If I want to create a font with multiple style combinations, like bold AND underline, I have to place the 'or' statement between it, like in the example below:
lblArt.Font = New Font("Tahoma", 18, FontStyle.Bold Or FontStyle.Underline)
If you place bold 'and' underline, it won't work, and you only get 1 of the 2 (like how the or statement should be working), while that would be the logically way to do it. What is the reason behind this?
Boolean logic works a bit differently than the way we use the terms in English. What's happening here is that the enumerated FontStyle values are actually bit flags, and in order to manipulate bit flags, you use bitwise operations.
To combine two bit flags, you OR them together. An OR operation combines the two values. So imagine that FontStyle.Bold was 2 and FontStyle.Underline was 4. When you OR them together, you get 6—you've combined them together. In Boolean logic, you can think of an OR operation as returning "true" (i.e., setting that bit in the result) if either of the bits in the two operands are set, and "false" if neither of the bits in the two operands are set.
You can write a truth table for such an operation as follows:
| A | B | A OR B |
|---|---|--------|
| 0 | 0 | 0 |
| 0 | 1 | 1 |
| 1 | 0 | 1 |
| 1 | 1 | 1 |
Notice that the results more closely mirror what we, in informal English, would call "and". If either one has it set, then the result has it set, too.
In contrast to OR, a bitwise AND operation only returns "true" (i.e., sets that bit in the result) if both of the bits in the two operands are set. Otherwise, the result is "false". Again, a truth table can be written:
| A | B | A AND B |
|---|---|---------|
| 0 | 0 | 0 |
| 0 | 1 | 0 |
| 1 | 0 | 0 |
| 1 | 1 | 1 |
Assuming again that FontStyle.Bold has the value 2 and FontStyle.Underline has the value 4, if you AND them together, you get 0. This is because the values effectively cancel each other out. The net result is that you don't get any font styles—precisely why it doesn't work when you write FontStyle.Bold And FontStyle.Underline.
In VB, a bitwise OR operation is performed using the Or operator. The And operator performs a bitwise AND operation. So in order to do a bitwise inclusion of values, which is how you combine bit flags, you use the Or operator.
try this:
lblArt.Font = New Drawing.Font("Tahoma", _
18, _
FontStyle.Bold or FontStyle.Italic)
use "New Drawing.Font" instead of Font alone
Source
Related
I have looked at the COALESCE documentation and it mentions the typical case of using COALESCE to make default/situational parameters, e.g.
COALESCE(discount, 5)
which evaluates to 5 if discount is not defined as something else.
However, I have seen it used where COALESCE actually evaluated all the arguments, despite the documentation explicitly saying it stops evaluating arguments after the first non-null argument.
Here is an example similar to what I encountered, say you have a table like this:
id | wind | rain | snow
1 | null | 2 | 3
2 | 5 | null | 6
3 | null | 7 | 2
Then you run
SELECT *
FROM weather_table
WHERE
COALESCE(wind, rain, snow) >= 5
You would expect this to only select rows with wind >= 5, right? NO! It selects all rows with either wind, rain or snow more than 5. Which in this case is 2 rows, specifically these two:
2 | 5 | null | 6
3 | null | 7 | 2
Honestly, pretty cool functionality, but it really irks me that I couldn't find any example of this online or in the documentation.
Can anyone tell me what's going on? Am I missing something?
You would expect this to only select rows with wind >= 5, right?
No, I expect it to select rows with what the Coalesce function returns.
The Coalesce function delivers the value of the first non-null parameter. You had Coalesce(wind,rain,snow). The first row had (null,2,3), so coalesce returned 2. The second row had (5,null,6) so returned 5. The third row had (null,7,2) so returned 7.
The last two rows meet the condition >=5, so 2 rows are retrieved.
Notice that the value for snow was never returned in your example, because either wind or rain always had a value.
After writing out the question so clear, I realized what was going on myself. But I want to answer it here in case anyone else is confused.
Turns out the reason is the COALESCE function is run once for each row, which I suppose I could have known. Then it all makes sense.
It checks for each row, do I have non-null wind, if it is >= 5 I add this row to the result, if not I check if rain is non-null, and so on.
Notably though, if my table was had been like this:
id | wind | rain | snow
1 | 0 | 2 | 3
2 | 5 | 0 | 6
3 | 0 | 7 | 2
The command would have worked like I thought, and the COALESCE function completely useless, would have picked only that one row
2 | 5 | 0 | 6
equal to SELECT * FROM weather_table WHERE wind >= 5.
It only works if there are columns which are null (0 <> null).
