I am trying to create a number sequencing formula in excel similar to a folder structure where each number can potentially contain many dots indicating which "folder" it lies within. For instance:
1.0
1.1
1.2
1.2.1
1.2.2
1.2.3
1.3
2.0
2.1
2.1.1
2.1.2
I have tried several different ways by using MAX formulas (for instance +MAX($A$1:B3)+1) and tried to combine these in different ways but I can's find a solution that works. Any help is much appreciated.
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I am using open-CV - 2.4 with python-3. I am able to show multiple images at the same time (8 of them and, I don't want to reduce the number). But many times, these windows overlap each other. So, I want to be able to put them all in the same windowj.
So, to do this I used the function np.hstack(). Now, my problem is that I don't know how to show their names(i.e I would like to give the names to these windows individually, the way we do using cv2.imshow("name", window) ).
Also, I want to avoid using GUI libraries like tkinter and qt.
Thanks in advance.
I know that similar questions have been asked many times, but still I have not found a satisfactory answer for what I am looking for. I want to be able to compare two versions of the same image, in order to detect the amount of perceptual artifacts resulting from JPEG compression, without any further changes (i.e., no crops, no rotation...). I mean, not just the histogram or the number of pixels that are different (those would be probably easy to get from Pillow), but instead I would like to be able to obtain some kind of measure of their overall visual impact.
Reading through some articles in SO and in other places, I have found multiple references to SSIM algorithm, that seems to do precisely what I am looking for. There is even a Python (https://github.com/jterrace/pyssim), but the problem is that all those implementations seem to depend on packages that can't be installed in some of my target devices. I am using Pythonista 3 on iOS, which includes Pillow 2.9.0 and numpy, but scipy (required by pysimm) is not compatible.
Is there any other viable way to calculate SIMM or a similar comparison value that does not require anything more that Python 3.6, Pillow and/or Numpy 1.8.0?
I'm using OpenTBS plugin for TinyButStront template engine more than 4 years, and almost since beginning, I found problem with merging XLSX files with more than 10000 rows in source data array.
Until now, I've used OpenTBS v.1.9.0, and solution which fix this problem, found here : http://www.tinybutstrong.com/forum.php?thr=3256
But, I decided update OpenTBS from v.1.9.0 to latest v.1.9.11, and found that my problem with large data source still not fixed, even that Skrol29 says that in v.1.9.2 "6 times faster when saving XLSX merged sheets with numerous rows."
I've used same fix from http://www.tinybutstrong.com/forum.php?thr=3256
in new v.1.9.11 and it still works and merge numerous rows way faster.
So, Skrol29, can you review again this solution and apply into official release ?
The fix submitted at http://www.tinybutstrong.com/forum.php?thr=3256 has not been implemented as is in OpenTBS because is uses regexp functions. Regexp are smart and powerful, nevertheless they assumes some string disposition that may sometime be different. So they may be not as rigorous as we can expect.
Thus TBS and OpenTBS simple XML parsing has been thoroughly tested and are more trusted.
So for this problem of performance with Ms Excel worksheets merging, it is recommended to use the command OPENTBS_RELATIVE_CELLS supported since OpenTBS 1.9.2.
Yes, Koogra only reads. EPPlus only supports .xlsx and is buggy in edge cases.
What else should one know for choosing between them?
Is one of them much slower than others?
NPOI seems way to complicated and is a Java port, so is it worth
using?
Should one use EPPlus for .xlsx and NPOI for .xls?
What is the general knowledge about them today?
Jet/ACE OLE DB either read worksheet as strings, or as typed columns, so you either lose numbers precision or you must have headers in the first row. Thus, they are to be avoided.
No library supports XLSB.
Speed.
For a large XLS, the time of reading for NPOI:Jet:Koogra:EDR is 14:8:7:5.
For the same XLSX, the time for EPPlus:NPOI:Koogra:EDR is 52:36:20:16.
For relatively small files with many tabs EPPlus can be a bit faster than EDR.
Errors (#DIV/0!, #VALUE!) etc.
EDR and Koogra don't explicitly support errors. EDR reads them as usual strings, Koogra -- as blank cells.
NPOI and EPPlus do.
Koogra reads dates as [OLE date] numbers and they are undistinguishable from real numbers. Also it sometimes reads numbers with many decimals digits incorrectly. EDR gets this fine. So, no to Koogra.
NPOI is complicated, 5 dlls of 4 MB. Koogra and EDR are simple, 200 KB and two dlls (themselves and zip) each.
EDR works as a IDataReader, so it reads data sequentially. It also has built-in function to get a DataSet. With sequential read yoou can only go through first sheet in the work book. Koogra supports random access to cells and sheets.
EDR is based on SharpZip, Koogra is based on Ionic.Zip. The former allows to open a file from .zip a Stream which can be benefical for other parts of the project.
I haven't looked at writing aspects of NPOI, so without the need to distinguish errors, I would go with EPPlus for .xlsx and with EDR for reading .xls.
I am using cartographic representations to symbolize roads such that both directions are visible. I need to convert this to KML. However, the Layer to KML tool from ArcToolbox creates an empty file. Is it possible to convert cartographic representations to KML? Thanks a lot!
There are many options.
Layer to KML - this should work and is moderately easy
Arc2Earth - You can get a limited community edition for free
Excel based tools - get your data in a spreadsheet and upload to any online tool or download an offline based implementation
Google Fusion Tables - requires spreadsheet type data
Python - Either as string templates or using something like simplekml