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But using %lu solved the issue But i only know how to do it without pivoting. Actually, rather than focusing on the problem and the line of codes, i want to know about the difference between %ul and %lu

Maybe i could figure out what's wrong I want to implement my own lu decomposition p,l,u = my_lu (a), so that given a matrix a, computes the lu decomposition with partial pivoting Searching doesn't give me something useful (except that they are different)

Any explanation or link/reference is appreciated.

Asked 11 years, 2 months ago modified 10 years ago viewed 27k times Printf and %llu vs %lu on os x [duplicate] asked 12 years, 11 months ago modified 12 years, 11 months ago viewed 43k times I get a 'lu decomposition' error where using sarimax in the statsmodels python package Import numpy as np from statsmodels.tsa.arima.model import arima items = np.log(og_items) items['count'] = items['count'].apply(lambda x

0 if math.isnan(x) or math.isinf(x) else x) model = arima(items, order=(14, 0, 7)) trained = model.fit() items is a dataframe containing a date index and a single column, count I apply the lambda on the second line because some counts can be 0, resulting in. What is the difference between %zu and %lu in string formatting in c %lu is used for unsigned long values and %zu is used for size_t values, but in practice, size_t is just an unsigned long.

I’d suppose yes, since i can see no reason why not

However, if yes, then this would remove the need for existence of these macroified specifiers like priu32, so i figure i’d better ask The reason i’m asking it is that i’d like to create a format string for printf dynamically, and it’d be hard to allocate space for this format string if i don't know the size of. I understand that %zd is the suggested way to format the sizeof result However, i don't understand why that is necessary

For example using lu gives me the same output, and isn't the result of siz. A = p l u it is entirely expected that multiplying the p, l, and u matrices should produce something close to the array originally passed to scipy.linalg.lu You are not supposed to invert p.

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