[Numpy-discussion] Who uses matrix?

[Robert Hetland]

I never use matrices primarily because I am worried about one more  
data type floating around in my code.  That is, data is often read in  
or constructed as lists, and must be converted to an array to do  
anything useful.

Take a simple example of optimal interpolation:  Read in the data (as  
a list?), construct the background error covariance arrays (arrays),  
then do about three lines of linear algebra; e.g.,

         W = dot(linalg.inv(B + O), Bi)  				# weights
         A = dot(self.Di,W).transpose() 				# analysis
         Ea = diag(sqrt(self.Be - dot(W.transpose(), Bi)))	# analysis  
error

Is it worth it to convert the arrays to matrices in order to do this  
handful of calculation?  Almost.  I covet the shorthand .T notation  
in matrix object while getting RSI typing in t-r-a-n-s-p-o-s-e.   
Also, for involved calculations inverse, transpose et. al are long  
enough words such that the line always wraps, resulting in less- 
readable code.

Should I give in?  If there was some shorthand links to inverse and  
transpose methods in the array object, I would definitely stick with  
arrays.

-Rob

p.s. By the way, array broadcasting saves much pain in creating the  
background error covariance arrays.  Yeah for array broadcasting!


-----
Rob Hetland, Assistant Professor
Dept of Oceanography, Texas A&M University
p: 979-458-0096, f: 979-845-6331
e: hetland at tamu.edu, w: http://pong.tamu.edu