def plot_both_things(sol, masses, plot_times, cell_start, cell_end, eps, y0,
y1, gridpoints, title, save_location, T):
fig, (ax1, ax2) = plt.subplots(1, 2)
ax1.set_xlabel('time')
ax1.set_ylabel('position')
ax2.set_xlabel('position')
ax2.set_ylabel('density')
ax1.set_title('particle trajectories colored by mass')
ax2.set_title('profiles colored by timestep')
fig.suptitle(title)
t = sol['t']
traj = sol['y']
cmap = plt.get_cmap('jet')
cNorm = colors.Normalize(vmin=0, vmax=max(masses))
ScalarMap1 = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
for i in range(len(masses)):
linecolor = ScalarMap1.to_rgba(masses[i])
ax1.plot(t, traj[i], color=linecolor)
ax1.plot([0, 0], [y0, y1], 'ro')
ax3 = fig.add_axes([0.01, 0.12, 0.02, 0.7])
cb = matplotlib.colorbar.ColorbarBase(ax3, cmap=cmap, norm=cNorm)
cNorm = colors.Normalize(vmin=0, vmax=T)
ScalarMap2 = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
grid = np.linspace(
np.min(np.array(sol['y'])) - .1,
np.max(np.array(sol['y'])) + .1, gridpoints)
for i in plot_times:
particles = sol['y'][:, i]
profile = blob(particles, grid, masses, eps)
true_time = (T / (max(plot_times) - 1)) * i
linecolor = ScalarMap2.to_rgba(true_time)
ax2.plot(grid, profile, color=linecolor)
ax2.plot([y0, y1], [0, 0], 'ro')
ax4 = fig.add_axes([0.94, 0.15, 0.02, 0.7])
cb = matplotlib.colorbar.ColorbarBase(ax4, cmap=cmap, norm=cNorm)
mng = plt.get_current_fig_manager()
mng.full_screen_toggle()
fig.set_size_inches((10, 5), forward=False)
fig.savefig(save_location + '.png', dpi=500)
return fig
def compute_and_plot_profiles(sol, masses, plot_times, cell_start, cell_end,eps,y0,y1,gridpoints, title):
cmap = plt.get_cmap('viridis')
fig, ax = plt.subplots(figsize = (7,5))
ax.set_title(title)
ax.set_xlabel('position')
ax.set_ylabel('density')
cNorm = colors.Normalize(vmin = 0, vmax = max(plot_times))
ScalarMap = cmx.ScalarMappable(norm = cNorm, cmap = cmap)
grid = np.linspace(cell_start, cell_end, gridpoints)
for i in plot_times:
particles = sol['y'][:,i]
profile = blob(particles, grid, masses, eps)
linecolor = ScalarMap.to_rgba(i)
ax.plot(grid, profile, color = linecolor)
ax.plot([y0,y1],[0,0],'ro')
ax2 = fig.add_axes([0.94,0.1,0.02,0.7])
cb = matplotlib.colorbar.ColorbarBase(ax2, cmap=cmap, norm=cNorm)
plt.savefig(title)
def plot_four_profiles(x_label, y_label, sol_dict_path, param_dict_path, plot_number, title, param_set = "drift", custom_params = None, save = False, save_path = None):
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2,2, sharex = True, sharey = True)
#ax1.set_xlabel('position')
ax1.set_ylabel(y_label)
#ax2.set_xlabel('position')
#ax2.set_ylabel('density')
ax3.set_xlabel(x_label)
ax3.set_ylabel(y_label)
ax4.set_xlabel(x_label)
#ax4.set_ylabel('density')
fig.suptitle(title)
ax4_box = fig.axes[3].get_position()
ax2_box = fig.axes[1].get_position()
ax4_box.x1 = ax4_box.x1 - .04
ax4_box.x0 = ax4_box.x0 - .04
ax2_box.x1 = ax2_box.x1 - .04
ax2_box.x0 = ax2_box.x0 - .04
fig.axes[3].set_position(ax4_box)
fig.axes[1].set_position(ax2_box)
if param_set == 'drift':
param_1 = (10,5,1)
param_2 = (10,1,5)
param_3 = (10,1,1)
param_4 = (10,5,5)
elif param_set == 'interaction':
param_1 = (5,10,1)
param_2 = (1,10,5)
param_3 = (1,10,1)
param_4 = (5,10,5)
else:
param_1 = custom_params[0]
param_2 = custom_params[1]
param_3 = custom_params[2]
param_4 = custom_params[3]
ax1.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_1[0], param_1[1], param_1[2]), pad = 3)
