I would like to store a time range (without dates) like "HH:MM-HH:MM".
Can you give me a hint, how can I implement it most easily? Maybe there is a way to use DateRangeField for this aim or something else.
Thanks for your spend time!
Time without date doesn't make much since if you ever need a range that span mid-night (days) You could always convert to text using to_char(<yourtimestamp>,'hh24.mi:ss') or extract the individual parts. Unfortunately Postgres does not provide an extract(time from <yourtimestamp>) function. The following function provides essentially that.
create or replace
function extract_tod(date_time_in timestamp without time zone)
returns time
language sql
as $$
select to_char(date_time_in, 'hh24:mi:ss')::time;
$$;
See here for timestatamp ranges and here for their associated functions. As for how to store then just store with the date
as a standard TIMESTAMP (date + time).
Related
Reference: https://github.com/offa/influxdb-cxx
It is easy to delete record by time using CLI interface,
delete from imagetable where time='2022-11-16T19:42:41.945508272Z'
but I am not able to figure out how to do the same with influxdb-cxx. i.e. not able to access the time through C++ interface.
e.g. Tags can be accessed with function points[0].getTags() but how to access the time ?
Have already tried to access it with points[0].getTimestamp() but not able to print it in this format in C++ 2022-11-17T03:37:25.934547412Z
can anyone please help ? Thanks in advance.
In influxdb-cxx you can use InfluxDB::execute method to execute InfluxQL statements like from your example for CLI interface. Regarding timestamps, they are saved as std::chrono::time_point<std::chrono::system_clock> (source) in the library's Point class, which denotes Unix (epoch) time excluding leap seconds (which is what timestamps in InfluxDB represent). Your example uses RFC3339 notation to provide timestamp, but InfluxQL also directly understands "nanosecond count since epoch" notation for it (example). So, it isn't necessary to represent Point's timepoint in RFC3339 notation to use it in execute command (which is possible, but harder and reduntant), you can just use standard C++ chrono library functions to get nanoseconds since epoch for given timepoint. Example:
using namespace std::chrono;
auto nsEpoch = duration_cast<nanoseconds>(points[0].getTimestamp().time_since_epoch()).count();
idb->execute("delete from imagetable where time=" + std::to_string(nsEpoch));
I have a dataset that I am trying to manipulate in GraphLab. I want to convert a UNIX Epoch timestamp from the input file (converted to an SFrame) into a human readable format so I can do analysis based on hour of day and day of week.
time_array is the column/feature of the SFrame sf representing the timestamp, I have broken out just the EPOCH time to simplify things. I know how to convert the time of one row, but I want a vector operation. Here is what I have for one row.
time_array = sf['timestamp']
datetime.datetime.fromtimestamp(time_array[0]).strftime('%Y-%m-%d %H')
You can also get parts of the time from the timestamp to create another column, by which to filter (e.g., get the hour):
sf['hour'] = [x.strftime('%H')for x in sf['timestamp']]
So after staring at this for awhile and then posting the question it came to me, hopefully someone else can benefit as well. Use the .apply method with the datetime.datetime() function
sf['date_string'] = sf['timestamp'].apply(lambda x: datetime.datetime.fromtimestamp(x).strftime('%Y-%m-%d %H'))
you can also use the split_datetime API to split the timestamp to multiple columns:
split_datetime('timestamp',limit=['hour','minute'])
I am saving the fingerprints in a field "blob", then wonder if the only way to compare these impressions is retrieving all prints saved in the database and then create a vector to check, using the function "identify_finger"? You can check directly from the database using a SELECT?
I'm working with libfprint. In this code the verification is done in a vector:
def test_identify():
cur = DB.cursor()
cur.execute('select id, fp from print')
id = []
gallary = []
for row in cur.fetchall():
data = pyfprint.pyf.fp_print_data_from_data(str(row['fp']))
gallary.append(pyfprint.Fprint(data_ptr = data))
id.append(row['id'])
n, fp, img = FingerDevice.identify_finger(gallary)
There are two fundamentally different ways to use a fingerprint database. One is to verify the identity of a person who is known through other means, and one is to search for a person whose identity is unknown.
A simple library such as libfprint is suitable for the first case only. Since you're using it to verify someone you can use their identity to look up a single row from the database. Perhaps you've scanned more than one finger, or perhaps you've stored multiple scans per finger, but it will still be a small number of database blobs returned.
A fingerprint search algorithm must be designed from the ground up to narrow the search space, to compare quickly, and to rank the results and deal with false positives. Just as a Google search may come up with pages totally unrelated to what you're looking for, so too will a fingerprint search. There are companies that devote their entire existence to solving this problem.
