## Numpy matrix to array

If you’d like something a bit more readable, you can do this: Equivalently, you could also do: A = np.asarray(M).reshape(-1), but that’s a bit less easy to read.

If you’d like something a bit more readable, you can do this: Equivalently, you could also do: A = np.asarray(M).reshape(-1), but that’s a bit less easy to read.

For a numpy based solution, you can use numpy.where and then get the row indexes from it and then use it for indexing you matrix. Example – Demo – Another method , as indicated in the comments would be to use boolean masks, Example – Demo –

The number of rows of a list of lists would be: len(A) and the number of columns len(A[0]) given that all rows have the same number of columns, i.e. all lists in each index are of the same size.

You can resolve this in several ways: Use g++ in stead of gcc: g++ -g -o MatSim MatSim.cpp Add -lstdc++: gcc -g -o MatSim MatSim.cpp -lstdc++ Replace <string.h> by <string> This is a linker problem, not a compiler issue. The same problem is covered in the question iostream linker error – it explains what is …

You want to reshape the array. where -1 infers the size of the new dimension from the size of the input array.

Numpy matrices are strictly 2-dimensional, while numpy arrays (ndarrays) are N-dimensional. Matrix objects are a subclass of ndarray, so they inherit all the attributes and methods of ndarrays. The main advantage of numpy matrices is that they provide a convenient notation for matrix multiplication: if a and b are matrices, then a*b is their matrix product. On the other hand, as …

The Numpythonic approach: (using numpy.dot in order to get the dot product of two matrices) The Pythonic approach: The length of your second for loop is len(v) and you attempt to indexing v based on that so you got index Error . As a more pythonic way you can use zip function to get the columns of a list then use starmap and mul within a list comprehension:

solve(c) does give the correct inverse. The issue with your code is that you are using the wrong operator for matrix multiplication. You should use solve(c) %*% c to invoke matrix multiplication in R. R performs element by element multiplication when you invoke solve(c) * c.

Math.NET Numerics is very nice, if it supports the operations you want. The older Math.Net Iridium still supports more options. Also, dnAnalytics is quite nice, but no longer being developed. (It, as well as Iridium, are being merged into Math.NET Numerics.) On the commercial side, there are some very good, robust options. The Extreme Optimization Numerical Libraries work very well. …

I have a list of variables name “comorbid_names”. And I want to select people who have those comorbidities in “comorbidities”. However, I want to select the variable names if they are true. For example patient 1 has “chd” only, therefore only that will be displayed as TRUE comorbid_names [1] “chd” “heart_failure” “stroke”[4] “hypertension” “diabetes” “copd”[7] …