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• Anomalie #2644 : Forum - Nombre de messages erroné

  12 avril 2012, par Ben .

  En passant un autre bug : quand on clique sur TOUS, le TOUS ne passe pas en blanc (SPIP 3.0.0-rc SVN [19239])

• Evolution #4427 : Permettre (via une constante) de passer de 65 536 à 4096 le nombre max de fichie...

  24 janvier 2020, par b b

  Merci, mais je te demandais un diff ;)

• even though my code is running without an error, it does not generate plot or video. I have xming runing

  23 octobre 2017, par Amin Abbasi

  This is my first code and I am really new to coding. I am trying to create a video or just plot my code.Eeven though my code is running without an error, I can’t get the video or the plot to generate. I have xming running and I have plotted a sample to make sure it not a computer Issue. I have also tried the following on GitHub but no success :
  https://jakevdp.github.io/blog/2013/05/19/a-javascript-viewer-for-matplotlib-animations/

  # -*- coding: utf-8 -*-
  
  import numpy as np
  
  def solver(I, V, f, c, L, dt, cc, T, user_action=None):
  
      """Solve u_tt=c^2*u_xx + f on (0,L)x(0,T]."""
  
      Nt = int(round(T/dt))
  
      t = np.linspace(0, Nt*dt, Nt+1) # Mesh points in time
  
      dx = dt*c/float(cc)
  
      Nx = int(round(L/dx))
  
      x = np.linspace(0, L, Nx+1) # Mesh points in space
  
      C2 = cc**2 # Help variable in the scheme
  
      # Make sure dx and dt are compatible with x and t
  
      dx = x[1] - x[0]
  
      dt = t[1] - t[0]
  
      if f is None or f == 0 :
  
          f = lambda x, t: 0
  
      if V is None or V == 0:
  
          V = lambda x: 0
  
      u       = np.zeros(Nx+1) # Solution array at new time level
  
      u_n     = np.zeros(Nx+1) # Solution at 1 time level back
  
      u_nm1   = np.zeros(Nx+1) # Solution at 2 time levels back
  
      import time; t0 = time.clock() # Measure CPU time
  
      # Load initial condition into u_n
  
      for i in range(0,Nx+1):
  
          u_n[i] = I(x[i])
  
      if user_action is not None:
  
          user_action(u_n, x, t, 0)
  
      # Special formula for first time step
  
      n = 0
  
      for i in range(1, Nx):
  
          u[i] = u_n[i] + dt*V(x[i]) + \
  
              0.5*C2*(u_n[i-1] - 2*u_n[i] + u_n[i+1]) + \
  
              0.5*dt**2*f(x[i], t[n])
  
      u[0] = 0; u[Nx] = 0
  
      if user_action is not None:
  
          user_action(u, x, t, 1)
  
      # Switch variables before next step
  
      u_nm1[:] = u_n; u_n[:] = u
  
      for n in range(1, Nt):
  
          # Update all inner points at time t[n+1]
  
          for i in range(1, Nx):
  
              u[i] = - u_nm1[i] + 2*u_n[i] + \
  
                      C2*(u_n[i-1] - 2*u_n[i] + u_n[i+1]) + \
  
                      dt**2*f(x[i], t[n])
  
          # Insert boundary conditions
  
          u[0] = 0; u[Nx] = 0
  
          if user_action is not None:
  
              if user_action(u, x, t, n+1):
  
                  break
  
          # Switch variables before next step
  
          u_nm1[:] = u_n; u_n[:] = u
  
      cpu_time = time.clock() - t0
  
      return u, x, t,
  
  def test_quadratic():
  
      """Check that u(x,t)=x(L-x)(1+t/2) is exactly reproduced."""
  
      def u_exact(x, t):
  
          return x*(L-x)*(1 + 0.5*t)
  
      def I(x):
  
          return u_exact(x, 0)
  
      def V(x):
  
          return 0.5*u_exact(x, 0)
  
      def f(x, t):
  
          return 2*(1 + 0.5*t)*c**2
  
      L = 2.5
  
      c = 1.5
  
      cc = 0.75
  
      Nx = 6 # Very coarse mesh for this exact test
  
      dt = cc*(L/Nx)/c
  
      T = 18
  
      def assert_no_error(u, x, t, n):
  
          u_e = u_exact(x, t[n])
  
          diff = np.abs(u - u_e).max()
  
          tol = 1E-13
  
          assert diff < tol
  
      solver(I, V, f, c, L, dt, cc, T,
  
              user_action=assert_no_error)
  
  def viz(
  
      I, V, f, c, L, dt, C, T,umin, umax, animate=True, tool='matplotlib'):
  
      """Run solver and visualize u at each time level."""
  
      def plot_u_st(u, x, t, n):
  
          """user_action function for solver."""
  
          plt.plot(x, u, 'r-')
  
  #                 xlabel='x', ylabel='u',
  
  #                 axis=[0, L, umin, umax],
  
  #                 title='t=%f' % t[n], show=True)
  
          # Let the initial condition stay on the screen for 2
  
          # seconds, else insert a pause of 0.2 s between each plot
  
          time.sleep(2) if t[n] == 0 else time.sleep(0.2)
  
          plt.savefig('frame_%04d.png' % n) # for movie making
  
      class PlotMatplotlib:
  
          def __call__(self, u, x, t, n):
  
              """user_action function for solver."""
  
              if n == 0:
  
                  plt.ion()
  
                  self.lines = plt.plot(x, u, 'r-')
  
                  plt.xlabel('x'); plt.ylabel('u')
  
                  plt.axis([0, L, umin, umax])
  
                  plt.legend(['t=%f' % t[n]], loc='lower left')
  
              else:
  
                  self.lines[0].set_ydata(u)
  
                  plt.legend(['t=%f' % t[n]], loc='lower left')
  
                  plt.draw()
  
              time.sleep(2) if t[n] == 0 else time.sleep(0.2)
  
              plt.savefig('tmp_%04d.png' % n) # for movie making
  
      if tool == 'matplotlib':
  
          import matplotlib.pyplot as plt
  
          plot_u = PlotMatplotlib()
  
      elif tool == 'scitools':
  
          import scitools.std as plt # scitools.easyviz interface
  
          plot_u = plot_u_st
  
      import time, glob, os
  
      # Clean up old movie frames
  
      for filename in glob.glob('tmp_*.png'):
  
          os.remove(filename)
  
      # Call solver and do the simulaton
  
      user_action = plot_u if animate else None
  
      u, x, t, cpu = solver_function(
  
          I, V, f, c, L, dt, C, T, user_action)
  
      # Make video files
  
      fps = 4 # frames per second
  
      codec2ext = dict(flv='flv', libx264='mp4', libvpx='webm',
  
                       libtheora='ogg') # video formats
  
      filespec = 'tmp_%04d.png'
  
      movie_program = 'ffmpeg' # or 'avconv'
  
      for codec in codec2ext:
  
          ext = codec2ext[codec]
  
          cmd = '%(movie_program)s -r %(fps)d -i %(filespec)s '\
  
                '-vcodec %(codec)s movie.%(ext)s' % vars()
  
          os.system(cmd)
  
      if tool == 'scitools':
  
          # Make an HTML play for showing the animation in a browser
  
          plt.movie('tmp_*.png', encoder='html', fps=fps,
  
                    output_file='movie.html')
  
      return cpu