I am building a timemanagement system, where im using a Datagrid to list tasks / days, so you can register how much time you spend on a given task on a given day.
What i would like, is to do a summary at the bottom of each day.
| Tasks | Moanday | Tuesday | Wednesday | Thursday | Friday |
| Task 1 | 1 | 1 | 0 | 0 | 0 |
| Task 2 | 2 | 0 | 0 | 0 | 0 |
| Task 3 | 3 | 2 | 0 | 0 | 0 |
| 6 | 3 | 0 | 0 | 0 |
Does anyone have any hints, on how to add a footer like effect, like this?
I suggest you take a look at the agDataGridSuite from DevExpress. It supports summaries. They offer this grid as a free download. See link text
Related
What is the best way for storing enumerated fields with ability to change its order?
Lets say my database looks like this:
| Table |
|---------------------|
| id | name | order|
| 1 | 1st | 1 |
| 2 | 2nd | 2 |
| 3 | 3rd | 3 |
| 4 | 4th | 4 |
Now, when user change order in such a away
| Table |
|---------------------|
| id | name | order|
| 1 | 1st | 1 |
| 4 | 4nd | 2 |
| 2 | 2nd | 3 |
| 3 | 3rd | 4 |
Here I would have to update all rows in this table.
I consider 2 solutions
Solution 1)
When inserting row X between for example order 2 and order 3, I would change row's X order field to 3.5, So I would choose number in the middle between adjacent orders.
Above table would look like this
| Table |
|---------------------|
| id | name | order|
| 1 | 1st | 1 |
| 4 | 4nd | 2.5 |
| 2 | 2nd | 2 |
| 3 | 3rd | 3 |
Then, after for example 16 changes I would update table and normalize all order fields, so table after normalization would be like this:
| Table |
|---------------------|
| id | name | order|
| 1 | 1st | 1 |
| 4 | 4nd | 2 |
| 2 | 2nd | 3 |
| 3 | 3rd | 4 |
Solution 2)
I also consider adding fields "next" (or "next" and "prev") to each row, but it looks for me like waste of memory.
I really dont want to update whole table every time somebody change order. What is the best way of solving this problem?
I have a concern about data organisation and the best approach to simplify some multi-layered data. Simply, I have a 10 replicates of small wood beams (BeamID, ~10) subjected to a 10 different treatment (TreatID, ~10), and each beam is load tested which produces a series data of a Load with consequent Displacement (ranging from 10 to 50 rows per test; I have code that corrects for disparities in row length). Each wood beam is tested multiple times (Rep, ~10).
My plan was to lump all this data into a 5-D array:
Array[Load, Deflection, BeamID, TreatID, Rep]
This way, I should be able to plot the load~deflection curves for a given BeamID, TreatID, for all Reps by using Array[ , ,1,1, ], right? So the hypothetical output for Array[ , ,1,1,1], would be:
+------------+--------+-----+
| Deflection | Load | Rep |
+------------+--------+-----+
| 0 | 0 | 1 |
| 6.35 | 10.5 | 1 |
| 12.7 | 20.8 | 1 |
| 19.05 | 45.3 | 1 |
| 25.4 | 75.2 | 1 |
+------------+--------+-----+
And Array[ , ,1,1,2] would be:
+------------+--------+-----+
| Deflection | Load | Rep |
+------------+--------+-----+
| 0 | 0 | 2 |
| 7.3025 | 12.075 | 2 |
| 14.605 | 23.92 | 2 |
| 21.9075 | 52.095 | 2 |
| 29.21 | 86.48 | 2 |
+------------+--------+-----+
Or I think I could keep it as a simpler, 'melted' dataframe, which would have columns for Load and Deflection, and BeamID, TreatID, and Rep would be repeated for each row of the test output.
+------------+--------+-----+--------+---------+
| Deflection | Load | Rep | BeamID | TreatID |
+------------+--------+-----+--------+---------+
| 0 | 0 | 1 | 1 | 1 |
| 6.35 | 10.5 | 1 | 1 | 1 |
| 12.7 | 20.8 | 1 | 1 | 1 |
| 19.05 | 45.3 | 1 | 1 | 1 |
| 25.4 | 75.2 | 1 | 1 | 1 |
| 0 | 0 | 2 | 1 | 1 |
| 7.3025 | 12.075 | 2 | 1 | 1 |
| 14.605 | 23.92 | 2 | 1 | 1 |
| 21.9075 | 52.095 | 2 | 1 | 1 |
| 29.21 | 86.48 | 2 | 1 | 1 |
+------------+--------+-----+--------+---------+
However, with the latter, I'm not sure how I could easily and discretely pull out all the Rep test values for a specific BeamID and TreatID, especially since I use a linear model to fit a 3rd order polynomial for an specific test to extract the slope of the curves. Having it as a continuous dataframe means I'd have to specify starting and stopping points to start the linear model, correct?
Thoughts, suggestions? Am I headed in the right direction in using a 5-D array? R is a new programming language for me, so please pardon my misunderstandings.
I was wondering if you can help me with the following problem in spss syntax.
My dataset has nested structure.
Data are nested in companies, then each company has 1 or 2 bosses, but in this case I care only about boss 1. At a previous stage in time the boss graded the workers (not all of them). Now, the ID and the grade of the workers is on the row each worker.
I would like to move the information that was obtained during worker's assessment and create new sets of variables for each (worker ID and grade) on the line/row of the boss.
