Adventures & experiences in contemporary technology
Custom error messages are good to add to SAS macros but you can get inconsistent colouration of the message text in multi-line messages. That was something that I just overlooked until I recently came across a solution. That is to use a hyphen at the end of the ERROR/WARNING/NOTE prefix instead of the more usual colon. Any prefixes ending on a hyphen are not included in the log text and the colouration ignores the carriage return that ordinary would change the text colour to black. The simple macro below demonstrates the effect.
Macro Code:
%macro test;
%put ERROR: this is a test;
%put ERROR- this is another test;
%put WARNING: this is a test;
%put WARNING- this is another test;
%put NOTE: this is a test;
%put NOTE- this is another test;
%mend test;
%test
Log Output:
ERROR: this is a test
this is another test
WARNING: this is a test
this is another test
NOTE: this is a test
this is another test
My response to changes in the technology stack used in clinical research is to develop some familiarity with programming and scripting platforms that complement and compete with SAS, a system with which I have been programming since 2000. One of these has been R but Python is another that has taken up my attention and I now also have Julia in my sights as well. There may be others to assess in the fullness of time.
While I first started to explore the Data Science world in the autumn of 2017, it was in the autumn of 2019 that I began to complete LinkedIn training courses on the subject. Good though they were, I find that I need to actually use a tool in order to better understand it. At that time, I did get to hear about Python packages like Pandas, NumPy, SciPy, Scikit-learn, Matplotlib, Seaborn and Beautiful Soup though it took until of spring of this year for me to start gaining some hands-on experience with using any of these.
During the summer of 2020, I attended a BCS webinar on the CodeGrades initiative, a programming mentoring scheme inspired by the way classical musicianship is assessed. In fact, one of the main progenitors is a trained classical musician and teacher of classical music who turned to Python programming when starting a family so as to have a more stable income. The approach is that a student selects a project and works their way through it with mentoring and periodic assessments carried out in a gentle and discursive manner. Of course, the project has to be engaging for the learning experience to stay the course and that point came through in the webinar.
That is one lesson that resonates with me with subjects as diverse as web server performance and the ongoing pandemic pandemic supplying data and there are other sources of public data to examine as well before looking through my own personal archive gathered over the decades. Some subjects are uplifting while others are more foreboding but the key thing is that they sustain interest and offer opportunities for new learning. Without being able to dream up new things to try, my knowledge of R and Python would not be as extensive as it is and I hope that it will help with learning Julia too.
In the main, my own learning has been a solo effort with consultation of documentation along with web searches that have brought me to the likes of Real Python, Stack Abuse, Data Viz with Python and R and others for longer tutorials as well as threads on Stack Overflow. Usually, the web searching begins when I need a steer on a particular or a way to resolve a particular error or warning message but books always are worth reading even if that is the slower route. Those from the Dummies series or from O’Reilly have proved must useful so far but I do need to read them more completely than I already have; it is all too tempting to go with the try the “programming and search for solutions as you go” approach instead.
To get going, many choose the Anaconda distribution to get Jupyter notebook functionality but I prefer a more traditional editor so Spyder has been my tool of choice for Python programming and there are others like PyCharm as well. Spyder itself is written in Python so it can be installed using pip from PyPi like other Python packages. It has other dependencies like Pylint for code management activities but these get installed behind the scenes.
The packages that I first met in 2019 may be the mainstays for doing data science but I have discovered others since then. It also seems that there is porosity between the worlds of R an Python so you get some Python packages aping R packages and R has the Reticulate package for executing Python code. There are Python counterparts to such Tidyverse stables as dply and ggplot2 in the form of Siuba and Plotnine, respectively. The syntax of these packages are not direct copies of what is executed in R but they are close enough for there to be enough familiarity for added user friendliness compared to Pandas or Matplotlib. The interoperability does not stop there for there is SQLAlchemy for connecting to MySQL and other databases (PyMySQL is needed as well) and there also is SASPy for interacting with SAS Viya.
