Specifying Customizations for Schedule Viewing

Recall that the available typefaces, sizes, and colors are indicated in the customization generalities. Following are five samples of different customizations and how to achieve them. One is Sample 1 from the initial output description, but we'll come back to that one after looking at some simpler samples. As one goes through the examples here, they become increasingly complex, and the naive user may not wish to slog through this. Several predefined customizations are available from the submission page, and, most likely, I can easily write anything else that you may desire. I will be glad to respond to requests for particular customizations that you may like if you just email me (rig at cs.luc.edu) to indicate what you desire.

Sample 2

The easiest thing to do is to just submit an empty customizations file; in that case everything will be in black roman type. In the listing, you will get the "small" (9pt) typesize, and in the plot, you will get "tiny" (5pt). In the plot, each distinct row in your course data will generate a separate box, and each box in the plot will contain the entire input line for your course except the entries in the Code, Days, Beg, End, and Link columns. (The time information will be used to determine the box position, and the link information will be used to draw gray arrows.) Here we use the same course data as in Sample 1 and the same grid data but an empty file for customization settings: The Sample 2 results follow: empty2004fa Schedule

The following views of the "empty2004fa" schedule were produced using this course data, this grid data, and these customization settings: 




 

 You may notice that in this example, some of the courses have too
much data to fit comfortably within the corresponding box.  Even
worse, there are two boxes for different courses (330-001 and 101-002
on Tuesday) that are on top of one another.  That's because the input
data includes more than four courses meeting at the same time on
Tuesday, and I've only allowed space in the plot for four.  The latter
problem can be alleviated by consolidating course sections that have
mostly the same information, e.g., plotting the two 271 lecture
sections (271-001 and 271-002) in the same box.  In the next sample,
such consolidations are done, and the amount of data printed in each
box is toned down to respond to the first problem.




Sample 3



This sample is intended to illustrate a toning down of the amount
of data per course and consolidation of similar courses in the plot so
that the plot is a little less busy.  Also, by using fewer output
columns in the PS and PDF listings, it facilitates use of a larger
type size, which will allow a nice illustration of how headings are
done when the listing goes over 1 page.  (This example could be done
with a simpler customization file than we are about to show by just
removing some columns from the input; then you would also get narrower
plain text listings.  But we show here how to use the same input file
as before and just restrict the PS and PDF output.)


For the following results, we use the same
 
 grid data
 that was used for all prior samples and also the
 
 same course data.
 We also used this
 
 tiny customization file.


The first line of the
 
 customization file
 contains a comment.  Any line or portion of a line beginning with "#"
is a comment.  Once comments are stripped out, there are three
possible types of lines that one may use in the customization file,
depending on the number of colon-separated fields in the line.


The first line of this
 
 customization file
 is a type of setting recognized by the presence of two
colon-separated fields; the first field is a test, and the second is a
setting to be applied to all parts of the course data.  (The
customizations are applied line by line to each course to be listed or
plotted.)  In the example here, the test is of a special
implementation variable ploT, which is set to 1 when
performing customizations for a plot and 0 when performing
customizations for a listing.  (Note the unusual use of lower-case and
upper-case letters in the variable name.)  The "!=" is an inequality
test.  Thus, this line sets all parts of the course data in "Large"
(14pt) type when not processing a plot.  The double backslash before
"Large" and the quotes are due to implementation details regarding use
of the
 
 AWK programming language and
 
 LaTeX document formatting program.
 (Don't worry; you do not need to know either of these languages,
since it should generally be easy for you to copy or emulate the what
you see.  For example, to obtain a different typesize or typeface, you
can just replace "Large" with anything from the list of size and face
names ---
 
 PS,
 
 PDF.
 You can also use both a size and a face by typing, e.g.,
"\\huge\\bf".)  The backslash is a special character in
 
 AWK,
 so the doubled version is used to produce just one backslash in the
output.  The reason there is even one backslash is that backslash is
also special for
 
 LaTeX;
 it introduces a LaTeX command.