+---------+------+--------+--------------+---------+---------+--------+---------+
| company | boss |workerID|worker's grade|N:workID1|N:grade1 |N:work2 |N:grade2 |
+---------+------+--------+--------------+---------+---------+--------+---------+
| A | 1 | 1 | | 3 | A | 4 | A |
| A | 2 | 2 | | | |
| A | 0 | 3 | A | | |
| A | 0 | 4 | A | | |
| A | 0 | 5 | | | |
| B | 1 | 1 | | 3 | B | 4 | A |
| B | 0 | 2 | | | |
| B | 0 | 3 | B | | |
| B | 0 | 4 | A | | |
| C | 1 | 1 | | 2 | D | -1 | -1 |
| C | 0 | 2 | D | | |
I would like to move the worker's id and the grade that to the row of the boss in the NEW variables, without loosing the existing variables on workerID and worker's grade.
Basically, I will need to feed forward the information into the new variables and to the row of boss EQ 1 separately for each company.
I have no idea how to proceed with this. I assume that I need a loop that creates new variable for each worker ID that has a valid grade and then feeds forward the information from the worker's row to the boss' newly generated variables.
Any suggestions are very wellcome :-)
Take a look at VARSTOCASES (Data > Restructure)
Given an array of domain objects (with the properties subject, trial and run) like this:
+---------+-------+-----+
| Subject | Trial | Run |
+---------+-------+-----+
| 1 | 1 | 1 |
| 1 | 2 | 1 |
| 1 | 3 | 2 |
| 1 | 4 | 2 |
| 2 | 1 | 1 |
| 2 | 2 | 1 |
| 1 | 1 | 1 |
| 1 | 2 | 1 |
+---------+-------+-----+
i want to split it into multiple arrays at every point where the value for subject changes.
The above example should result in three arrays:
+---------+-------+-----+
| Subject | Trial | Run |
+---------+-------+-----+
| 1 | 1 | 1 |
| 1 | 2 | 1 |
| 1 | 3 | 2 |
| 1 | 4 | 2 |
+---------+-------+-----+
+---------+-------+-----+
| 2 | 1 | 1 |
| 2 | 2 | 1 |
+---------+-------+-----+
+---------+-------+-----+
| 1 | 1 | 1 |
| 1 | 2 | 1 |
+---------+-------+-----+
What would be the idiomatic Smalltalk (Pharo) way to split the array like this?
SequenceableCollection >> piecesCutWhere: which takes a binary block is your friend:
{ 1. 1. 2. 2. 2. 3. 1. 2. } piecesCutWhere: [:left :right | left ~= right]
=> an OrderedCollection #(1 1) #(2 2 2) #(3) #(1) #(2)
I have "components" which can be assembled in different ways into a "system". I want my database to hold all these "components", their type specific data and define how they are connected to each other to form a "system".
The systems are typically gearboxes and they can have rather complex branched designs. Let's start with an easy example:
This system is built up out of Masses (horizontal lines) and Stiffnesses (vertical lines). Gears and clutches are types of masses and come in pairs. Colors represent different branch speeds due to gear ratios. Here's a (bad) example of how I could store everything from this particular illustration:
ID | Type | Clutch | Ends | DrivenBy | NoOfTeeth| Mass | Stiffness
--- | ---- | ------ | ---- | --------- | -------- | ---- | ---------
1 | Mass | | Input1 | | | 5 |
2 | Stiffness | | | | | | 15
3 | Mass | 1.1 | | | | 2 |
4 | Mass | 1.2 | | | | 3 |
5 | Stiffness | | | | | | 20
6 | Gear | | | | 10 | 4 |
7 | Stiffness | | | | | | 30
8 | Gear | | | | 4 | 5 |
9 | Gear | | | 8 | 7 | 2 |
10 | Stiffness | | | | | | 40
11 | Mass | | | | | 4 |
12 | Stiffness | | Output1 | | | | 10
13 | Gear | | | 6 | 5 | 4 |
14 | Stiffness | | | | | | 20
15 | Mass | 2.1 | | | | 4 |
16 | Mass | 2.2 | | | | 3
17 | Stiffness | | | | | | 30
18 | Mass | | Output2 | | | 2 |
Obviously, this is not a very good way to store the data. This design pattern resembles somewhat of a "Repeated attributes" since each component type has a different attribute to be filled. I could create a table for each type of component, but things become more complex when looking at other examples, such as this 2-stage gearbox:
There are also examples with more than 1 input and several outputs, but I can't post more links due to low reputation.
Eitherway, you will see that the usual hierarchical data storage doesn't apply here because the data is not purely "tree-shaped" where everything branches off from 1 main branch.
I think that even though I could store data in the above mentioned way, I will get huge difficulties when it comes to the programming stage.
To add to the complexity, these gearboxes are actually sub-systems to a much bigger system.
So, any suggestions on a good way to store this type of data?*
Perhaps this is a possible way of doing it?
Here you will see that there is a "main" table called GearboxBranch, keeping track of all elements in the gearbox, giving them an id and to identify in which branch the element exists.
Then for the elements themselves, masses are defined in their dedicated table, so are stiffnesses. Gears and Clutches (which are types of masses) are then defined in their perspective tables. A recursive relationship is existing in the gear table, since one gear has to be driven by at least one other gear.
Furthermore, the table with Shaft Ends defines which of the elements in the gearbox are input or output and what number they have.
I can't seem to see any problems with this method, but I'm a little unsure how to get data out of the database. There will be considerable coding involved I'm afraid.