Pyhton may not have the speed of Julia but there are plenty of packages for working with larger workloads. Of these, Dask, Modin and RAPIDS all have there uses for dealing with data volumes that make Pandas code crawl. As if to prove that there are plenty of libraries for various forms of data analytics, data science, artificial intelligence and machine learning, there also are the likes of Keras, TensorFlow and NetworkX. These are just a selection of what is available and there is no need not to check out more. It may be tempting to stick with the most popular packages all the time, especially when they do so much, but it never hurst to keep an open mind either.
For as long as I have been programming with SAS, there has been the ability to test if a variable does or does not have one value from a list of values in data step IF clauses or WHERE clauses in both data step and most if not all procedures. It was only within the last decade that its Macro language got similar functionality with one caveat that I recently uncovered: you cannot have a NOT IN construct. To get that, you need to go about things in a different way.
In the example below, you see the NOT operator being placed before the IN operator component that is enclosed in parentheses. If this is not done, SAS produces the error messages that caused me to look at SAS Usage Note 31322. Once I followed that approach, I was able to do what I wanted without resorting to older more long-winded coding practices.
options minoperator;
%macro inop(x);
%if not (&x in (a b c)) %then %do;
%put Value is not included;
%end;
%else %do;
%put Value is included;
%end;
%mend inop;
%inop(a);
Running the above code should produce a similar result to another featured on here in another post but the logic is reversed. There are times when such an approach is needed. One is where a small number of possibilities is to be excluded from a larger number of possibilities. Programming often involves more inventive thinking and this may be one of those.
When I upgraded to Ubuntu GNOME 13.10 and went for the 64-bit variant, I tried a previously tried and tested approach for installing Nightingale that used a PPA only for it not to work. At that point, the repository had not caught up with the latest Ubuntu release (it has by the time of writing) and other pre-compiled packages would not work either. However, there was one further possibility left and that was downloading a copy of the source code and compiling that. My previous experiences of doing that kind of thing have not been universally positive so it was not my first choice but I gave it a go anyway.
In order to get the source code, I first needed to install Git so I could take a copy from the version controlled repository and the following command added the tool and all its dependencies:
sudo apt-get install git autoconf g++ libgtk2.0-dev libdbus-glib-1-dev libtag1-dev libgstreamer-plugins-base0.10-dev zip unzip
With that lot installed, it was time to checkout a copy of the latest source code and I went with the following:
git clone https://github.com/nightingale-media-player/nightingale-hacking.git
The next step was to go into the nightingale-hacking sub-folder and issue the following command:
./build.sh
That should produce a sub-directory named nightingale that contains the compiled executable files. If this exists, it can be copied into /opt. If not, then create a folder named nightingale under /opt using copy the files from ~/nightingale-hacking/compiled/dist into that location. Ubuntu GNOME 13.10 comes with GNOME Shell 3.8, the next step took a little fiddling before it was sorted: adding an icon to application menu or dashboard. This involved adding a file called nightingale.desktop in /usr/share/applications/ with the following contents:
[Desktop Entry]
Name=Nightingale
Comment=Play music
TryExec=/opt/nightingale/nightingale
Exec=/opt/nightingale/nightingale
Icon=/usr/share/pixmaps/nightingale.xpm
Type=Application
X-GNOME-DocPath=nightingale/index.html
X-GNOME-Bugzilla-Bugzilla=Nightingale
X-GNOME-Bugzilla-Product=nightingale
X-GNOME-Bugzilla-Component=BugBuddyBugs
X-GNOME-Bugzilla-Version=1.1.2
Categories=GNOME;Audio;Music;Player;AudioVideo;
StartupNotify=true
OnlyShowIn=GNOME;Unity;
Keywords=Run;
Actions=New
X-Ubuntu-Gettext-Domain=nightingale
[Desktop Action New]
Name=Nightingale
Exec=/opt/nightingale/nightingale
OnlyShowIn=Unity
It was created from a copy of another *.desktop file and the categories in there together with the link to the icon were as important as the title and took a little tinkering before all was in place. Also, you may find that /opt/nightingale/chrome/icons/default/default.xpm needs to be become /usr/share/pixmaps/nightingale.xpm using the cp command before your new menu entry gains an icon to go with it. While the steps that I describe here worked for me, there is more information on the Nightingale wiki if you need it.
