Sparse matrix file I/O in SciPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a sparse matrix?

A sparse matrix is a matrix mostly filled with zeros. It saves memory by only storing the non-zero values and their positions.

beginner

Which SciPy module is commonly used for sparse matrix file input/output?

The scipy.sparse module along with scipy.io is used to save and load sparse matrices efficiently.

intermediate

How do you save a sparse matrix to a file using SciPy?

Use scipy.io.savemat to save a sparse matrix in MATLAB format or scipy.sparse.save_npz to save in compressed NumPy format.

intermediate

How do you load a sparse matrix saved in NPZ format?

Use scipy.sparse.load_npz(filename) to load the sparse matrix back into memory.

beginner

Why is it better to use sparse matrix file formats instead of saving as dense arrays?

Saving sparse matrices in special formats keeps file size small and loading fast because it only stores non-zero values, unlike dense arrays which store all values including zeros.

Which function saves a sparse matrix in compressed NPZ format?

A scipy.sparse.save_npz

B scipy.io.savemat

C numpy.save

D scipy.sparse.load_npz

scipy.sparse.save_npz saves sparse matrices in compressed NPZ format, which is efficient for storage.

What does a sparse matrix mainly store to save space?

A Only zero values

B All values including zeros

C Only non-zero values and their positions

D Only the diagonal values

Sparse matrices store only the non-zero values and their positions to save memory.

Which function loads a sparse matrix saved in NPZ format?

A scipy.io.loadmat

B scipy.sparse.load_npz

C numpy.load

D scipy.sparse.save_npz

scipy.sparse.load_npz loads sparse matrices saved in NPZ format.

What file format does scipy.io.savemat save data in?

A MATLAB .mat format

B CSV format

C JSON format

D NPZ format

scipy.io.savemat saves data in MATLAB's .mat file format.

Why should you use sparse matrix file I/O methods instead of saving as dense arrays?

A Because dense arrays are faster to save

B Dense arrays use less memory

C Sparse matrix file I/O is slower but more accurate

D To save disk space and load data faster

Sparse matrix file I/O saves disk space and loads data faster by storing only non-zero values.

Explain how to save and load a sparse matrix using SciPy.

Think about the functions for saving and loading NPZ files.

Why is it important to use sparse matrix file I/O methods instead of saving as dense arrays?

Consider the difference in storage between sparse and dense matrices.