search

sharppy / SHARPpy

Sounding/Hodograph Analysis and Research Program in Python
https://sharppy.github.io/SHARPpy/index.html
Other
216 stars 112 forks source link

Error when using mlpcl #138

Closed Silviameteoro closed 5 years ago

Silviameteoro commented 6 years ago

Hi All,

I am having an issue with the computation of parameters that use the mlpcl (please see below).

/usr/lib/python2.7/site-packages/SHARPpy-1.3.0-py2.7.egg/sharppy/sharptab/interp.py:53: RuntimeWarning: divide by zero encountered in log10 return generic_interp_pres(np.log10(p), prof.logp[::-1], prof.hght[::-1]) /usr/lib64/python2.7/site-packages/numpy/lib/function_base.py:2059: UserWarning: Warning: converting a masked element to nan. return interp_func([x], xp, fp, left, right).item() /usr/lib/python2.7/site-packages/SHARPpy-1.3.0-py2.7.egg/sharppy/sharptab/winds.py:45: UserWarning: Warning: converting a masked element to nan. ps = np.arange(pbot, ptop+dp, dp) Traceback (most recent call last): File "sharppyreaderTESTE.py", line 86, in mlpcl = params.parcelx( prof, flag=4 ) # 100 mb Mean Layer Parcel File "/usr/lib/python2.7/site-packages/SHARPpy-1.3.0-py2.7.egg/sharppy/sharptab/params.py", line 1935, in parcelx bulk_rich(prof, pcl) File "/usr/lib/python2.7/site-packages/SHARPpy-1.3.0-py2.7.egg/sharppy/sharptab/params.py", line 1994, in bulk_rich mnlu, mnlv = winds.mean_wind(prof, pbot, p) File "/usr/lib/python2.7/site-packages/SHARPpy-1.3.0-py2.7.egg/sharppy/sharptab/winds.py", line 45, in mean_wind ps = np.arange(pbot, ptop+dp, dp) ValueError: arange: cannot compute length

I currently have numpy v. 1.14.2. I notice there is a “closed issue” about a similar problem when it was suggested a downgrading to numpy v.1.12.1.

Is there any other potential available solutions? I am running on a server and downgrading the numpy version is not an option for me since there are other python applications running on this server.

I am working with python 2.7.5 on a Red Hat linux installation.

Thank you very much in advance!

Silvia

wblumberg commented 6 years ago

Hi Silvia. I'm terribly sorry about getting to this now! This was posted during my 'writing dissertation' phase. I can't think of any other potential solutions. Anaconda does offer the ability to build different environments, so perhaps you can make one with the needed Numpy installation. Changes to numpy have made it extremely frustrating for us to keep SHARPpy working with several different numpy versions, and we keep running into new issues with each new numpy version. We're trying to figure out a fix, but I'm not sure if that'll happen in the near future.

wblumberg commented 5 years ago

Our fix here will be to deploy SHARPpy on conda which will allow us to deploy the correct numpy version that works with this.