I'm quite new to MQL so this may be a misunderstanding.
This code:
Print( TimeToStr( iTime(NULL,PERIOD_M5,i), TIME_DATE|TIME_MINUTES), iOpen(NULL,PERIOD_M5,i), iHigh(NULL,PERIOD_M5,i), iLow(NULL,PERIOD_M5,i), iClose(NULL,PERIOD_M5,i) );
Prints this:
2023.01.05 23:25, 0.91648, 0.91678, 0.91636, 0.91676
If I export data from the History Center I get slightly different numbers:
2023.01.05T23:25, 0.91646 ,0.91675, 0.91633 ,0.91675, 146
The values are just a tiny bit smaller. This is consistent - ALL of the values exported from the History Center are a bit lower than what I see when I examine the data with iOpen() etc. The difference seems to range from 0.1 to 0.3 pips.
I assume this is a Bid vs Ask thing. Is it? I understand the iOpen() etc returns Bid prices. But does the History database contain both Bid and Ask? Is there a way to see both prices?
Or it it just guessing? If so, it does not seem to be adjusting the prices consistently.
Edit: I am running in the Strategy Tester.
Edit2: Today I downloaded a bunch of M1 data from Dukascopy and imported it into MT4 History Center. Now I get exactly the results I expect from my program.
But my question stands, about the data MT4 downloads from the broker.
Related
I have a list of abstracts and articles approx 500 in csv each paragraph contains approx 800 to 1000 words whenever I build vocab and print with words giving none and how I can improve results?
lst_doc = doc.translate(str.maketrans('', '', string.punctuation))
target_data = word_tokenize(lst_doc)
train_data = list(read_data())
model = gensim.models.doc2vec.Doc2Vec(vector_size=50, min_count=2, epochs=40)
train_vocab = model.build_vocab(train_data)
print(train_vocab)
{train = model.train(train_data, total_examples=model.corpus_count,
epochs=model.epochs) }
Output:
None
A call to build_vocab() only builds the vocabulary inside the model, for further usage. That function call doesn't return anything, so your train_vocab variable will be Python None.
So, the behavior you're seeing is as expected, and you should say more about what your ultimate aims are, and what you'd want to see as steps towards those aims, if you're stuck.
If you want to see reporting of the progress of your calls to build_vocab() or train(), you can set the logging level to INFO. This is always a usually a good idea working to learn a new library: even if initially the copious info shown is hard to understand, by reviewing it you'll start to see the various internal steps, and internal counts/timings/etc, that hint whehter things are doing well or poorly.
You can also examine the state of the model and its various internal properties after the code has run.
For example, the model.wv property contains, after build_vocab(), a Gensim KeyedVectors structure holding all the untrained ready-for-training vectors. You can ask for its length (len(model.wv) or examine the discovered active list of words (model.wv.index_to_key).
Other comments:
It's not clear your 1st two lines – assigning into lst_doc and target_data – affect anything further, since it's unclear what read_data() might be doing to fill the train_corpus.
Often low min_count values worsen results, by including more words that have so few usage examples that they're little more than noise during training.
only 500 documents is rather small compared to most published work showing impressive results with this algorithm, which uses tens-of-thousands of documents (if not millions). So, keep in mind that results on such a small dataset may be unrepresentative of what's possible with a larger corpus - in terms of quality, optimal parameters, etc.
This is actually part of my thesis research, where I have to run a time series analysis on pollution and economic growth of a single country.
I have data of over 144 years of the two variables with each value representing a single year. I imported, set the values as numeric and attached the dataset through the console and ran:
ts_gdp= (data=`GDP per capita, start=1871,end=2014,frequency=1, names=gdp)
I get to see all the values for the first variable and then follow up with the stl() but I get this error. Any clues why this shows up, although I have set the frequency=1, which is the number of observations for the unit of time, in this case a year? Thank you in advance!
Error in stl(GDP, s.window = "periodic") :
series is not periodic or has less than two periods
first time user of this forum - guidance on how to provide enough information is very appreciated. I am trying to replicate the presentation of data used in the Medical education field. This will help improve the quality of examiners' marking of trainees in a Clinical Exam. What I would like to communicate will be similar to what is already communicated in the College of General Practitioners regarding one of their own exams, please see www.gp10.com.au/slides/thursday/slide29.pdf to help understand what it is I want to present. I have access to Excel, SPSS and R, so any help with any of these would be great. However as a first attempt I have used SPSS and created 3 variables: dummy variable, a "station score" and a "global rating score"(GRS). The "station score"(ST) is a value between 0 and 10 (non-integers) and is on the y-axis similar to the pdf presentation of "Candidate Final Marks". The x-axis is the "global rating scale", an integer from 1 to 6 and is represented in the pdf as the "Overall Performance Scale". When I use SPSS's boxplot I get a boxplot as depicted.
.
What I would like to do is overlay a single examiners own scoring of X number of examinees. So for one examiner (examiner A) provided the following marks:
ST: 5.53,7.38,7.38,7.44,6.81
GRS: 3,4,4,5,3
(this is transposed into two columns).
