i have some problem with doxygen documentation.
I want to have something like
E_SOME_ERROR | 0x000001 Detailed info about this error
Important think is that I need values generated by doxygen but I can't find any solution. Do you guys know if this is possible?
So for example
/**
* #brief Enum with error codes.
*/
enum enumName
{
ONE, /**< {HEX value} - 1st number */
TWO, /**< {HEX value} - 2nd number */
THREE, /**< {HEX value} - 3rd number */
FOUR, /**< {HEX value} - 4th number */
}
Should be generated in pdf like:
--------------------------------
| ONE | 0x0001 - 1st number |
--------------------------------
| TWO | 0x0002 - 2nd number |
--------------------------------
| THREE | 0x0003 - 3rd number |
--------------------------------
| FOUR | 0x0004 - 4th number |
--------------------------------
And each {HEX value} have to be generated by some macro or something like this not hardcoded.
Related
I use [TS] varsoc to obtain the optimum lag length for the Granger causality test in Stata. This command reports the optimal number of lags based on different criteria such as Akaike's information criterion (AIC).
Is there any way to store the optimal lag number (obtained based on AIC) in a variable and use it in the next command to estimate causality? Something like this:
Lag= varsoc X Y
tvgc X Y, p(Lag) d(Lag) trend window(30) prefix(_) graph
Here I adapt the first example in the help for varsoc. You can sort the matrix of statistics so that minimum AIC is in the first row, and read off the lag concerned.
. webuse lutkepohl2, clear
(Quarterly SA West German macro data, Bil DM, from Lutkepohl 1993 Table E.1)
. varsoc dln_inv dln_inc dln_consump
Lag-order selection criteria
Sample: 1961q2 thru 1982q4 Number of obs = 87
+---------------------------------------------------------------------------+
| Lag | LL LR df p FPE AIC HQIC SBIC |
|-----+---------------------------------------------------------------------|
| 0 | 696.398 2.4e-11 -15.9402 -15.9059 -15.8552* |
| 1 | 711.682 30.568 9 0.000 2.1e-11 -16.0846 -15.9477* -15.7445 |
| 2 | 724.696 26.028 9 0.002 1.9e-11* -16.1769* -15.9372 -15.5817 |
| 3 | 729.124 8.8557 9 0.451 2.1e-11 -16.0718 -15.7294 -15.2215 |
| 4 | 738.353 18.458* 9 0.030 2.1e-11 -16.0771 -15.632 -14.9717 |
+---------------------------------------------------------------------------+
* optimal lag
Endogenous: dln_inv dln_inc dln_consump
Exogenous: _cons
.
. mata
------------------------------------------------- mata (type end to exit) ---------------
: stats = st_matrix("r(stats)")
: _sort(stats, 7)
: st_numscalar("opt_lag_AIC", stats[1,1])
: end
-----------------------------------------------------------------------------------------
.
. di opt_lag_AIC
2
To plug into a later command automatically, use expressions like
`=opt_lag_AIC'
as arguments to options.
I'm trying to do simple calculations but I'm new and SAS is not intuitive to me.
Suppose I have this table.
data money;
infile datalines delimiter=",";
input name $ return $ invested;
datalines;
Joe,10,100
Bob,7,50
Mary,80,1000
;
Which creates this
/* name | return | invested */
/* _________________________ */
/* Joe | 10 | 100 */
/* Bob | 7 | 50 */
/* Mary | 80 | 50 */
I have three things I would like to do for my job that just switched over to SAS.
I need to make sure columns return and invested are numeric. When I run the code above, return column ends up being a CHAR column and I don't know why.
Now I want to create a new column and calculate the share of the total return they each got. In this case, the sum of return=97. This is the result I want.
/* name | return | invested | share_of_return */
/* ____________________________________________ */
/* Joe | 10 | 100 | 10.30% */
/* Bob | 7 | 50 | 7.22% */
/* Mary | 80 | 50 | 82.47% */
Next I want to find their ROI. Which is (return-investment) / investment * 100. This is the result I am looking for
/* Find ROI */
/* name | return | invested | share_of_return | ROI */
/* ___________________________________________________ */
/* Joe | 10 | 100 | 10.30% | -90% */
/* Bob | 7 | 50 | 7.22% | -86% */
/* Mary | 80 | 50 | 82.47% | 60% */
I appreciate your explanations and guidance in advanced. This is for a work project and we just switched over to SAS
1 & 3 are easy, 2 is slightly more difficult.