The next section in the
 
 customization file
 is used to restrict the columns that appear in the heading and data
rows of the PS and PDF listings and make the headings come out in
"Large" type.  These lines would be unnecessary if one simply limited
the input data to what one wants to print.  But with the bigger input
that is trimmed down in the PS and PDF output, we use here two special
variables heaD and outpuT (with unusual case as
before) that define the content of the header and data rows in the PS
and PDF listings.  The settings of these variables may look rather
strange, because they are based on details of
 
 AWK
 and
 
 LaTeX,
 but you can just mimic the style.


The next section in the
 
 customization file
 defines the conditions under which courses are consolidated into a
single box in the plot, the format of data that may be gathered from
different input lines in the course data for consolidation into a
single box, and the choice of other data printed in the box.  All
these lines (after the comment) are a different type of setting than
what we saw before; they are recognized by the presence of just
one (colon-separated) field.  Each such line is used directly
as an "action" in the
 
 AWK programming language.
 (Again, don't worry about fully understanding AWK, because you should
be able to emulate emulate customization examples provided through
this page.)


The first line of this consolidation section sets a special
variable keY; note the unusual case.  The value of
keY is what courses must have in common in order to be
consolidated into a single box.  You pretty much need to you start the
value of keY with "$daY$Beg$End" to be doing something
sensible.  Note that the first thing in the keY value is a
column name daY with unusual case.  This is not the
Days column that is expected to be present in the
input data; rather it is a new column added by the implementation to
the course data that was provided.  (The new column is not modified by
the general customization settings that appeared above.)  This new
column is utilized because courses are actually split into separate
entries for each day of the week on which they meet before they are
processed further for plotting, and $daY denotes the single meeting
day for the item currently under consideration.  In this example,
courses that have the same time, location, and title are consolidated;
these courses may differ in other columns, e.g., course number and
section number.  (Recall that Beg and
End are required input columns; a special
implementation trick is used so that if the course data lacks a
Loc or Title column, it will be
harmless, but if you write your own keY setting, you should
generally be careful that any new column names you introduce actually
appear in your input.)


(You may have noticed by now that when the underlying software
automatically creates a new column name or a variable assignment, it
uses a name that is all lower-case except the last letter.  The user
can create his own temporary variables in the customization file; to
avoid conflicts with other names, it is safest for the user to
introduce only new variables that do not begin or end with an
upper-case letter and to use column names that have a single
upper-case letter at the beginning.)


Skipping down to the third line of the consolidation
section, we find the format for non-common data that must be joined
from each of the courses being consolidated.  In this example, the
visible representation is the course number followed by an underscore (preceded
by one backslash in
 
 LaTeX
 since it is a special character and, thus, two backslashes inside the
 
 AWK
 string) and the section number, but the "\node" command of the
 
 LaTeX
 
 tree-dvips
 package is used to label the section number so that it can be the
source and/or target of a link (gray arrow in the plot).  This line
uses the special variable codeplaiN to recover the original
input value in the Code column before its
modification by other lines in the
 
 customization file.  Such a variable setting is automatically
provided for each column in the input data.  (These node labels are
attached automatically to courses that are not consolidated with
something else, but if consolidation is occuring, the customization
file is responsible for deciding how to attach these labels.)


Going back to the second line of the consolidation
section, we find the key logic to effect the consolidation.  You will
almost certainly not want to modify this line, but if you understand
 
 LaTeX,
 you could change the terminal "\\\\" to end up with something other
than "\\" (which is the
 
 LaTeX
 new line command) as the separator between the non-common data
fragments from different courses.


The remaining lines of the customization section are all designed
to manipulate a special variable corE.  This variable is
initially set by the processing software to contain all the original
input fields for the course (separated by spaces) except for
Code, Days, Beg,
End, and Link.  (That is
corE contains all the course data that won't already be shown
in the plot by way of positioning and arrows.)  But in our
consolidation of similar courses, we have determined that the contents
of the Num and Sec columns may
differ among items that are consolidated, and we have defined a print
format (in joiN) for the non-common Num and
Sec data that is joined together.  Thus we wish to
exclude the Num and Sec data from
the remaining print content of the box.  We do this by emptying the
content of corE so that the processing software will
recompute it later, and we add directives to omit the
Num and Sec columns.  (Note that a
reference to column content is, e.g., "$Num", but the form needed to
exclude $Num from corE is "corexclude[Num]=1" with no "$".)  We also
further tone down the amount of data to print in the boxes (as we had
indicated we would do) by excluding the Type,
Cred, Lim, and
Link columns.  This is consistent with the way we
toned down the amount of data in the PS and PDF listings.  (We
wouldn't need to do this if we had just put fewer columns in the
input.)


