Well, I'm a bit new to Prolog, so my question is on Prolog pattern/logic.
I have an relationship called tablet. It has many parameters, such as name, operationSystem, ramCapacity, etc. I have many objects/predicates of this relationship, like
tablet(
name("tablet1"),
operatingSystem("ios"),
ramCapacity(1024),
screen(
type("IPS"),
resolution(1024,2048)
)
).
tablet(
name("tablet2"),
operatingSystem("android"),
ramCapacity(2048),
screen(
type("IPS"),
resolution(1024,2048),
protected(yes)
),
isSupported(yes)
).
And some others similar relationships, BUT with different amounts of parameters. Some of attributes in different objects I do not need OR I have created some tablets, and one day add one more field and started to use it in new tablets.
There are two questions:
I need to use the most flexible structure as possible in prolog. Some of the tablets have attributes/innerPredicates and some do not, but They are all tablets.
I need to access data the easiest way, for example find all tablets that have ramCapacity(1024), not include ones that do not have this attributes.
I do need to change some attributes' values in the easiest way. For example query - change ramCapacity to 2048 for tablet that has name "tablet1".
If it's possible it should be pretty to read in a word editor :)
Is this structure flexible? Should I use another one? Do I need additional rules to manipulate this structure? Is this structure easy to change with query?(I keep this structure in a file).
Since the number of attributes is not fixed and needs to be so flexible, consider to represent these items as in option lists, like this:
tablet([name=tablet1,
operating_system=ios,
ram_capacity=1024,
screen=screen([type="IPS",
resolution = res(1024,2048)])]).
tablet([name=tablet2,
operating_system=android,
ram_capacity=2048,
screen=screen([type="IPS",
resolution = res(1024,2048)]),
is_supported=yes]).
You can easily query and arbitrarily extend such lists. Example:
?- tablet(Ts), member(name=tablet2, Ts).
Ts = [name=tablet2, operating_system=android, ram_capacity=2048, screen=screen([type="IPS", resolution=res(..., ...)]), is_supported=yes] ;
false.
Notice also the common Prolog naming_convention_to_use_underscores_for_readability instead of mixingCasesAndMakingEverythingExtremelyHardToRead.
Related
I'm sort of new to Web2py. I have a system that's working just fine, but I want to make an improvement regarding visualization. There's a couple of fields that use numbers (defined as double in their respective define_table methods) to represent currency, but I want them to also show with a separator for thousands, such as 183,403,293.34. I checked some documentation, but I couldn't find a direct way to handle this form of customization, though I could be missing something.
Any suggestions regarding this? Cheers!
First, if representing currency, you should use the decimal field type rather than double (some calculations using double values may yield incorrect results due to the use of floating point representations internally). However, if using SQLite, there is no distinction between decimal and double, so in that case, you might want to multiply all values by 100 and instead store integers.
In any case, to display a given numeric value with thousands separators in Python, you can do:
'{:,}'.format(myvalue)
For more details, see https://stackoverflow.com/a/10742904/440323 and https://stackoverflow.com/a/21208495/440323.
If you are using the values via web2py functionality that makes use of the field's represent function (e.g., the grid or the .render() method), you can define a custom represent function, such as:
Field('amount', 'decimal(12, 2)',
represent=lambda v, r: '{:,}'.format(v) if v is not None else '')
You could use the Python function of the locale module:
{{= locale.format ('%. 2f', your_value, grouping = True)}}
How can I get the value of important id and ValueType?
I have tried using web_save_param_regexp (but unfortunately I don't fully understand how the function works).
I have also tried using web_save_param (with the help of offset and length).
unfortunately once again I cannot get the accurate value some values change in length specially when the total amount values dynamically changes per run.
<important id=\"insertsomevalueshere\" record=\"1\" nucTotal=\"NUC609.40\"><total amount=\"68.75\" currency=\"USD\"/><total amount=\"609.40\" currency=\"USD\"/><out avgsomecost=\"540.65\" ValueType=\"insertsomevalueshere\" containsawesomeness=\"1\" Score=\"-97961\" somedatatype=\"1\" typeofData=\"VAL\" web=\"1\">
Put these lines of code before the line of code which does your web request:
web_reg_save_param_regexp("ParamName=importantid","Regexp=<important id=\\\"(.*?)\\\"",LAST);
web_reg_save_param_regexp("ParamName=ValueType","Regexp= ValueType=\\\"(.*?)\\\"",LAST);
You will then have two stored parameters 'importantid' and 'ValueType'
Dynamic number of elements to correlate? Your path for resubmission is through web_custom_request(). You will need to build the string you need dynamically with the name:value pairs for all of the data which needs to be included.
This path will place a premium on your string manipulation skills in the language of the tool. The default path is through C, but you have other language options if your skills are more refined in another language.
I'm trying to figure out how to use JSL to write some of the analysis of variance variables values to a table in JMP. My idea is to write a script that runs different types of models with different parameters with R^2 and RSME logging to a table (maybe there is a better way to do this I'm on my second day of JMP). Going through the documentation it seems that different analysis have different ways of doing this and I can't find one for "fit model". I also will need to know how to do this for a neural network which I think I may have found the documentation for.