Remove $ in INPUT statement. $ indicates character. In your data you may need to convert it using the input function instead though.
Fix for example:
input name $ return invested;
Fix for actual data using input function. Note that you cannot convert types in a data step to the same name so I rename it while reading it in using the rename data set option.
data money2;
set money (rename = return = return_char);
return = input(return_char, best.);
drop return_char;
run;
Add total value to data step, SQL is fastest here:
proc sql;
create table money3 as
select *, sum(return) as return_total, return/calculated return_total as return_percentage f=percent12.1
from money2;
quit;
I outline two different methods of doing this here
Within a data step, add your calculation. It's probably most efficient if it can be done in first step.
Since a data step loops automatically you write the formula pretty much as shown. In this case I've also applied a format so it shows as a percentage but that requires you to not multiply it by 100. Depending on what you're doing next it may be best to leave it as numeric.
data money2;
set money (rename = return = return_char);
return = input(return_char, best.);
ROI = (return - investment)/investment;
format ROI percent12.1;
run;
drop return_char;
run;
My dataset contains multiple variables called avar_1 to bvar_10 referring to the history of an individual. For some reasons, the history is not always complete and there are some "gaps" (e.g. avar_1 and avar_4 are non-missing, but avar_2 and avar_3 are missing). For each individual, I want to store the first non-missing value in a new variable called var1 the second non-missing in var2 etc, so that I have a history without missing values.
I've tried the following code
local x=1
foreach wave in a b {
forval i=1/10 {
capture drop var`x'
generate var`x'=.
capture replace var`x'=`wave'var`i' if !mi(`wave'`var'`i')
if (!mi(var`x')) {
local x=1+`x'
}
}
}
var1 is generated properly but var2 only contains missings and following variables are not generated. However, I set trace on and saw that the var2 is actually replaced for all variables from avar_1 to bvar_10.
My guess is that the local x is not correctly updated as its value change for the whole dataset but should be different for each observation.
Is that the problem and if so, how can I avoid it?
A concise concrete data example is worth more than a long explanation. Your description seems consistent with an example like this:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str1 id float(avar_1 avar_2 avar_3 bvar_1 bvar_2)
"A" 1 . 6 8 10
"B" 2 4 . 9 .
"C" 3 5 7 . 11
end
* 4 is specific to this example.
rename (bvar_*) (avar_#), renumber(4)
reshape long avar_, i(id) j(which)
(note: j = 1 2 3 4 5)
Data wide -> long
-----------------------------------------------------------------------------
Number of obs. 3 -> 15
Number of variables 6 -> 3
j variable (5 values) -> which
xij variables:
avar_1 avar_2 ... avar_5 -> avar_
-----------------------------------------------------------------------------
drop if missing(avar_)
bysort id (which) : replace which = _n
list, sepby(id)
+--------------------+
| id which avar_ |
|--------------------|
1. | A 1 1 |
2. | A 2 6 |
3. | A 3 8 |
4. | A 4 10 |
|--------------------|
5. | B 1 2 |
6. | B 2 4 |
7. | B 3 9 |
|--------------------|
8. | C 1 3 |
9. | C 2 5 |
10. | C 3 7 |
11. | C 4 11 |
+--------------------+
Positive points:
Your data layout cries out for some structure given by a rename and especially by a reshape long. I don't give here code for a reshape wide as for the great majority of Stata purposes, you'd be better off with this layout.
Negative points:
!mi(var`x')
returns whether the first value of a variable is not missing. If foo were a variable in the dataset, !mi(foo) is evaluated as !mi(foo[1]). That is not what you want here. See https://www.stata.com/support/faqs/programming/if-command-versus-if-qualifier/ for the full story.
I'd recommend more evocative variable names.
I have a dataset where each person (row) has values 0, 1 or . in a number of variables (columns).
I would like to create two variables. One that includes the count of all the 0 and one that has the count of all the 1 for each person (row).
In my case, there is no pattern in the variable names. For this reason I create a varlist of all the existing variables excluding the ones that need not to be counted.
