My code is:
import numpy as np
import matplotlib as plt
polyCoeffiecients = [1,2,3,4,5]
plt.plot(PolyCoeffiecients)
plt.show()
The result for this is straight lines that describe the points in 1,2,3,4,5 and the straight lines between them, instead of the polynomial of degree 5 that has 1,2,3,4,5 as its coeffiecients ( P(x) = 1 + 2x + 3x + 4x + 5x)
How am i suppose to plot a polynomial with just its coefficients?
Eyzuky, see if this is what you want:
import numpy as np
from matplotlib import pyplot as plt
def PolyCoefficients(x, coeffs):
""" Returns a polynomial for ``x`` values for the ``coeffs`` provided.
The coefficients must be in ascending order (``x**0`` to ``x**o``).
"""
o = len(coeffs)
print(f'# This is a polynomial of order {o}.')
y = 0
for i in range(o):
y += coeffs[i]*x**i
return y
x = np.linspace(0, 9, 10)
coeffs = [1, 2, 3, 4, 5]
plt.plot(x, PolyCoefficients(x, coeffs))
plt.show()
You could approximately draw the polynomial by getting lots of x-values and using np.polyval() to get the y-values of your polynomial at the x-values. Then you could just plot the x-vals and y-vals.
import numpy as np
import matplotlib.pyplot as plt
curve = np.array([1,2,3,4,5])
x = np.linspace(0,10,100)
y = [np.polyval(curve, i) for i in x]
plt.plot(x,y)
np.polyval accepts the whole array of x as an argument in place of i. You don't need the list comprehension for the y equation.A very pythonic solution is to use list comprehension to calculate the values for the function.
import numpy as np
from matplotlib import pyplot as plt
x = np.linspace(0, 10, 11)
coeffs = [1, 2, 3, 4, 5]
y = np.array([np.sum(np.array([coeffs[i]*(j**i) for i in range(len(coeffs))])) for j in x])
plt.plot(x, y)
plt.show()
Generic, vectorized implementation:
from typing import Sequence, Union
import numpy as np
import matplotlib.pyplot as plt
Number = Union[int, float, complex]
def polyval(coefficients: Sequence[Number], x: Sequence[Number]) -> np.ndarray:
# expand dimensions to allow broadcasting (constant time + inexpensive)
# axis=-1 allows for arbitrarily shaped x
x = np.expand_dims(x, axis=-1)
powers = x ** np.arange(len(coefficients))
return powers @ coefficients
def polyplot(coefficients: Sequence[Number], x: Sequence[Number]) -> None:
y = polyval(coefficients, x)
plt.plot(x, y)
polyplot(np.array([0, 0, -1]), np.linspace(-10, 10, 210))
plt.show()
numpy.poly1d