flange | scala client for heroku doozer | Platform As A Service library

Given source and target dataframes in Pandas, I need to update a column in the target dataframe by an amount specified in a column of the source dataframe, for every match on a key column.

In the example below, the source and target dataframes are RecetteDF and InventaireDF, respectively. The key column common to both is Codes interne. Quantite Reserver in the target has to be incremented with values from Quantite requise from the source on matching key.

I've made it work, but it's really not optimal.

So far my function looks like this:

I am trying to pause a thread until the initial thread finishes.

My thread_pool starts like:

I hope I can ask this question in a way that makes some sense as the data itself is not good. However, as it was written in the 1950s, I have no option but to try to make the best of it in trying to bring it into the current century for those of us who need it. Also, Benchmark speed is not an issue as this is run manually and only rarely, and always on my local PC rather than on the live server. The resulting table is then uploaded.

To outline, it is looking in the Models field in parts_listing to see any with the ordinal numbers 22ND, 23RD etc. If there are any, then it looks in parts_modelno to find all that begin with the cardinal number 22, 23 etc. It takes all that match and populates parts_parsed with the rows in the select statement. It is doing that but it is getting all from parts_modelno, not just those that match.

For the first query below, it works well but needs multiple copies, one for each of the ordinal and cardinal values of 22ND, 23RD, 24TH, 25TH, 26TH, 54TH and 22, 23, 24, 25, 26, 54.

The Models field being queried in parts_listing contains data that varies considerably and another query has already extracted the bulk of it. For example, 2250-51-52-55-70-71 is a shortcut for 2250, 2251, 2252, 2255, 2270, 2271 and there are others such as these below with each example being in its own row. Those have already been parsed into parts_parsed. Those with BODY (and similar ones with MODEL) are not being parsed properly but that's another issue and not important here.

In the example below we are trying to convert XML data into an HTML and here we are facing the challenge due to inconsistant for the element like as '' & '

' :

Note# If we are removing '

' element from the '' then xslt code working fine.

Reference URL : https://xsltfiddle.liberty-development.net/nbiE1aA/1

INPUT XML:

I have a Asp.Net Core API v5.0.7. The client is a ReactJs.Net app.

All my controllers are marked with:

I am filtering elements from a list that include '"' by the following code:

the model is as simple as this: I'd like to apply a torque to the Rotational Flange of a Revolute Joint.
However, the torque reaction should not be applied to the Support Flange of the Revolute Joint.
The torque reaction is indeed counterbalanced elsewhere and not in the Revolute Joint itself.
A real-world example is a vehicle wheel: the torque is given by a powertrain and transferred to the wheel by a shaft, so the torque reaction is not perceived on the wheelhub but on the powertrain mounts.

So, none of the above seems to be correct:

• in BLUE: there is a reaction on the Revolute frame_a that there shoudn't be. The support (white circle) seems to always balance the torque applied to the flange (gray circle)) but it doesn't make sense in this case;
• in RED: there is no reaction on Revolute frame_a but there is no speed in the 1D line and this is not ok.

So, how can apply a Torque to a Revolute Joint without being forced to sense the counterbalanced torque directly on the joint?

Here the code

Can someone please guide me how should I Load data in hive where I am getting " in some rows and in some rows data is coming without " for the same column value.

I'm trying to implement the QR24-Algorithm to calibrate flange/tool and robot/world from this paper by Floris Ernst (2012).

I need to solve an equation M_i*X - Y*N_i = 0 where M_i and N_i are known and i from 1 to the number of measurements and X and Y are unknown Matrices.

In the paper they combined this equation into a system of linear equations A*w = b, where A consists of 12*number of measurements rows and 24 columns, so I have a system of linear equations with 24 parameters, where I need at least 2 measurements to solve this system.

To solve this equation, I need to use the QR-Factorization in least square sense because with more measurements, this system has more equations than parameters.

I'm using the OLSMultipleLinearRegression from the Apache Commons Math library to solve the equation system: