Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Axis limits cannot be NaN or InF when using Gacos correction #401

Open
faraksoch1881 opened this issue Sep 6, 2024 · 7 comments
Open

Axis limits cannot be NaN or InF when using Gacos correction #401

faraksoch1881 opened this issue Sep 6, 2024 · 7 comments

Comments

@faraksoch1881
Copy link

faraksoch1881 commented Sep 6, 2024

Hello Dr. Yumorishita
I changed the "do03op_GACOS="y"" in batch script file and used the command 'LiCSBAS01_get_geotiff.py --get_gacos" to download the Gacos data set in the default folder. I downloaded the missing files manually and placed them inside same folder. I manually downloaded files by using input of lon1\lon2\lat1\lat2 more then frame size to make sure that it covers entire area ( as i read form comments that there will be errors if Gacos data don't contain study area" though my study is very small which i used clip property to crop image form whole frame. Just for information the file i downloaded from Gacos website is named as ztd..tif and files automatically downloaded has a name sltd.geo.tif, if it is something needs to be taken notice.
Also the file size the LiCSBAS downloaded is around 13 MB but file i downloaded manually from Gacos webiste is not more then 500 KB.

then i ran the batchscript and now and it is giving me an error of

`
File "/home/sagar/anaconda3/lib/python3.11/site-packages/matplotlib/axes/_base.py", line 3585, in _validate_converted_limits
raise ValueError("Axis limits cannot be NaN or Inf")
ValueError: Axis limits cannot be NaN or Inf

`

Here is my logfile
202409061743batch_LiCSBAS_01_16.log

and my file directory image
file_directory

How to solve this issue ?

@yumorishita
Copy link
Owner

I guess the manually downloaded files have something wrong. Please check if all the files cover the AOI.

@faraksoch1881
Copy link
Author

It should be pretty basic question but is there any text file where i can get list of files name whose gacos data is not availaible after running step 01. The new folder is created with name GACOS and i want to download the missing files manually from GACOS website to apply atmospheric correction.

@yumorishita
Copy link
Owner

Just ls and compare the list.

@as1234554321
Copy link

as1234554321 commented Sep 12, 2024

Hi sir,
I have succeeded in processing the data to the ts plot, but when I look at the log it says something like this, what does that mean, does it affect the results?

  1. "GACOS data for the following dates are missing". Do I have to download it manually?
    image
    2)the percentage of masked files is higher than kept, is it better to mask/kept with a high percentage? how to increase the percentage?
    image
    3)how to get ztd?
    image

  2. which one is better for decomposition?
    image
    thankyou

@yumorishita
Copy link
Owner

  1. You don't have to, but you can do it.
  1. It seems to be not bad.
  2. http://www.gacos.net/
  1. Generally I recommend a masked one,
@as1234554321
Copy link

as1234554321 commented Sep 12, 2024

Thankyou sir

  1. You don't have to, but you can do it.
    I wrote the end date "20240715" but the GACOS data (get gacos option 0-3) is only up to 20240219. UNW and CC data is up to 20240715. Is there a big influence on the LOS results?

  2. It seems to be not bad
    Does the percentage of the size of the mask and kept pixels have no effect?
    better higher mask pixels or kept pixels?

  3. http://www.gacos.net/

  4. Generally I recommend a masked one,
    which file is better to use for decomposition vel.mskd or vel.filter.mskd?

@yumorishita
Copy link
Owner

  1. I don't know.
  2. The better the more the kept pixels, but the masked result seems to be acceptable because the deformation is captured.
  3. vel.filt.mskd
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
3 participants