like here: /** * set tensor value by index * @type {array} indices [ index1, index2, index3 ] -> length == rank. * @type {string} value. */ tensor.prototype.setValueByIndex = function( indices,

问题 I am trying to implement a lstm model with keras. The problem is that I have data of different shapes. My data looks like this: col1 col2 col3 col4 col5 [1,2,3] [2,3,4] [3,4,5] [5,6,7] [4,5,9] [0,2] [1,5] [1,24] [11,7] [-1,4] [0,2,4,5] [1,5,7,8] [1,24,-7,6] [11,7,4,5] [-1,4,1,2] My code is import numpy as np import pandas as pd import h5py from sklearn.model_selection import train_test_split from keras.layers import Dense from keras.layers import Input, LSTM from keras.models import Model X

问题 Suppose a PHP array, when cast to JSON, has the following format: [{ "key": "width", "value": "1200", "label": "Width (mm)", "choice": "" }, { "key": "height", "value": "900", "label": "Height (mm)", "choice": "" }, { "key": "material", "value": "paper", "label": "Material", "choice": "Paper" }] (This is a shortened version of the original, which can have many more elements) Let's suppose I want to efficiently find what material is used. In other words, I want to search for a nested array