ICS CMS | R. Sauser (EPFL)

9.1 Aide-mémoire des fonctions rencontrées dans les librairies Python

NumPy

import numpy as np

np.linspace(start, stop, num=50, endpoint=True, retstep=False)

np.logspace(start, stop, num=50, endpoint=True)

np.arange(start, stop, step)

np.zeros(shape, dtype=float)

np.ones(shape, dtype=None)

np.empty(shape, dtype=float)

np.array(object, dtype=None)

np.empty_like(a)

np.zeros_like(a)

np.ones_like(a)

ndarray.ndim

ndarray.shape

ndarray.dtype

np.eye(N)

np.reshape(a, newshape)

np.dot(a, b)

a.T

a.transpose()

np.linalg.det(a)

np.linalg.inv(a)

np.linalg.eig(a)

np.random.rand(N)

np.meshgrid(x,y,indexing='ij')

np.gradient(f)

np.loadtxt(fname, comments='#', skiprows=0, usecols=None, unpack=False)

np.savetxt(fname, X, fmt='%.18e', delimiter=' ', newline='\n',

header=' ', footer=' ', comments='\#')

SciPy

from scipy import constants

from scipy import optimize

from scipy import misc

from scipy import integrate

constants.c

constants.m_e

constants.g

constants.physical constants[''speed of light in vacuum'']

constants.physical constants[''electron mass'']

constants.physical constants[''standard acceleration of gravity'']

optimize.curve_fit(f, xdata, ydata)

optimize.bisect(f, a, b, xtol=2e-12, maxiter=100,full_output=False)

optimize.newton(func, x0, fprime=None, tol=1.48e-08,maxiter=50,

fprime2=None, full_output=False)

optimize.fsolve(func, x0, xtol=1.49012e-08)

misc.derivative(func, x0, dx=1.0, n=1, order=3)

integrate.quad(f, a, b)

integrate.odeint(f, y0, t, tfirst=True)

Matplotlib

import matplotlib.pyplot as plt

import matplotlib.image as mpimg

plt.figure(num=None, figsize=None)

plt.plot(x, y)

plt.errorbar(x, y, yerr=None, xerr=None)

plt.scatter(x, y)

plt.quiver(x,y,u,v)

fig.suptitle(str)

ax = plt.subplot(m,n,a)

ax = plt.subplot() (ou ax = fig.gca())

ax = plt.subplot(projection='3d') (ou ax = fig.gca(projection='3d')

ax.plot(x, y)

ax.barh(y, width)

ax.contour(x,y,z,levels)

ax.plot_surface(x,y,z)

ax.quiver(x,y,u,v)

ax.streamplot(x, y, u, v, linewidth=1, density = 2,

ax.set_title(str)

ax.set_yticks(labels)

ax.set_xlabel(xlabel)

ax.set_ylabel(ylabel)

ax.set_zlabel(zlabel)

ax.imshow(x)

plt.fill_between(x, y1, y2)

plt.clabel(cs)

plt.axis('equal')

plt.axis('scaled')

plt.grid()

plt.xlabel(xlabel)

plt.ylabel(ylabel)

plt.legend()

plt.title(label)

plt.savefig(fname)

plt.imshow(x)

plt.show()

mpimg.imread(fname)

mpimg.imsave(fname, arr)