You may be wondering how we managed in
 Sample 2
 to omit the consolidation section completely.
 Such an omission is fine if you do not want any different input lines
from the course data to be consolidated in the plot; you will get a
default value of keY containing "$daY$Beg$End" and then all
input data for the course, starting from the first column, and then
columns added automatically when courses are processed for plotting:
 



 
The results for Sample 3 follow:
 
 
 fewcols2004fa Schedule
 






The following views of the "fewcols2004fa" schedule were produced using
this
 course data,
 this
 grid data,
 and these
 customization settings:
 







 





Sample 4



In this sample we return to the exact same
 
 course data
 as in
 Sample 1
 and
 Sample 2
 and the same
 
 grid data
 but with this
 
 customization file.
 This
 
 customization file
 illustrates some new features.


The first two lines of this
 
 customization file
 are in the format of two (colon-separated) fields specifying
a test and then a setting.  The first of these two lines assigns the
color Blue to all parts of a course's data as long as the course
number (in the Num column) contains a three digit
number beginning with a digit in the range 0 to 3.  The ~ character
and the slashes around the specification of the digits are part of the
 
 AWK
 syntax for pattern matching.  (This is a safer way to do the test
than a numeric "<400" test in case the Num column is
actually not present or in case some preceding manipulation has
already added non-numeric content to the field (e.g., a color, size,
or typeface).)  The second of the two lines assigns the color BrickRed
to courses in which the Num contains a three digit
number of 400 or greater.  (It should be apparent how to change the
number of digits in course numbers or the cutoff between undergraduate
and graduate.) These two lines show the detailed syntax for a color
setting with the string "\\color" and the curly braces around the
color name; to use a different color it is only necessary to change
the color name.


The next three non-blank lines of the
 
 customization file
 determine a typeface for each course according to it's location.
These lines again use the format of test and then setting.  The third
line in this section uses the test "1", meaning that the condition is
always satisfied.  Thus every course gets a setting of the sans serif
typeface, but this is applied after the possible application of
boldface for courses at WTC or roman for courses at LSC, and the first
typeface overrides any later typeface setting.  The result, then, is
that courses at WTC are in boldface, those at LSC are in roman, and
other courses are in sans serif.  (The rule that the first setting
overrides later settings also applies to typesizes; similarly it
applies to colors.  But settings of typeface are independent of
typesize settings, and similarly for any two different categories of
settings.)


Next comes the section for consolidation of similar courses in the
plot.  This section introduces no new concepts as compared to
 Sample 3,
 but it changes the values of keY and coreE.  In
this example, courses that have the same time, location, type,
credits, and instructor are consolidated; these courses may differ in
other columns, e.g., course number, section number, and title.  (One
may note that the input data we are working with does have crosslisted
courses with slightly different titles; they won't consolidate here,
because they are not at the same level (undergraduate versus
graduate), so they'll have different colors in the fields in
keY, but in the next sample, they will consolidate.)  Unlike
the prior example, we do not make corexcludE settings and leave the
redefinition of corE to the underlying software; instead here we
explicitly define the format for the core data to print in each box in
the plot.


Finally, the
 
 customization file
 specifies one more detail for plots; the typesize is set to
"scriptsize" (7pt) by using the "==" test for equality.  Note the
doubled equal sign for the equality test; a single equal sign is an
assignment.


