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Update deltaSHAPE.py #1

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Update deltaSHAPE.py #1

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8 changes: 4 additions & 4 deletions deltaSHAPE.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,8 +75,8 @@ def smooth(data,err,pad):
# use numpy masked array to calculate average without including no-data (nan) nucleotides.
new_data.append(np.mean(np.ma.MaskedArray([j for j in data[i-pad:i+pad+1]], np.isnan([j for j in data[i-pad:i+pad+1]]))))

# use stats.nanmean to calculate average without including no-data (nan) nucleotides. This causes long_scalars runtime warnings.
#new_data.append(stats.nanmean([j for j in data[i-pad:i+pad+1] if np.isnan(j) != True]))
# use np.nanmean to calculate average without including no-data (nan) nucleotides. This causes long_scalars runtime warnings.
#new_data.append(np.nanmean([j for j in data[i-pad:i+pad+1] if np.isnan(j) != True]))
errs = np.array(err[i-pad:i+pad+1])
squerrs = np.power([j for j in errs if np.isnan(j) != True], 2)
total = np.sum(squerrs)
Expand Down Expand Up @@ -106,8 +106,8 @@ def z_factor(data1, data2, err1, err2, factor=1.96):
return z_factors

def calc_zScores(diffs):
mean = stats.nanmean(diffs)
sigma = stats.nanstd(diffs)
mean = np.nanmean(diffs)
sigma = np.nanstd(diffs)
# calc Z-score
z_scores = (diffs - mean) / sigma
return np.array(z_scores)
Expand Down