Another way would be to have a mysql plugin that knows how to work with fingerprint images and select based on what you are looking for.
I really doubt that there is such a thing.
You could also try to parallelize the fingerprint comparation, ie - calling:
FingerDevice.identify_finger(gallary)
in parallel, on different cores/machines
You can't check directly from the database using a SELECT because each scan is different and will produce different blobs. libfprint does the hard work of comparing different scans and judging if they are from the same person or not
What zinking and Tudor are saying, I think, is that if you understand how does that judgement process works (which is by the way, by minutiae comparison) you can develop a method of storing the relevant data for the process (the *minutiae, maybe?) in the database and then a method for fetching the relevant values -- maybe a kind of index or some type of extension to the database.
In other words, you would have to reimplement the libfprint algorithms in a more complex (and beautiful) way, instead of just accepting the libfprint method of comparing the scan with all stored fingerprint in a loop.
other solutions for speeding your program
use C:
I only know sufficient C to write kind of hello-world programs, but it was not hard to write code in pure C to use the fp_identify_finger_img function of libfprint and I can tell you it is much faster than pyfprint.identify_finger.
You can continue doing the enrollment part of the stuff in python. I do it.
use a time / location based SELECT:
If you know your users will scan their fingerprints with more probability at some time than other time, or at some place than other place (maybe arriving at work at some time and scanning their fingers, or leaving, or entering the building by one gate, or by other), you can collect data (at each scan) for measuring the probabilities and creating parallel tables to sort the users for their probability of arriving at each time and location.
We know that identify_finger tries to identify fingers in a loop with the fingerprint objects you provided in a list, so we can use that and give it the objects sorted in a way in which the more likely user for that time and that location will be the first in the list and so on.
I have a date stored in the format dd-mm-yyyy. I want to store the day, date and year as individual variables, while getting rid of any leading zeros (e.g. "09-09-2010" is stored as 9, 9, 2010).
I attempted to use the code on this page to split the date by dashes, but it is throwing expression errors.
Some people, when confronted with a
problem, think "I know, I'll use
regular expressions." Now they have
two problems.
Coding Horror: Regular Expressions: Now You Have Two Problems
Investigate the ColdFusion functions month(date), day(date) and year(date).
Update: you can pass a string to these functions so long as CF can turn into a date.
When you say that you have a date
stored in the format dd-mm-yyyy
are you sure you aren't confusing this with the way that your database UI is presenting it to you or are you actually storing the date in this format (for example, by writing it this way to a text file or a varchar column rather than a DateTime column)?
The reason I ask is that if a date is stored in a database as a date then CF will represent it as a date irrespective of how it appears in, say, SQL Management Studio. If this is the case then you can simply split the parts out using DatePart("datepart", "date").
If you have a date in a text format (such as from a form submission or because it has been stored as plain text) then you should be able to parse it in to a DateTime object using LSParseDateTime() and then use the DatePart(...) method on it to split out the parts.
See http://livedocs.adobe.com/coldfusion/8/htmldocs/help.html?content=functions_c-d_30.html
(sorry, can't post the URL to the other function due to lack of SO points!)
for the documentation on this.
As an aside, if you are using SQL2005 (or later) then you can create computed columns on the date field in order to split out the day, year and month at the database level. I thought I'd mention this just in case it proves useful.
Steve
If you're working with a string in that format, there's no need for regular expressions.
myDate = "13-12-2010";
theDay = listGetAt(myDate,1,"-");
theMonth = listGetAt(myDate,2,"-");
theYear = listGetAt(myDate,3,"-");
Using the val() function will also drop leading zeroes, if any.
What is the optimal query to obtain all the records for one specific day?
In my Weather model, 'timestamp' is a standard DateTimeField.
I'm currently using
start = datetime.datetime(2009, 1, 31)
end = start + datetime.timedelta(hours=23, minutes=59, seconds=59)
Weather.objects.filter(timestamp__range=(start, end))
but wonder if there is a more efficient method.
The way it's done in django.views.generic.date_based is:
{'date_field__range': (datetime.datetime.combine(date, datetime.time.min),
datetime.datetime.combine(date, datetime.time.max))}
There should soon be a patch merged into Django that will provide a __date lookup for exactly this type of query (http://code.djangoproject.com/ticket/9596).
Do not prematurely optimize
Index columns that your queries are based on frequently
Optimize expensive columns, like add auto-updated year, month, and day values (maybe just as a string) if and only if tests show it provides a significant speedup and only after using what already works NOW and determining it isn't viable.