I have a strange problem. But first, I want to match a hierarchy-based string onto the value of a column in a pandas data frame and count the occurrence of the current node and all of its children.
| index | hierarchystr |
| ----- | --------------------- |
| 0 | level0level00level000|
| 1 | level0level01 |
| 2 | level0level02level021|
| 3 | level0level02level021|
| 4 | level0level02level020|
| 5 | level0level02level021|
| 6 | level1level02level021|
| 7 | level1level02level021|
| 8 | level1level02level021|
| 9 | level2level02level021|
Assume that there are 300k lines. Each node can have multiple children with again multiple children so on and so forth (here represented by level0-2 strings). Now I have a separate hierarchy where I extract the hierarchy strings from. Now to the problem:
#hstrs = ["level0", "level1", "level0level01", "level0level02", "level0level02level021"]
pat = "|".join(hstrs)
s = df.hierarchystr.str.extract('(' + pat + ')', expand=True)[0]
df1 = df.groupby(s).size().reset_index(name='Count')
df1 = df1[df1 > 200]
size = len(df1)
The size of the found matched substrings with occurrence greater than 200 differ every RUN! "level0" should match every row where the hierarchy str level0 is included and should build a group with all its subchildren and that size needs to be greater than 200.
Edit:// levelX is just an example, i have thousands of nodes, with different names and again thousands of different subchilds. The hstrs strings do not include each other, besides the parent nodes. (E.g. "parent1" is included in "parent1subchild1" and "parent1subchild2")
I traced it back to a different order of the hierarchy strings in the array hstrs. So I changed the code and compare each substring individually:
for hstr in hstrs:
s = df.hierarchystr.str.extract('(' + hstr + ')', expand=True)
s2 = s.count()
s3 = s2.values[0]
if s3 > 200:
list.append(hstr)
This is slow as hell, but the result sticks the same, no matter which order hstrs has. But for efficiency is it possible to do the same with only one regex matching group, all at once for all hstrs?
Edit://
expected output would be:
|index| 0 | Count |
|-----|---------------------|-------|
|0 |level0 | 5 |
|1 |level1 | 3 |
|2 |level0level01 | 1 |
|3 |level0level02 | 4 |
|4 |level0level02level021| 3 |
Edit2://
it has something to do with the ordering of hstrs. I think with the match and stop after the first match the behavior of the extract method. If the ordering is different the hierarchy strings in the pat will be matched differently which results in different sizes of each group. A high hierarchy (short str) will be matched first, the lower hierarchy levels in the same pat won't be matched again. But IDK what to do against this behavior.
Edit3://
an alternative would be, but is also slow as hell:
for hstr in hstrs:
s = df[df.hierarchystr.str.contains(fqn)]
s2 = s.count()
s3 = s2.values[0]
if s3 > 200:
beforeset.append(fqn)
Edit4://
I think what I am searching for is the opportunity to do a "group_by" with "contains" or "is in" for the hstrs. I am glad for every Idea. :)
Edit5://
Found a simple, but not satisfying alternative (but faster than the previous tries):
containing =[item for hierarchystr in df.hierarchystr for item in hstrs if item in hierarchystr]
containing = Counter(containing)
df1 = pd.DataFrame([containing]).T
nodeNamesWithOver200 = df1[df1 > 200].dropna().index.values
As I cannot attach a conditional formatting on a Table, I need an abstract function to chech if a set of records or all records have errors inside, and show these errors into forms and/or reports.
Because, to achieve this goal in the 'standard' mode, I have to define the rule [○for a field of a table every time I use that field in a control or report, and this means the need to repeate the same things an annoying lot of times, not to tell about introducing errors and resulting in a maintenance nightmare.
So, my idea is to define all the check for all the tables and their rows in an CheckError-table, like the following fragment related to the table 'Persone':
TableName | FieldName | TestNumber | TestCode | TestMessage | ErrorType[/B][/COLOR]
Persone | CAP | 4 | len([CAP]) = 0 or isnull([cap]) | CAP mancante | warning
Persone | Codice Fiscale | 1 | len([Codice Fiscale]) < 16 | Codice fiscale nullo o mancante | error
Persone | Data di nascita | 2 | (now() - [Data di nascita]) < 18 * 365 | Minorenne | info
Persone | mail | 5 | len([mail)] = 0 or isnull([mail] | email mancante | warning
Persone | mail | 6 | (len([mail)] = 0 or isnull([mail]) | richiesto l'invio dei referti via e- mail, | error
| | | and [modalità ritiro referti] = ""e-mail"" | ma l'indirizzo e-mail è mancante |
Persone | Via | 3 | len([Via]) = 0 or isnull([Via]) | Indirizzo mancante | warning
Now, in each form or report which use the table Persona, I want to set an 'onload' property to a function
' to validate all fields in all rows and set the appropriate bg and fg color
Private Sub Form_Open(Cancel As Integer)
Call validazione.validazione(Form, "Persone", 0)
End Sub
' to validate all fields in the row identified by ID and set the appropriate bg and fg color
Private Sub Codice_Fiscale_LostFocus()
Call validazione.validazione(Form, "Persone", ID)
End Sub
So, the function validazione, at a certain point, as exactly one row for the table Persone, and the set of expressions described in the column [TestCode] above.