This useful addition came in SAS 9.2 and I am amazed that it isn’t enabled by default. To accomplish that, you need to set the MINOPERATOR option unless someone has done it for you in the SAS AUTOEXEC or another configuration program. Thus, the safety first approach is to have code like the following:
options minoperator;
%macro inop(x);
%if &x in (a b c) %then %do;
%put Value is included;
%end;
%else %do;
%put Value not included;
%end;
%mend inop;
%inop(a);
Also, the default delimiter is the space, so if you need to change that, then the MINDELIMITER option needs setting. Adjusting the above code so that the delimiter now is the comma character gives us the following:
options minoperator mindelimiter=",";
%macro inop(x);
%if &x in (a,b,c) %then %do;
%put Value is included;
%end;
%else %do;
%put Value not included;
%end;
%mend inop;
%inop(a);
Without any of the above, the only approach is to have the following and that is what we had to do for SAS versions prior to 9.2:
%macro inop(x);
%if &x=a or &x=b or &x=c %then %do;
%put Value is included;
%end;
%else %do;
%put Value not included;
%end;
%mend inop;
%inop(a);
It may be clunky but it does work and remains a fallback in newer versions of SAS. Saying that, having the IN operator available makes writing SAS Macro code that little bit more swish so it’s a good thing to know.
Recently, I found myself with a plot to produce but there were no data to be presented so a placeholder output is needed. For a lisitng or a table, this is a matter of detecting if there are observations to be listed or summarised and then issuing a placeholder lisitng using PROC REPORT if there are no data available. Using SAS/GRAPH, something similar can be acheived using one of its curiosities.
In the case of SAS/GRAPH, PROC GSLIDE looks like the tool to user for the same purpose. The procedure does get covered as part of a SAS Institute SAS/GRAPH training course but they tend to gloss over it. After all, there is little reason to go creating presentations in SAS when PowerPoint and its kind offer far more functionality. However, it would make an interesting tale to tell how GSLIDE became part of SAS/GRAPH in the first place. Its existence makes me wonder if it pre-exists the main slideshow production tools that we use today.
The code that uses PROC GSLIDE to create a placeholder graphic is as follows (detection of the number of observations in a SAS dataset is another entry on here):
proc gslide;
note height=10;
note j=center "No data are available";
run;
quit;
PROC GSLIDE is one of those run group procedures in SAS so a QUIT statement is needed to close it. The NOTE statements specify the text to be added to the graphic. The first of these creates a blank line of the required height for placing the main text in the middle of the graphic. It is the second one that adds the centred text that tells users of the generated output what has happened.
The inspiration for this post is a situation where having the string “OR” or “AND” as an input to a piece of SAS Macro code breaking a program that I had written. Here is a simplified example of what I was doing:
%macro test;
%let doms=GE GT NE LT LE AND OR;
%let lv_count=1;
%do %while (%scan(&doms,&lv_count,' ') ne );
%put &lv_count;
%let lv_count=%eval(&lv_count+1);
%end
%mend test;
%test;
The loop proceeds well until the string “AND” is met and “OR” has the same effect. The result is the following message appears in the log:
ERROR: A character operand was found in the %EVAL function or %IF condition where a numeric operand is required. The condition was: %scan(&doms,&lv_count,' ') ne
ERROR: The condition in the %DO %WHILE loop, , yielded an invalid or missing value, . The macro will stop executing.
ERROR: The macro TEST will stop executing.
Both AND & OR (case doesn’t matter but I am sticking with upper case for sake of clarity) seem to be reserved words in a macro DO WHILE loop while equality mnemonics like GE cause no problem. Perhaps, the fact that and equality operator is already in the expression helps. Regardless, the fix is a simple one:
%macro test;
%let doms=GE GT NE LT LE AND OR;
%let lv_count=1;
%do %while ("%scan(&doms,&lv_count,' ')" ne "");
%put &lv_count;
%let lv_count=%eval(&lv_count+1);
%end
%mend test;
%test;
Now none of the strings extracted from the macro variable &DOMS will appear as bare words and confuse the SAS Macro processor but you do have to make sure that you are testing for the null string (“” or ”) or you’ll send your program into an infinite loop, always a potential problem with DO WHILE loops so they need to be used with care. All in all, an odd looking message gets an easy solution without recourse to macro quoting functions like %NRSTR or %SUPERQ.
Recently, I tried code like this in a SAS macro:
data sections;
infile datalines dlm=",";
input graph_table_number $15. text_line @1 @;
datalines;
"11.1 ,Section 11.1",
"11.2 ,Section 11.2",
"11.3 ,Section 11.3"
;
run;
While it works in its own right, including it as part of a macro yielded this type of result:
ERROR: The macro X generated CARDS (data lines) for the DATA step, which could cause incorrect results. The DATA step and the macro will stop executing.
A bit of googling landed me on SAS-L where I spotted a solution like this one that didn’t involving throwing everything out:
filename temp temp;
data _null_;
file temp;
put;
run;
data sections;
length graph_table_number $15 text_line $100;
infile temp dlm=",";
input @;
do _infile_=
"11.1 ,Section 11.1",
"11.2 ,Section 11.2",
"11.3 ,Section 11.3"
;
input graph_table_number $15. text_line @1 @;
output;
end;
run;
filename temp clear;
The filename statement and ensuing data step creates a dummy file in the SAS work area that gets cleared at the end of every session. That seems to fool the macro engine into thinking that input is from a file and not the CARDS/DATALINES method to which it takes grave exception. The trailing @’s hold an input record for the execution of the next INPUT statement within the same iteration of the DATA step so that the automatic variable _infile_ can be fed as part of the input process in a do block with the output statement ensure that new records from the input buffer reach the data set being created.
This method does work but I would like to know the underlying reason as to why SAS Macro won’t play well with included data entry using DATALINES or CARDS statements in a data step, particularly when it allows other methods that using either SQL insert statements or standard variable assignment in data step. I find it such a curious behaviour that I remain on the lookout for the explanation why it is like this.
In previous posts, I have talked about getting VMware Workstation back on its feet again after a kernel upgrade. It also seems that VirtualBox is prone to the same sort of affliction. However, while VMware Workstation fails to start at all, VirtualBox at least starts itself even if it cannot get a virtual machine going and generates errors instead.
My usual course of action is to fire up Synaptic and install the drivers for the relevant kernel. Looking for virtualbox-ose-modules-[kernel version and type] and installing that usually resolves the problem. For example, at the time of writing, the latest file available for my system would be virtualbox-ose-modules-2.6.24-19-generic. If you are a command line fan, the command for this would be:
sudo apt-get install virtualbox-ose-modules-2.6.24-19-generic
The next thing to do would be to issue the command to start the vboxdrv service and you’d be all set:
sudo /etc/init.d/vboxdrv start
There is one point of weakness (an Achilles heal, if you like) with all of this: the relevant modules need to be available in the first place and I hit a glitch after updating the kernel to 2.6.24-20 when they weren’t; I do wonder why Canonical fail to keep both in step with one another and why the new kernel modules don’t come through the updates automatically either. However, there is a way around this too. That means installing virtualbox-ose-source via either Synaptic or the command line:
sudo apt-get install virtualbox-ose-source
The subsequent steps involve issuing more commands to perform a reinstallation from the source code:
sudo m-a prepare
sudo m-a auto-install virtualbox-ose
Once these are complete, the next is to start the vbox drv as described earlier and to add yourself to vboxusers group if you’re still having trouble:
sudo adduser [your username] vboxusers
The source code installation option certainly got me up and running again and I’ll be keeping it on hand for use should the situation raise its head again.
Rendering opening and closing brackets as pieces in SAS macro language programming caused me a bit of grief until I got it sorted a few months back. All of the usual suspects for macro quoting (or escaping in other computer languages) let me down: even the likes of %SUPERQ or %NRBQUOTE didn’t do the trick. The honours were left to %NRQUOTE(%(), which performed what was required very respectably indeed. The second "%" escapes the bracket for %NRQUOTE to do the rest.