si is step 1 instruction , How can I move few steps with 1 GDB commands?
For example I want to skip 3 instruction after address 0xabcd
b *0xabcd
---Breakpoint 2 at xabcd
commands 2
si
si
si
end
But this skip only 1 instruction , not 3
Related
I'm looking to run lm and ANOVA for the following Latin Square design:
Time
Subject 1 2 3
Square 1 1 9 (B) 3 (C) 6 (A)
2 18(A) 6 (B) 12(C)
3 12(C) 15(A) 5 (B)
Square 2 4 14(C) 8 (B) 11(A)
5 17(A) 9 (C) 9 (B)
6 7 (B) 7 (A) 7 (C)
I found that, if the replication occurs with different rows and the same columns, as in we'll have 6 different subjects and the subjects are nested in each replication (R/S), then the command is:
lm.1 <- lm(A ~ R/S + D + T + R)
anova(lm.1)
But, if we assume now that the replication occurs with the same rows and columns, as in S1=S4, S2=S5, and S3=S6, how would the lm code change?
Thank you.
It is ok to use this command:
opt -enable-new-pm=0 -instcount -stats source_IR.ll
I will get the result like:
===-------------------------------------------------------------------------===
... Statistics Collected ...
===-------------------------------------------------------------------------===
3 instcount - Number of Add insts
2 instcount - Number of And insts
10 instcount - Number of Br insts
1 instcount - Number of Call insts
10 instcount - Number of FAdd insts
11 instcount - Number of FDiv insts
7 instcount - Number of FMul insts
5 instcount - Number of ICmp insts
2 instcount - Number of Or insts
10 instcount - Number of PHI insts
2 instcount - Number of Ret insts
6 instcount - Number of UIToFP insts
12 instcount - Number of basic blocks
2 instcount - Number of non-external functions
69 instcount - Number of instructions (of all types)
But this is the instruction count of whole program. I want to get the instruction counts of each function in this IR.
I try the command below:
opt -enable-new-pm=0 -instcount -stats source_IR.ll -analyze
and I get the result:
Printing analysis 'Counts the various types of Instructions' for function 'main':
Printing analysis 'Counts the various types of Instructions' for function 'compute_pi_baseline':
===-------------------------------------------------------------------------===
... Statistics Collected ...
===-------------------------------------------------------------------------===
3 instcount - Number of Add insts
2 instcount - Number of And insts
10 instcount - Number of Br insts
1 instcount - Number of Call insts
10 instcount - Number of FAdd insts
11 instcount - Number of FDiv insts
7 instcount - Number of FMul insts
5 instcount - Number of ICmp insts
2 instcount - Number of Or insts
10 instcount - Number of PHI insts
2 instcount - Number of Ret insts
6 instcount - Number of UIToFP insts
12 instcount - Number of basic blocks
2 instcount - Number of non-external functions
69 instcount - Number of instructions (of all types)
there is nothing after the Printing line.
How could I get the instruction counts of each function by using llvm command?
I prefer not to write the pass by myself first.
I think you may edit the current instcount pass and print the information you want after loop through each function.
In Stata I have a list of subjects and contributions from an economic experiment.
There are multiple rounds being played for each treatment. Now I want to keep track of those who contributed in the first period and give them either 1 if a contributor or 0 if a defector. The game is played for multiple periods, but I only really care about the first round. My current code looks like this
g firstroundcont = 0
replace firstroundcont = 1 if c>0 & period==1
This however results in everyone getting a 0 for every subsequent period meaning that they are not "identified" as either a "first round" contributor or a defector for all other periods in the dataset. The table below shows a snippet of how my data looks and how the variable firstroundcont should look.
sessionID
period
subject
group
contribution
firstroundcont
1
1
1
1
4
1
1
1
2
1
0
0
1
1
3
1
2
1
1
1
4
2
10
1
1
1
5
2
0
0
1
1
6
2
0
0
1
2
1
1
0
1
1
2
2
1
5
0
1
2
3
1
0
1
#JR96 is right: this sorely and surely needs a data example. But I guess you want something with the flavour of
bysort id (period) : gen wanted = c[1] > 0
See https://www.stata.com/support/faqs/data-management/creating-dummy-variables/ and https://www.stata-journal.com/article.html?article=dm0099 for more on how to get indicators in one step. The business of generating with 0 and then replacing with 1 can usually be cut to a direct one-line statement.
I have a dataset that I am converting from wide to long format.
Currently I have 1 observation per patient, and each patient can have up to 5 aneurysms, currently recorded in wide format.
I am trying to re-arrange this dataset so that I have one observation per aneurysm instead. I have done so successfully, but now I need to label the aneurysms in a new variable called aneurysmIdentifier.