If you're doing something like screening variables to determine an optimized model, you're in the right place with the fit model platform. However, running the fit model in a loop without human judgment in model selection as you've suggested isn't necessarily expedient.
So at the expense of trying to make JMP/JSL do something it's not really suited for, one way to achieve your generic goal of grabbing text from the fit model platform output is to send your platform to a "report" and then pull from that "report" the data you want, and then send it to a data table. From that data table, you can concatenate it with another data table and you would have your log. That's the idea, here's an example, for some dummy data "Ydata" and "Xdata":
thing = Fit Model(
Y( :Ydata ),
Effects( :Xdata ),
Personality( Standard Least Squares ),
Emphasis( Minimal Report ),
Run(
:Ydata << {Plot Actual by Predicted( 0 ),
Plot Residual by Predicted( 0 ), Plot Effect Leverage( 0 )}
)
);
thing_report = thing<<report;
thing_report_dt_ref = thing_report["Summary of Fit"][1] << make into data table;
//alternatively
//thing_report_dt_ref = thing_report[TableBox(1)] << make into data table;
thing_report_dt_ref << Set Name("Choose_a_name_for_your_new_data_table");
You'd have to handle the looping part, but if you can do it once, you can do it N times.
Because JMP/JSL is stupid, you can alternatively call the "Summary of Fit" directly if your know it's name in the tree structure. In my case, its name was "TableBox(1)". Do:
thing << show tree structure
To see where your data lives in the platform display box.
Which package is best for a heatmap/image with sorting on rows only, but don't show any dendrogram or other visual clutter (just a 2D colored grid with automatic named labels on both axes). I don't need fancy clustering beyond basic numeric sorting. The data is a 39x10 table of numerics in the range (0,0.21) which I want to visualize.
I searched SO (see this) and the R sites, and tried a few out. Check out R Graphical Manual to see an excellent searchable list of screenshots and corresponding packages.
The range of packages is confusing - which one is the preferred heatmap (like ggplot2 is for most other plotting)? Here is what I found out so far:
base::image - bad, no name labels on axes, no sorting/clustering
base::heatmap - options are far less intelligible than the following:
pheatmap::pheatmap - fantastic but can't seem to turn off the
dendrograms? (any hacks?)
ggplot2 people use geom_tile, as Andrie points out
gplots::heatmap.2 , ref - seems
to be favored by biotech people, but way overkill for my purposes. (no
relation to ggplot* or Prof Wickham)
plotrix::color2D.matplot also exists
base::heatmap is annoying, even with args heatmap(..., Colv=NA, keep.dendro=FALSE) it still plots the unwanted dendrogram on rows.
For now I'm going with pheatmap(..., cluster_cols=FALSE, cluster_rows=FALSE) and manually presorting my table, like this guy: Order of rows in heatmap?
Addendum: to display the value inside each cell, see: display a matrix, including the values, as a heatmap . I didn't need that but it's nice-to-have.
With pheatmap you can use options treeheight_row and treeheight_col and set these to 0.
just another option you have not mentioned...package bipartite as it is as simple as you say
library(bipartite)
mat<-matrix(c(1,2,3,1,2,3,1,2,3),byrow=TRUE,nrow=3)
rownames(mat)<-c("a","b","c")
colnames(mat)<-c("a","b","c")
visweb(mat,type="nested")
I need to be able to lookup based on the full key or part of the key..
e.g. I might store keys like 10,20,30,40 11,12,30,40, 12,20,30,40
I want to be able to search for 10,20,30,40 or 20,30,40
What is the best data structure for achieving this..best for time.
our programming language is Java..any pointers for open source projects will be appreciated..
Thanks in advance..
If those were the actual numbers I'd be working with, I'd use an array where a given index contains an array of all records that contain the index. If the actual numbers were larger, I'd use a hash table employed the same way.
So the structure would look like (empty indexes elided, in the case of the array implementation):
10 => ((10,20,30,40)),
11 => ((11,12,30,40)),
12 => ((11,12,30,40), (12,20,30,40)),
20 => ((10,20,30,40), (12,20,30,40)),
30 => ((10,20,30,40), (11,12,30,40), (12,20,30,40)),
40 => ((10,20,30,40), (11,12,30,40), (12,20,30,40)),
It's not clear to me whether your searches are inclusive (OR-based) or exclusive (AND-based), but either way you look up the record groups for each element of the search set; for the inclusive search you find their union, and for the exclusive search you find their intersection.
Since you seen to care about retrieval time over other concerns (such as space), I suggest you use a hashtable and you enter your items several times, once per subkey. So you'd put("10,20,30,40",mydata), then put("20,30,40",mydata) and so on (of course this would be a method, you're not going to manually call put so many times).
Use a tree structure. Here is an open source project that might help ... written in Java :-)
http://suggesttree.sourceforge.net/