Extracting polynomial coefficients from file in Python-CodePudding

I have recently been working with text files that contain data like the following:

A = a_0   a_1*x   ...   a_l*x^l
B = b_0   b_1*x   ...   b_m*x^m
.
.
.
G = g_2*x^2   g_n

where l and m are not necessarily the same, and B might not be the longest equation. Is there a way to import the coefficients into a NumPy array, inserting 0s where the coefficients are missing, such that the above example would yield

I was initially thinking of using numpy.genfromtxt where the x are filled with 1 (so that only the coefficient survives), but that has the problem that we lose which column and row the coefficient in. Any help is very much appreciated.

CodePudding user response：

This is very custom type of text you have to write a parser to do so:

considering the txt file is read, example here s you probably have to read from file, with open('..') as fid ...

s  = """A =  2*x    3*x^5
B = 3   2*x    3*x^5
C = 8   20*x    3*x^9"""

like this:

equations = s.split('\n')

def parse_lines(s):
    def foo(val):
        coef, _power,*_ = *val.split('*'), '^'  #  parse a_0*x^n 
        x, power, *_ =  *_power.split('^'), '1' #  parse x^n
        power = 0 if not power else power 
        return int(coef) , int(power)
    
    _, eq = s.split('=')
    return  [foo(item) for item in eq.split(' ')]
 

indexes = [(idx, *t)  for idx, eq in enumerate(equations) for t in parse_lines(eq)]

output: (row, val, col)

[(0, 2, 1),
 (0, 3, 5),
 (1, 3, 0),
 (1, 2, 1),
 (1, 3, 5),
 (2, 8, 0),
 (2, 20, 1),
 (2, 3, 9)]

you could parse to a format that could be reconstructed to an array. after this it is simple just build array:

m, _, n = np.array(d).max(axis=0)
m , n = m   1, n   1
arr = np.zeros((m,n))
for row, val, col in indexes:
    arr[row, col] = val

output:

array([[ 0.,  2.,  0.,  0.,  0.,  3.,  0.,  0.,  0.,  0.],
       [ 3.,  2.,  0.,  0.,  0.,  3.,  0.,  0.,  0.,  0.],
       [ 8., 20.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  3.]])