Here is a glimpse at the data. You can see how, when a patient has 4 aneurysms, I have successfully created 4 corresponding observations, however these are duplicates created via the expand function.
I am stuck at the next point, which, as mentioned, is creating a new variable aneurysmIdentifier that reads 1 if there is only one copy of the specific record_id, 1 and 2 if there are two copies and so forth all the way to 1-2-3-4-5. This would enable me to have a point of reference as to what I call aneurysm 1, 2, 3, 4 and 5 so I can keep re-arranging data to fit as such.
I have created this sketch hopefully showcasing what I mean. As you can see it counts how many duplicates there are and then counts forward up to the maximum of 5.
Can anyone push me in the right direction on how to achieve this?
Example of data:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str32 record_id float aneurysmNumber
"007128de18ce5cb1635b8f27c5435ff3" 1
"00abd7bdb6283dd0ac6b97271608a122" 1
"0142103f84693c6eda416dfc55f65de1" 1
"0153826d93a58d7e1837bb98a3c21ba8" 1
"01c729ac4601e36f245fd817d8977917" 2
"01c729ac4601e36f245fd817d8977917" 2
"01dd90093fbf201a1f357e22eaff6b6a" 1
"0208e14dcabc43dd2b57e2e8b117de4d" 1
"0210f575075e5def7ffa77530ce17ef0" 1
"022cc7a9397e81cf58cd9111f9d1db0d" 1
"02afd543116a22fc7430620727b20bb5" 1
"0303ef0bd5d256cca1c836e2b70415ac" 2
"0303ef0bd5d256cca1c836e2b70415ac" 2
"041b2b0cac589d6e3b65bb924803cf1a" 1
"0536317a2bbb936e85c3eb8294b076da" 1
"06161d4668f217937cac0ac033d8d199" 1
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"065e151f8bcebb27fabf8b052fd70566" 4
"07196414cd6bf89d94a33e149983d102" 1
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"0721c38f8275dab504fc53aebcc005ce" 4
"07bef516d53279a3f5e477d56d552a2b" 1
"08678829b7e0ee6a01b17974b4d19cfa" 1
"08bb6c65e63c499ea19ac24d5113dd94" 1
"08f036417500c332efd555c76c4654a0" 1
"090c54d021b4b21c7243cec01efbeb91" 1
"09166bb44e4c5cdb8f40d402f706816e" 1
"0930159addcdc35e7dc18812522d4377" 1
"096844af91d2e266767775b0bee9105e" 1
"09884af1bb9d59803de0c74d6df57c23" 1
"09e03748da35e9d799dc5d8ddf1909b5" 1
"0a4ce4a7941ff6d1f5c217bf5a9a3bf9" 1
"0a5db40dc58e97927b407c9210aab7ba" 2
"0a5db40dc58e97927b407c9210aab7ba" 2
"0a73c992955231650965ed87e3bd52f6" 1
"0a84ab77fff74c247a525dfde8ce988c" 3
"0a84ab77fff74c247a525dfde8ce988c" 3
"0a84ab77fff74c247a525dfde8ce988c" 3
"0af333ae400f75930125bb0585f0dcf5" 1
"0af73334d9d2166191f3385de48f15d2" 1
"0b341ac8f396a8cdb88b7c658f66f653" 2
"0b341ac8f396a8cdb88b7c658f66f653" 2
"0b35cf4beb830b361d7c164371f25149" 2
"0b35cf4beb830b361d7c164371f25149" 2
"0b3e110c9765e14a5c41fadcc3cfc300" .