Whether it be SPSS, Excel or R how would I be able to overlay the box and whisker plots with the individual data points provided by the one examiner? This would help show the degree to which the examiners' marking styles are in concordance with the expected distribution of ST scores across GRS. Any help greatly appreciated! I like Excel graphics but I have found it very difficult to work with when choosing the examiners' data as a separate series - somehow the examiners' GRS scores do not line up nicely on the x-axis. I am very new to R but am also very interested in R, and would expend time to get a good result in R if a good result is viable. I understand JMP may be preferable for this type of thing but access to this may not be possible.
We have an application that prints 2 invoice copies - 1 on white (for the cust) and 1 on blue (for us).
We print a LOT of these so we are getting a printer with 3 big trays. One tray (tray 5) holds 4000 sheets and the other two (trays 3 and 4) are a tandem set holding 1600 and 2000 sheets. The application automatically generates the invoice and sends one document to the tray with the white paper and one to the tray with the blue paper.
The user has no input in this process.
Now, my problem is this - if I specifically send the blue copy to tray 3 and there is no paper in tray 3, the job will go on hold until someone loads it up even though tray 4 has 2000 more sheets ready to go. On the other hand, if I tell the printer to print on Blue 8 1/2x11" paper, it is smart enough to know that that type of paper is in both trays and to pull from either one until they are both empty. So, I want to change our application to select a paper type/size and color instead of a specific tray.
The program is written in Delphi and I have been looking at the DEVMODE structure returned by TPrinter.GetPrinter. The DEVMODE structure has a memory size in dmDriverExtra that indicates how much extra data the print driver is adding to the structure for its own storage.
Does anyone know of anyway to access this data and make changes to it? If you have examples in other languages, I can probably adapt it to Delphi so anything will help.
There are actually two different items in the questions:
How to set the pater size and type:
PaperSize would be stored in dmPaperSize (value DMPAPER_LETTER)
PaperType is a bit more difficult. I'd guess that it's in dmMediaType (use DeviceCapabilities to retrieve available media types and their names)
How to access / edit "DriverExtra" data:
In short: don't!
A bit longer: dmDriverExtra is described as "Contains the number of bytes of private driver-data that follow this structure". So this data is private to the driver (which means that you need very good documentation for the driver to actually know the format and content of this data. It's not guaranteed that different versions of the driver use the same format).
So the only thing you can do is to use a print dialog, retrieve the DevMode structure and store it for further use (however as I said: If the driver changes, this data may become invalid...)
I am using the NWS REST API as my weather service for an app I am making. I was initially reluctant to use NWS because of its bad documentation, but I couldn't resist as it is offered completely free.
Now that I am trying to use it, I am running into some difficulty. When making a request for multiple days, the minimum temperature appears nil for several days.
(EDIT: As I have been testing the API more I have found that it is not always the minimum temperatures that are nil. It can be a max temp or a precipitation, it seems completely random. If you would like to make test calls using their web interface, you can do so here: http://graphical.weather.gov/xml/sample_products/browser_interface/ndfdBrowserByDay.htm
and here: http://graphical.weather.gov/xml/sample_products/browser_interface/ndfdXML.htm)
Here is an example of a request the minimum temperatures are empty: http://graphical.weather.gov/xml/sample_products/browser_interface/ndfdBrowserClientByDay.php?listLatLon=40.863235,-73.714780&format=24%20hourly&numDays=7
Surprisingly, on their website, the minimum temperatures are available:
http://forecast.weather.gov/MapClick.php?textField1=40.83&textField2=-73.70
You'll see under the Minimum temperatures that it is filled with about 5 (sometimes less, it is inconsistent) blank fields that say <value xsi:nil="true"/>
If anybody can help me it would be greatly appreciated, using the NWS API can be a little overwhelming at times.
Thanks,
The nil values, from what I can understand of the documentation, here and here, simply indicate that the data is unavailable.
Without making assumptions about NOAA's data architecture, it's conceivable that the information available via the API may differ from what their website displays.
Missing values are represented by an empty element and xsi:nil=”true” (R2.2.1).
Nil values being returned seems to involve the time period. Notice the difference between the time-layout keys (see section 5.3.2) in 1 in these requests:
k-p24h-n7-1
k-p24h-n6-1
The data times are different.
<layout-key> element
The key is derived using the following convention:
“k” stands for key.
“p24h” implies a data period length of 24 hours.
“n7” means that the number of data times is 7.
“1” is a sequential number used to keep the layout keys unique.
Here, startDate is the factor. Leaving it off includes more time and might account for some requested data not yet being available.
Per documentation:
The beginning day for which you want NDFD data. If the string is empty, the start date is assumed to be the earliest available day in the database. This input is only needed if one wants to shorten the time window data is to be retrieved for (less than entire 7 days worth), e.g. if user wants data for days 2-5.
I'm not experiencing the randomness you mention. The folks on NOAA's Yahoo! Groups forum might be able to tell you more.