newton | Multiphysics coupling master code
kandi X-RAY | newton Summary
kandi X-RAY | newton Summary
Newton is a master code that solves implicit coupling in nonlinear calculations. It was designed with a general purpose. For example, it can be used in multiscale coupled problems, in CFD-temalhydraulic problems, in neutronic-termalhydraulic problems, and others. Newton solves residual coupling equations explicitly or implicitly. It has been demostrated in several works([1], [2]) that in some kind of problems implicit approaches improve convergence of the iterations.
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QUESTION
Could not load file or assembly 'Newtonsoft.Json, Version=12.0.0.0, Culture=neutral, PublicKeyToken=30ad4fe6b2a6aeed' or one of its dependencies. The located assembly's manifest definition does not match the assembly reference. (Exception from HRESULT: 0x80131040)
Doing my head in trying to find this reference. I am running a .NET Framework v4.5 project, and then importing the DLL into an aspx page.
The DLL contains a class used to connect to the Google APIs - specifically for the Google Calendar.
I've tried removing all the NuGet references and re-installing. I've ensured they are all updated to the latest stable version. The Newton.JSON library is specifically set to v13.0.1.
My packages.config file is as follows:
...ANSWER
Answered 2021-Jun-01 at 07:15Look into the .csproj file it should also been updated v13
sample
QUESTION
I am attempting to write a code for Newton's Method for nonlinear systems in Python. My g function is a 5x1 matrix and the jacobian (derivative matrix) of this is a 5x5 matrix. The vector for the initial y values (y0) is also a 5x1. i keep on getting the error
...ANSWER
Answered 2021-Jun-10 at 14:39The dimensions of y0
and g
seems to be wrong. Reduce them by one dimension:
QUESTION
I have the following table
...ANSWER
Answered 2021-Jun-07 at 10:57You can create a view:
QUESTION
I made a dropdown using Button
and a Popper
using Material UI components where you can click on the button and get a list of subjects to choose from.
To make the popper disappear either we can click on the button again or use a component which listens to click event and closes the
Popper
.
Now I've to make the list capable of drag and drop feature so I use the react-beautiful-dnd
npm package.
But the doesn't seem to work when I include
,
and
components.
Can anyone help me figure it out?
Here's the code without drag and drop feature. CodeSandbox link https://codesandbox.io/s/gallant-newton-mfmhd?file=/demo.js
ANSWER
Answered 2021-Jun-05 at 12:17You need to have your ClickAwayListener
at the top when you are using the Drag and Drop.
QUESTION
I've been asked in an exercise to find out how many years did all the inventors live in one number using "Array.prototype.reduce()"
...ANSWER
Answered 2021-Jun-04 at 21:04acc
should be a number representing the total years:
QUESTION
DROP TABLE IF EXISTS ..Players
DROP TABLE IF EXISTS ..FreeAgents
CREATE TABLE [dbo].[FreeAgents](
[Id] [int] IDENTITY(1,1) NOT NULL,
[FirstName] [nvarchar](50) NOT NULL,
[LastName] [nvarchar](50) NOT NULL,
[Position] [nvarchar](50) NOT NULL,
CONSTRAINT [PK_FreeAgents] PRIMARY KEY CLUSTERED
(
[Id] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
GO
CREATE TABLE [dbo].[Players](
[Id] [int] IDENTITY(1,1) NOT NULL,
[FirstName] [nvarchar](50) NOT NULL,
[LastName] [nvarchar](50) NOT NULL,
[Position] [nvarchar](50) NOT NULL,
CONSTRAINT [PK_Players] PRIMARY KEY CLUSTERED
(
[Id] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
GO
SET IDENTITY_INSERT [dbo].[FreeAgents] ON
GO
INSERT [dbo].[FreeAgents] ([Id], [FirstName], [LastName], [Position]) VALUES (2, N'Julian', N'Edelman', N'WideReceiver')
GO
INSERT [dbo].[FreeAgents] ([Id], [FirstName], [LastName], [Position]) VALUES (3, N'Dez', N'Bryant', N'WideReceiver')
GO
INSERT [dbo].[FreeAgents] ([Id], [FirstName], [LastName], [Position]) VALUES (4, N'Brandon', N'Jacobs', N'DefensiveEnd')
GO
SET IDENTITY_INSERT [dbo].[FreeAgents] OFF
GO