"0b6681f0f441e69c26106ab344ac0733" 1
"0b8d8253a8415275dbc2619e039985bb" 3
"0b8d8253a8415275dbc2619e039985bb" 3
"0b8d8253a8415275dbc2619e039985bb" 3
"0b92c26375117bf42945c04d8d6573d4" 2
"0b92c26375117bf42945c04d8d6573d4" 2
"0ba961f437f43105c357403c920bdef1" 1
"0bb601fabe1fdfa794a5272408997a2f" 1
"0c75b36e91363d596dc46bd563c3f5ef" 1
"0d461328a3bae7164ce7d3a10f366812" 1
"0d4cc4eb459301a804cbef22914f44a3" 1
"0d4e29e11bb94e922112089f3fec61ef" 2
"0d4e29e11bb94e922112089f3fec61ef" 2
"0d513c74d667f55c8f4a9836c304149c" 1
"0da25de126bb3b3ee565eff8888004c2" 2
"0da25de126bb3b3ee565eff8888004c2" 2
"0db9ae1f2201577f431b7603d0819fa6" 1
"0dd8a681f6a5d4c888831a591e57a747" 1
"0e05d6958d878368b5fb831211fad6a1" 1
"0e3ff41e0e2b2cb5ec336fd0b04e5d44" 1
"0f61e560ab56b8fea1f2593d7d3b2718" 2
"0f61e560ab56b8fea1f2593d7d3b2718" 2
"0f69f1f998984d37f133185179d63c60" 1
"1037032886a93e66406a4c910d1ef747" 2
"1037032886a93e66406a4c910d1ef747" 2
"1044b81b354b420e85ae835ea07de2d6" 1
"10620fc488346291281212a404681386" 1
"1074389c469944edf026d193a55b1148" 1
"1090d5a678119b03cddab609289a4d3c" 1
"111eebb45cef2211a2a2ff0219095e6a" 1
"11ddcbc8de8ef56cbc578fc81b602ffc" 1
"11f22488513cf717c333786c789b0289" 2
"11f22488513cf717c333786c789b0289" 2
"121552b22cee2a1eb4360b4d2534cd39" 1
"1251d707c5dc9243dc45d04beb7c3493" 1
"125689659bb3821fa81698dd72462773" 1
"127ba572433921c5bb408fc62eb9b5d7" 1
"129bea3f73e84e37d77d55fadfeb49dd" 1
"12e8dc6fb87822be26d6678cee9644f5" 1
"12f05a65f771c9675c2c5e9cdbfc33d1" 2
"12f05a65f771c9675c2c5e9cdbfc33d1" 2
"13d2bc86f1a19ed2959cd7354bc92d1d" 1
"13db5ede38e2ae1da17884c9a18df202" 1
"13f946e50df8ad74d7cf9fa05b4ad05b" 1
"146c4b8be7996a9789873fe55a47ab41" 1
"147fadd87da13a0271225d944d2a5e98" 1
"14a1dcfa015343bbefaac9a3a45769e5" 2
"14a1dcfa015343bbefaac9a3a45769e5" 2
"14d1377f74a63ffa29db2d99e7f6a1ce" 1
"150017d944a87b4c61f90034380c0659" 1
"150f6ca1ea453260eabf3472d3ebcad1" 1
end
You can go
bysort record_id: gen aneurysm_id = _n
but the results will be arbitrary unless there is some other information, say a date variable, to provide a rationale for the ordering. Let's suppose that there is a date variable date that is numeric and in good order. Then
bysort record_id (date) : gen aneurysm_id = _n
would be a suitable modification. For date read also date-time if time of day is noted and notable.
I'm trying to detect specific values of one variable and create a new one if those conditions are fulfilled.
Here's a part of my data (I have much more rows) :
id time result
1 1 normal
1 2 normal
1 3 abnormal
2 1 normal
2 2
3 3 normal
4 1 normal
4 2 normal
4 3 abnormal
5 1 normal
5 2 normal
5 3
What I want
id time result base
1 1 normal
1 2 normal x
1 3 abnormal
2 1 normal x
2 2
2 3 normal
3 3 normal
4 1 normal
4 2 normal x
4 3 abnormal
5 1 normal
5 2 normal x
5 3
My baseline value (base) should be populated when result exists at timepoint (time) 2. If there's no result then baseline should be at time=1.
if result="" and time=2 then do;
if time=10 and result ne "" then base=X; end;
if result ne "" and time=2 then base=X; `
It works correctly when time=2 and results exists. But if results missing, then there's something wrong.
The question seems a bit off. "Else if time="" and time=1" There seems to be a typo there somewhere.
However, your syntax seems solid. I've worked an example with your given data. The first condition works, but second (else if ) is assumption. Updating as question is updated.
options missing='';
data begin;
input id time result $ 5-20 ;
datalines;
1 1 normal
1 2 normal
1 3 abnormal
2 1 normal
2 2
3 3 normal
4 1 normal
4 2 normal
4 3 abnormal
;
run;
data flagged;
set begin;
if time=2 and result NE "" then base='X';
else if time=1 and id=2 then base='X';
run;
Edit based on revisited question.
Assuming that the time-point (1) is always next to the point (2). (If not, then add more lags.) Simulating the Lead function we sort the data backwards and utilize lag.
proc sort data=begin; by id descending time; run;
data flagged;
set begin;
if lag(time)=2 and lag(result) EQ "" then base='X';
if time=2 and result NE "" then base='X';
run;
More about opposite of lag: https://communities.sas.com/t5/SAS-Communities-Library/How-to-simulate-the-LEAD-function-opposite-of-LAG/ta-p/232151