+--------+--------+------+------+------+------+------+----------+--------+
| ID | region | Qa | Qb | C3 | C4 | Wa | count 0 | count 1|
+--------+--------+------+------+------+------+------+----------+--------+
| 1 | A | 1 | 1 | 1 | 1 | . | 0 | 4 |
| 2 | B | 0 | 0 | 0 | 1 | 1 | 3 | 2 |
| 3 | C | 0 | 0 | . | 0 | 0 | 4 | 0 |
| 4 | D | 1 | 1 | 1 | 1 | 0 | 0 | 4 |
+--------+--------+------+------+------+------+------+----------+--------+
The following works, however, I cannot add an if statement
ds ID region, not // all variables in the dataset apart from ID region
return list
local varlist = r(varlist)
egen count_of_1s = rowtotal(`varlist')
If I change the last line with the one below, I get an error of invalid syntax.
egen count_of_1s = rowtotal(`varlist') if `v' == 1
I turned from count to summing because I thought this is a sneaky way out of the problem. I could change the values from 0,1 to 1, 2, then sum all the two values separately in two different variables and then divide accordingly in order to get the actual count of 1 or 2 per row.
I found this Stata: Using egen, anycount() when values vary for each observation however Stata freezes as my dataset is quite large (100.000 rows and 3000 columns).
Any help will be very appreciated :-)
Solution based on the response of William
* number of total valid responses (0s and 1s, excluding . )
ds ID region, not // all variables in the dataset apart from ID region
return list
local varlist = r(varlist)
egen count_of_nonmiss = rownonmiss(`varlist') // this counts all the 0s and 1s (namely, the non missing values)
* total numbers of 1s per row
ds ID region count_of_nonmiss, not // CAUTION: count_of_nonmiss needs not to be taken into account for this!
return list
local varlist = r(varlist)
generate count_of_1s = rowtotal(`varlist')
How about
egen count_of_nonmiss = rownonmiss(`varlist')
generate count_of_0s = count_of_nonmiss - count_of_1s
When the value of the macro varlist is substituted into your if clause, the command expands to
egen count_of_1s = rowtotal(`varlist') if Qa Qb C3 C4 Wa == 1
Clearly a syntax error.
I had the same problem to count the occurrences of specifies values in each observation across a set of variables.
I could resolve that problem in the following ways: If you want to count the occurrences of 0 in the values across x1-x2, so
clear
input id x1 x2 x3
id x1 x2 x3
1. 1 1 0 2
2. 2 2 0 2
3. 3 2 0 3
4. end
egen count2 = anycount(x1-x3), value(0)
i have a confussing problem here. I'm working with some arrays and trying to get the 10 minors values from all of them merged as well as the array they are within and the position they are inside such array.
My relation is arrays(id int, array float[]);
So, on it i have several stored arrays:
1, '{v1,v2,v3,v4,v5...}'
2, '{v1,v2,v3,v4,v5...}'...etc
My first query is next:
WITH T1 AS(SELECT id, unnest(array) value from arrays order by value LIMIT 10)
SELECT T1.id as id, cell(array,value) as offset, value from T1;
In this case cell() is an UDF i developed to return the position given an array and an arbitrary value.
The second query (using w-functions) is next:
WITH T1 AS(SELECT id, unnest(array) value from arrays)
SELECT id, row_number() over (partition by sid) as offset, value from T1 order by value LIMIT 10;
Despite they both return the same values (which is correct), the offset is not the same and seems they are somehow upside-down.
These are some examples outputs with bigger arrays im working with, and you can see the problemim having.
Query 1 output:
id | offset | value
-----+--------+-----------
1 | 17569 | 0.0156216
1 | 20801 | 0.0164499
1 | 20802 | 0.0171007
1 | 17570 | 0.0171008
1 | 17568 | 0.0180476
1 | 20800 | 0.0182249
1 | 20803 | 0.0194675
1 | 1411 | 0.02142
1 | 1412 | 0.02142
1 | 1413 | 0.0215976
Query 2 output:
id | offset | value
-----+--------+-----------
1 | 6591 | 0.0156216
1 | 9823 | 0.0164499
1 | 9824 | 0.0171007
1 | 6592 | 0.0171008
1 | 6590 | 0.0180476
1 | 9822 | 0.0182249
1 | 9825 | 0.0194675
1 | 26144 | 0.02142
1 | 26140 | 0.02142
1 | 26149 | 0.0215976
I would appreciate any help please. Thank you!
You haven't got an order specified in your window function in Query 2, which means that Postgres will probably be internally sorting by sid - before you outer ORDER BY value is applied.
WITH t1 AS (
SELECT id, UNNEST( array ) AS value
FROM arrays
)
SELECT id, row_number() OVER ( PARTITION BY sid ORDER BY value ) as offset, value
FROM t1
ORDER BY value
LIMIT 10;