Some other requirements for the project¶
Sparse matrix¶
Sparse matrix are very efficient when we need to use a matrix with a lot of zeros-values. To illustrate its use, we need a function that will randomly spread numbers with a chosen density.
-
sparse_matrix(wi, leng, den)¶ Creates a sparse matrix.
It uses random number to place the values (non-null values).
- Parameters
wi (integer) – the width of the matrix
leng (integer) – the length of the matrix
den (float) – density of non-null number in the matrix
- Returns
The representation of a sparse matrix
- Return type
matplotlib plot
Pixel colors¶
When we use the mandel_loop function, one can visualize the speed of divergence of the \((z_n)_n\) sequence.
We built an histogram representing each color for the speed of divergence on the \((0,x)\) axis and the associated
number of pixels in a chosen window on the \((0,y)\) axis.
-
histogram(x=- 0.5, y=0, window=1.5)¶ Creates a histogram.
Histogram display for each color density.
- Parameters
x (float) – coordinate for the points of mandelbrot set
y (float) – coordinate for the points of mandelbrot set
window (float) – size of the viewing window
- Returns
histogram
- Return type
matplotlib plot