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change filt variable from global to local #389

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change filt variable from global to local #389

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73f2e3e
change filt variable from global to local
martin-springer Sep 12, 2023
7e2b095
update minimize in single_opt
martin-springer Nov 16, 2023
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7 changes: 3 additions & 4 deletions rdtools/normalization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -380,7 +380,7 @@ def irradiance_rescale(irrad, irrad_sim, max_iterations=100,
'''

if method == 'iterative':
def _rmse(fact):
def _rmse(fact, filt):
"""
Calculates RMSE with a given rescale fact(or) according to global
filt(er)
Expand All @@ -392,10 +392,9 @@ def _rmse(fact):

def _single_rescale(irrad, irrad_sim, guess):
"Optimizes rescale factor once"
global filt
csi = irrad / (guess * irrad_sim) # clear sky index
filt = (csi >= 0.8) & (csi <= 1.2) & (irrad > 200)
min_result = minimize(_rmse, guess, method='Nelder-Mead')
min_result = minimize(_rmse, guess, (filt), method='Nelder-Mead')
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I think we may need to use a lambda function like lambda x : _rmse(x, filt) here as the first argument to minimize

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@mdeceglie - I'm not seeing why we might need a lambda function. I created a jupyter notebook that re-creates the analysis and I obtain the same result between my suggested changes and the initial implementation. I opened a new PR #399 from the master branch to have running tests and to check whether my changes cause any troubles. So far, all pytests seem to be passing.


factor = min_result['x'][0]
return factor
Expand Down Expand Up @@ -429,7 +428,7 @@ def _rmse(fact):

guess = np.percentile(irrad.dropna(), 90) / \
np.percentile(irrad_sim.dropna(), 90)
min_result = minimize(_rmse, guess, method='Nelder-Mead')
min_result = minimize(_rmse, guess, (filt), method='Nelder-Mead')
factor = min_result['x'][0]

out_irrad = factor * irrad_sim
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