Now, I need to logically evaluate the TestString against the table row, to obtain a true or a false.
If true, I'll set the fg and bg color of the field as normal
if false, I'll set the the fg and bg color as per error, info or warning, as defined by the column [ErrorType] above.
All the above is easy, ready, and running, except for the red statement above:
How can I evaluate the teststring against the table row, to obtain a result?
Thank you
Paolo
We use Lucene.net for indexing. One of the fields that we index, is a numeric field with the values 1 to 6 and 9999 for not set.
When using Luke to explore the index, we see terms that we do not recognize. The index contains a total of 38673 documents, and Luke shows the following top ranked terms for this field:
Term | Rank | Field | Text | Text (decoded as numeric-int)
1 | 38673 | Axis | x | 0
2 | 38673 | Axis | p | 0
3 | 38673 | Axis | t | 0
4 | 38673 | Axis | | | 0
5 | 19421 | Axis | l | 0
6 | 19421 | Axis | h | 0
7 | 19421 | Axis | d# | 0
8 | 19252 | Axis | ` N | 9999
9 | 19252 | Axis | l | 8192
10 | 19252 | Axis | h ' | 9984
11 | 19252 | Axis | d# p | 9984
12 | 18209 | Axis | ` | 4
13 | 950 | Axis | ` | 1
14 | 116 | Axis | ` | 5
15 | 102 | Axis | ` | 6
16 | 26 | Axis | ` | 3
17 | 18 | Axis | ` | 2
We find the same pattern for other numeric fields.
Where does the unknown values come from?
NumericFields are indexed using a trie structure. The terms you see are part of it, but will not return results if you query for them.
Try indexing your NumericField with a precision step of Int32.MaxValue and the values will go away.
NumericField documentation
... Within Lucene, each numeric value is indexed as a trie structure, where each term is logically assigned to larger and larger pre-defined brackets (which are simply lower-precision representations of the value). The step size between each successive bracket is called the precisionStep, measured in bits. Smaller precisionStep values result in larger number of brackets, which consumes more disk space in the index but may result in faster range search performance. The default value, 4, was selected for a reasonable tradeoff of disk space consumption versus performance. You can use the expert constructor NumericField(String,int,Field.Store,boolean) if you'd like to change the value. Note that you must also specify a congruent value when creating NumericRangeQuery or NumericRangeFilter. For low cardinality fields larger precision steps are good. If the cardinality is < 100, it is fair to use Integer.MAX_VALUE, which produces one term per value. ...
More details on the precision step available in the NumericRangeQuery documentation:
Good values for precisionStep are depending on usage and data type:
• The default for all data types is 4, which is used, when no
precisionStep is given.
• Ideal value in most cases for 64 bit data
types (long, double) is 6 or 8.
• Ideal value in most cases for 32 bit
data types (int, float) is 4.
• For low cardinality fields larger
precision steps are good. If the cardinality is < 100, it is fair to use •Integer.MAX_VALUE (see below).
• Steps ≥64 for long/double and
≥32 for int/float produces one token per value in the index and
querying is as slow as a conventional TermRangeQuery. But it can be
used to produce fields, that are solely used for sorting (in this case
simply use Integer.MAX_VALUE as precisionStep). Using NumericFields
for sorting is ideal, because building the field cache is much faster
than with text-only numbers. These fields have one term per value and
therefore also work with term enumeration for building distinct lists
(e.g. facets / preselected values to search for). Sorting is also
possible with range query optimized fields using one of the above
precisionSteps.
EDIT
little sample, the index produced by this will show terms with value 8192, 9984, 1792, etc in luke, but using a range that would include them in the query doesnt produce results:
NumericField number = new NumericField("number", Field.Store.YES, true);
Field regular = new Field("normal", "", Field.Store.YES, Field.Index.ANALYZED);
IndexWriter iw = new IndexWriter(FSDirectory.GetDirectory("C:\\temp\\testnum"), new StandardAnalyzer(), true);
Document doc = new Document();
doc.Add(number);
doc.Add(regular);
number.SetIntValue(1);
regular.SetValue("one");
iw.AddDocument(doc);
number.SetIntValue(2);
regular.SetValue("one");
iw.AddDocument(doc);
number.SetIntValue(13);
regular.SetValue("one");
iw.AddDocument(doc);
number.SetIntValue(2000);
regular.SetValue("one");
iw.AddDocument(doc);
number.SetIntValue(9999);
regular.SetValue("one");
iw.AddDocument(doc);
iw.Commit();
IndexSearcher searcher = new IndexSearcher(iw.GetReader());
NumericRangeQuery rangeQ = NumericRangeQuery.NewIntRange("number", 1, 2, true, true);
var docs = searcher.Search(rangeQ);
Console.WriteLine(docs.Length().ToString()); // prints 2
rangeQ = NumericRangeQuery.NewIntRange("number", 13, 13, true, true);
docs = searcher.Search(rangeQ);
Console.WriteLine(docs.Length().ToString()); // prints 1
rangeQ = NumericRangeQuery.NewIntRange("number", 9000, 9998, true, true);
docs = searcher.Search(rangeQ);
Console.WriteLine(docs.Length().ToString()); // prints 0
Console.ReadLine();
I want to represent the list "hi", "hello", "goodbye", "good day", "howdy" (with that order), in a SQL table:
pk | i | val
------------
1 | 0 | hi
0 | 2 | hello
2 | 3 | goodbye
3 | 4 | good day
5 | 6 | howdy
'pk' is the primary key column. Disregard its values.