SET IDENTITY_INSERT [dbo].[Players] ON
GO
INSERT [dbo].[Players] ([Id], [FirstName], [LastName], [Position]) VALUES (1, N'Tom', N'Brady', N'Quarterback')
GO
INSERT [dbo].[Players] ([Id], [FirstName], [LastName], [Position]) VALUES (2, N'Cam', N'Newton', N'Quarterback')
GO
INSERT [dbo].[Players] ([Id], [FirstName], [LastName], [Position]) VALUES (3, N'Julian', N'Edelman', N'WideReceiver')
GO
SET IDENTITY_INSERT [dbo].[Players] OFF
GO
SELECT FirstName, LastName, Position FROM ..Players
UNION
SELECT FirstName, LastName, Position FROM ..FreeAgents
...ANSWER
Answered 2021-Jun-02 at 15:04If you have some set of keys that are not computation intensive (like id col in your example) I think you best bet would be to use temp table to store results from first view and then union ALL it with second with where check it does not exists in temp table.
QUESTION
I am trying to execute a code using the gfortran compiler. In order to compile, I use :
...ANSWER
Answered 2021-May-26 at 09:50Your structure basically is
QUESTION
I am using Python Spacy to replace any entity with the label_ == "PERSON" with "[XXX]". It seems like I have done that correctly, but I am struggling with replacing it in my Teststring:
...ANSWER
Answered 2021-May-25 at 21:26Since all you need is a string output, you can use
QUESTION
I am wondering which technique is used to learn the Dirichlet priors in Mallet's LDA implementation.
Chapter 2 of Hanna Wallach's Ph.D. thesis gives a great overview and a valuable evaluation of existing and new techniques to learn the Dirichlet priors from the data.
Tom Minka initially provided his famous fixed-point iteration approach, however without any evaluation or recommendations.
Furthermore, Jonathan Chuang did some comparisons between previously proposed methods, including the Newton−Raphson method.
LiangJie Hong says the following in his blog:
A typical approach is to utilize Monte-Carlo EM approach where E-step is approximated by Gibbs sampling while M-step is to perform a gradient-based optimization approach to optimize Dirichlet parameters. Such approach is implemented in Mallet package.
Mallet mentions the Minka's fixed-point iterations with and without histograms.
However, the method that is actually used simply states:
Learn Dirichlet parameters using frequency histograms
Could someone provide any reference that describes the used technique?
...ANSWER
Answered 2021-May-21 at 13:47It uses the fixed point iteration. The frequency histograms method is just an efficient way to calculate it. They provide an algebraically equivalent way to do the exact same computation. The update function consists of a sum over a large number of Digamma functions. This function by itself is difficult to compute, but the difference between two Digamma functions (where the arguments differ by an integer) is relatively easy to compute, and even better, it "telescopes" so that the answer to Digamma(a + n) - Digamma(a) is one operation away from the answer to Digamma(a + n + 1) - Digamma(a). If you work through the histogram of counts from 1 to the max, adding up the number of times you saw a count of n at each step, the calculation becomes extremely fast. Initially, we were worried that hyperparameter optimization would take so long that no one would do it. With this trick it's so fast it's not really significant compared to the Gibbs sampling.
QUESTION
I am trying to create a type for my function so that the return type changes based on a value passed to it. I've considered Typescript return type depending on parameter and following that to (almost) the letter seems to work just fine. In my project however, I must use arrow functions. Also, I'd like to avoid overloads if at all possible. Consider this signature and implementation:
...ANSWER
Answered 2021-May-20 at 14:50If you are giving up on overloads, but you still want a return type that switches depending on the parameter, then you will need to use a generic function returning a conditional type. For example:
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