Prevent warning and add variable to plot

tools/plot_raw_data.py

@@ -103,7 +103,8 @@ def get_uniform_data(grids, domain, min_pixels, interpolation='linear',
 
 
 def plot_uniform_data(uniform_data, x, time, vmin=None, vmax=None, cmap=None,
- xlim=None, ylim=None, hide_axes=False, save_plot=None):
+ xlim=None, ylim=None, hide_axes=False, save_plot=None,
+ variable=None):
  # Plot data
  fig, ax = plt.subplots()
  ndim = uniform_data.ndim
@@ -128,7 +129,10 @@ def plot_uniform_data(uniform_data, x, time, vmin=None, vmax=None, cmap=None,
  if ylim:
  ax.set_ylim(*ylim)
 
- ax.set_title(f't = {time:.3e}')
+ title = f't = {time:.3e}'
+ if variable is not None:
+ title = title + ' - ' + variable
+ ax.set_title(title)
 
  if save_plot:
  print(f'Saving to {save_plot}')
@@ -165,7 +169,8 @@ def plot_uniform_data(uniform_data, x, time, vmin=None, vmax=None, cmap=None,
  vmin=args.vmin, vmax=args.vmax,
  cmap=args.cmap, xlim=args.xlim, ylim=args.ylim,
  hide_axes=args.hide_axes,
- save_plot=args.save_plot)
+ save_plot=args.save_plot,
+ variable=args.variable)
  else:
  # All spatial dimensions are projected, only print time and sum
  grid_values = np.array([g['values'] for g in grids])

tools/raw_reader.py

@@ -74,7 +74,7 @@ def read_single_grid(f):
 
  # Number of cell centers is one less than number of faces
  n_cells = dims-1
- fmt = '=' + str(np.product(n_cells)) + 'd'
+ fmt = '=' + str(np.prod(n_cells)) + 'd'
  tmp = unpack(fmt, f.read(calcsize(fmt)))
  vals = np.array(tmp).reshape(n_cells, order='F')
 
@@ -143,7 +143,7 @@ def write_single_grid(f, grid):
 
  # Number of cell centers is one less than number of faces
  n_cells = grid['dims']-1
- fmt = '=' + str(np.product(n_cells)) + 'd'
+ fmt = '=' + str(np.prod(n_cells)) + 'd'
  f.write(grid['values'].tobytes(order='F'))
 
 
@@ -226,13 +226,13 @@ def grid_project(in_grid, project_dims, axisymmetric):
  if axisymmetric and 0 in pdims:
  # Multiply with 2 * pi * r
  r = g['coords_cc'][0][valid_ix[0]]
- w = np.product(g['dr'][pdims]) * 2 * np.pi * r
+ w = np.prod(g['dr'][pdims]) * 2 * np.pi * r
 
  # Broadcast to have volume weight for every grid cell
  w = np.broadcast_to(w[:, None], ihi-ilo)
  g['values'] = (g['values'][valid_ix] * w).sum(axis=tuple(pdims))
  else:
- fac = np.product(g['dr'][pdims])
+ fac = np.prod(g['dr'][pdims])
  g['values'] = fac * g['values'][valid_ix].sum(axis=tuple(pdims))
 
  g['n_dims'] -= len(project_dims)
@@ -328,7 +328,7 @@ def map_grid_data_to(g, r_min, r_max, dr, axisymmetric=False,
  cdata = np.zeros(nx)
 
  if axisymmetric:
- rvolume = np.product(g['dr']/dr) * coords_fine[0]/coords_coarse[0]
+ rvolume = np.prod(g['dr']/dr) * coords_fine[0]/coords_coarse[0]
 
  if rvolume.ndim < len(g['ihi']):
  # Broadcast to have volume weight for every grid cell
@@ -338,7 +338,7 @@ def map_grid_data_to(g, r_min, r_max, dr, axisymmetric=False,
  values = rvolume.ravel() * g['values'][valid_ix].ravel()
  else:
  # Cartesian grid, simple averaging
- rvolume = np.product(g['dr']/dr)
+ rvolume = np.prod(g['dr']/dr)
  values = rvolume * g['values'][valid_ix].ravel()
 
  np.add.at(cdata, tuple(map(np.ravel, ixs)), values)