 
The settings for Sample 4 can be summarized as follows:
 

 The results for Sample 4 follow:
 
 
 simplest2004fa Schedule
 






The following views of the "simplest2004fa" schedule were produced using
this
 course data,
 this
 grid data,
 and these
 customization settings:
 







 





Sample 5



In this sample we again use the exact same
 
 course data
 as in
 Sample 1,
 Sample 2,
 and
 Sample 4,
 and the same
 
 grid data
 but with this
 
 customization file.


The customization here differs only a little from that of
 Sample 4.
 The first change is that the initial color customization by course
number is not applied to all fields of the course data; rather it is
only applied to the course number and section number.  This is done
with two lines of a slightly different form than we have seen before.
These lines in the
 
 customization file.
 have more than two (whitespace separated) fields; they are thus
interpreted as specifying a test, then a setting, and then a list of
the course data fields to which the setting should be applied.
 After this initial color customization, we do the same consolidation of
courses for the plot as we did in
 Sample 4,
 but now there is nothing to impede consolidation of courses that have
the same time, location, type, credits, and instructor, even if one is
undergraduate and one is graduate.  Before, they would not
consolidate, because different colors had been applied to there common
data; now the initial color customization has not been applied to any
of the fields in the keY variable that controls consolidation.


The second new feature of the
 
 customization file
 is that we do a test after consolidation for courses that are
crosslisted undergraduate and graduate courses.  We use our knowledge
of the format used for consolidating the non-common information from
consolidated courses to search for appropriate patterns indicating a
three-digit course number of 400 or greater and a three-digit course
number of 399 or less.  Understanding this statement in detail does
require some understanding of the
 
 AWK programming language,
 but one should be able to see how to do simple modifications such as
changing the form of numbers indicating undergraduate versus graduate.
The setting applied here to courses that are crosslisted
undergraduate/graduate is to color them Magenta (chosen because it is
the additive combination of Red and Blue).  The previous settings of
Blue and Red for course/section numbers of undergraduate and graduate
courses, respectively, take precedence, but now any remaining fields
of crosslisted undergraduate/graduate courses are colored Magenta.


Next, this
 
 customization file
 applies the earlier Blue and Red colorings for undergaduate and
graduate course/section numbers, respectively to the remaining fields
of these courses.  For crosslisted undergraduate/graduate courses, the
Magenta setting for these other fields will take precedence, but
courses that are solely undergraduate or graduate will now be totally
colored Blue or Red, respectively.  This coloring of all fields was
deferred to avoid interfering with consolidation in the plot of
crosslisted undergradate/graduate courses.  (An alternative way to
write these two lines would be:
 
 $Num~/Red/ "\\color{Red}"
 $Num~/Blue/ "\\color{Blue}"
 
)


 
The settings for Sample 5 can be summarized as follows:
 

 The results for Sample 5 follow:
 
 
 simpler2004fa Schedule
 






The following views of the "simpler2004fa" schedule were produced using
this
 course data,
 this
 grid data,
 and these
 customization settings:
 







 





Sample 1



Now we return to Sample 1, which was presented in the initial
 output description.
 Sample 1 differs from
 Sample 5,
 that we just looked at only in using a slightly more complicated
 
 customization file.


The customization here differs from that of
 Sample 5
 only in that course level (undergraduate versus graduate) is coded by
tpeface rather than color, and colors are used to code course location
and type (e.g., lab versus lecture) rather than level.  The
substitution of typefaces for colors with the level tests should be
immediately comprehensible.  The color-coding by level and type is
just a bit more subtle, because the order is significant.  We do more
specific tests first (e.g., coloring a WTC Lab CornflowerBlue) before
a more inclusive test (e.g., coloring all WTC courses Blue).  The
first setting of CornflowerBlue will take precedence for a WTC Lab,
while all other WTC courses will be colored Blue.

 
The settings for Sample 1 can be summarized as follows:
 

 
 The results for Sample 1 are repeated here:
 
 
 2004fa Schedule
 






The following views of the "2004fa" schedule were produced using
this
 course data,
 this
 grid data,
 and these
 customization settings:
 







 









 Last updated
 on 29-Jan-08 at 11:30 CST
 by Ronald I. Greenberg 
 (rig at cs.luc.edu)