'i' is the "index" that defines that order of the values in the 'val' column. It is only used to establish the order and the values are otherwise unimportant.
The problem I'm having is with inserting values into the list while maintaining the order. For example, if I want to insert "hey" and I want it to appear between "hello" and "goodbye", then I have to shift the 'i' values of "goodbye" and "good day" (but preferably not "howdy") to make room for the new entry.
So, is there a standard SQL pattern to do the shift operation, but only shift the elements that are necessary? (Note that a simple "UPDATE table SET i=i+1 WHERE i>=3" doesn't work, because it violates the uniqueness constraint on 'i', and also it updates the "howdy" row unnecessarily.)
Or, is there a better way to represent the ordered list? I suppose you could make 'i' a floating point value and choose values between, but then you have to have a separate rebalancing operation when no such value exists.
Or, is there some standard algorithm for generating string values between arbitrary other strings, if I were to make 'i' a varchar?
Or should I just represent it as a linked list? I was avoiding that because I'd like to also be able to do a SELECT .. ORDER BY to get all the elements in order.
As i read your post, I kept thinking 'linked list'
and at the end, I still think that's the way to go.
If you are using Oracle, and the linked list is a separate table (or even the same table with a self referencing id - which i would avoid) then you can use a CONNECT BY query and the pseudo-column LEVEL to determine sort order.
You can easily achieve this by using a cascading trigger that updates any 'index' entry equal to the new one on the insert/update operation to the index value +1. This will cascade through all rows until the first gap stops the cascade - see the second example in this blog entry for a PostgreSQL implementation.
This approach should work independent of the RDBMS used, provided it offers support for triggers to fire before an update/insert. It basically does what you'd do if you implemented your desired behavior in code (increase all following index values until you encounter a gap), but in a simpler and more effective way.
Alternatively, if you can live with a restriction to SQL Server, check the hierarchyid type. While mainly geared at defining nested hierarchies, you can use it for flat ordering as well. It somewhat resembles your approach using floats, as it allows insertion between two positions by assigning fractional values, thus avoiding the need to update other entries.
If you don't use numbers, but Strings, you may have a table:
pk | i | val
------------
1 | a0 | hi
0 | a2 | hello
2 | a3 | goodbye
3 | b | good day
5 | b1 | howdy
You may insert a4 between a3 and b, a21 between a2 and a3, a1 between a0 and a2 and so on. You would need a clever function, to generate an i for new value v between p and n, and the index can become longer and longer, or you need a big rebalancing from time to time.
Another approach could be, to implement a (double-)linked-list in the table, where you don't save indexes, but links to previous and next, which would mean, that you normally have to update 1-2 elements:
pk | prev | val
------------
1 | 0 | hi
0 | 1 | hello
2 | 0 | goodbye
3 | 2 | good day
5 | 3 | howdy
hey between hello & goodbye:
hey get's pk 6,
pk | prev | val
------------
1 | 0 | hi
0 | 1 | hello
6 | 0 | hi <- ins
2 | 6 | goodbye <- upd
3 | 2 | good day
5 | 3 | howdy
the previous element would be hello with pk=0, and goodbye, which linked to hello by now has to link to hey in future.
But I don't know, if it is possible to find a 'order by' mechanism for many db-implementations.
Since I had a similar problem, here is a very simple solution:
Make your i column floats, but insert integer values for the initial data:
pk | i | val
------------
1 | 0.0 | hi
0 | 2.0 | hello
2 | 3.0 | goodbye
3 | 4.0 | good day
5 | 6.0 | howdy
Then, if you want to insert something in between, just compute a float value in the middle between the two surrounding values:
pk | i | val
------------
1 | 0.0 | hi
0 | 2.0 | hello
2 | 3.0 | goodbye
3 | 4.0 | good day
5 | 6.0 | howdy
6 | 2.5 | hey
This way the number of inserts between the same two values is limited to the resolution of float values but for almost all cases that should be more than sufficient.