How to remove RunTimeWarning Errors from code?

Question

I keep getting RuntimeWarning when I run the regression code at the very bottom. I am not sure how to fix them. I believe it may be the attencoef list because there is some nan values in it. Any suggestions?

These are the errors I am getting:

C:\Users\MTM User\Anaconda3\lib\site-packages\scipy\stats\_stats_mstats_common.py:106: RuntimeWarning: invalid value encountered in double_scalars
  slope = r_num / ssxm
C:\Users\MTM User\Anaconda3\lib\site-packages\scipy\stats\_stats_mstats_common.py:116: RuntimeWarning: invalid value encountered in sqrt
  t = r * np.sqrt(df / ((1.0 - r + TINY)*(1.0 + r + TINY)))
C:\Users\MTM User\Anaconda3\lib\site-packages\scipy\stats\_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in greater
  return (self.a < x) & (x < self.b)
C:\Users\MTM User\Anaconda3\lib\site-packages\scipy\stats\_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in less
  return (self.a < x) & (x < self.b)
C:\Users\MTM User\Anaconda3\lib\site-packages\scipy\stats\_distn_infrastructure.py:1818: RuntimeWarning: invalid value encountered in less_equal
  cond2 = cond0 & (x <= self.a)
C:\Users\MTM User\Anaconda3\lib\site-packages\scipy\stats\_stats_mstats_common.py:118: RuntimeWarning: invalid value encountered in double_scalars
  sterrest = np.sqrt((1 - r**2) * ssym / ssxm / df)

The code:

for depthvalues in split_depth.values(): # only takes the values (separated lists), removes keys

    # takes into account the number of yows
    count+=1

    depthlst = depthvalues
    depthfirst = depthlst[0] #find my first depth or deepest depth
    depthlast = depthlst[-1] # find my last depth, or shallowest

    depthfirst_index = depth.index(depthfirst) #finds the index of my deepest depth for this segment in the filtered lists
    depthlast_index = depth.index(depthlast) #finds the index of my shallowest depth for this segment in the filtered lists

    irradlst = irrad[depthfirst_index:depthlast_index+1]

    irrad_first = irradlst[0] #finds the corresponding irradiance
    irrad_last = irradlst[-1] 
    irrad_last = float(irrad_last)

    irradlst = np.array(irradlst).astype(np.float)
    depthlst = np.array(depthlst).astype(np.float)

    attencoef = [np.log(i/irrad_last) for i in irradlst]

    #whenever I use this line of code(below) I get a bunch of errors
    regress = linregress(attencoef,depthlst) 

Answer 1

You should filter the warning with:

import warnings
warnings.filterwarnings("ignore", category=RuntimeWarning) 

The category is the type of warning you want to silence.