ax2.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_2[0], param_2[1], param_2[2]), pad = 3)
ax3.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_3[0], param_3[1], param_3[2]), pad = 3)
ax4.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_4[0], param_4[1], param_4[2]), pad = 3)
sol_dict = pickle.load(open(sol_dict_path, "rb"))
param_dict = pickle.load(open(param_dict_path, "rb"))
sol_dict.keys()
N = param_dict['N']
masses = param_dict['M']
eps = param_dict['eps']
y0 = param_dict['y0']
y1 = param_dict['y1']
T = param_dict['T']
sols = [sol_dict[param_1], sol_dict[param_2], sol_dict[param_3], sol_dict[param_4]]
plot_times = [compute_even_plot_times(len(sol['t']), plot_number) for sol in sols]
axess = [ax1, ax2, ax3, ax4]
cmap = plt.get_cmap('viridis')
cNorm = colors.Normalize(vmin = 0, vmax = T)
ScalarMap = cmx.ScalarMappable(norm = cNorm, cmap = cmap)
colorbar = fig.add_axes([0.90,0.15,0.02,0.7])
colorbar.set_title('time')
cb = matplotlib.colorbar.ColorbarBase(colorbar, cmap = cmap, norm = cNorm)
for i in range(4):
ax = axess[i]
plot_time = plot_times[i]
sol = sols[i]
grid = np.linspace(-2.1, 2.1, 100)
for i in plot_time:
particles = sol['y'][:,i]
profile = blob(particles, grid, masses, eps)
true_time = (T / (max(plot_time) -1)) * i
linecolor = ScalarMap.to_rgba(true_time)
ax.plot(grid, profile, color = linecolor)
ax.plot([y0,y1],[0,0],'ro')
return fig
def plot_six_profiles(x_label,
y_label,
sol_dict_path,
param_dict_path,
plot_number,
title,
moll_eps,
params=None):
fig, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(3,
2,
sharex=True,
sharey=True)
#ax1.set_xlabel('position')
ax1.set_ylabel(y_label)
#ax2.set_xlabel('position')
#ax2.set_ylabel('density')
ax3.set_ylabel(y_label)
ax5.set_ylabel(y_label)
ax5.set_xlabel(x_label)
ax6.set_xlabel(x_label)
#ax4.set_ylabel('density')
fig.suptitle(title)
ax4_box = fig.axes[3].get_position()
ax2_box = fig.axes[1].get_position()
ax6_box = fig.axes[5].get_position()
ax4_box.x1 = ax4_box.x1 - .04
ax4_box.x0 = ax4_box.x0 - .04
ax2_box.x1 = ax2_box.x1 - .04
ax2_box.x0 = ax2_box.x0 - .04
ax6_box.x1 = ax6_box.x1 - .04
ax6_box.x0 = ax6_box.x0 - .04
fig.axes[3].set_position(ax4_box)
fig.axes[1].set_position(ax2_box)
fig.axes[5].set_position(ax6_box)
fig.set_figheight(fig.get_figheight() + fig.get_figheight() * .3)
param_1 = params[0]
param_2 = params[1]
param_3 = params[2]
param_4 = params[3]
param_5 = params[4]
param_6 = params[5]
ax1.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_1[0], param_1[1],
param_1[2]),
pad=3)
ax2.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_2[0], param_2[1],
param_2[2]),
pad=3)
ax3.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_3[0], param_3[1],
param_3[2]),
pad=3)
ax4.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_4[0], param_4[1],
param_4[2]),
pad=3)
ax5.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_5[0], param_5[1],
param_5[2]),
pad=3)
ax6.set_title('$A= {}$, $B ={} $, $C = {}$'.format(param_6[0], param_6[1],
param_6[2]),
pad=3)
sol_dict = pickle.load(open(sol_dict_path, "rb"))
param_dict = pickle.load(open(param_dict_path, "rb"))
sol_dict.keys()
N = param_dict['N']
masses = param_dict['M']
eps = param_dict['eps']
y0 = param_dict['y0']
y1 = param_dict['y1']
T = param_dict['T']
sols = [
sol_dict[param_1], sol_dict[param_2], sol_dict[param_3],
sol_dict[param_4], sol_dict[param_5], sol_dict[param_6]
]
plot_times = [
compute_even_plot_times(len(sol['t']), plot_number) for sol in sols
]
axess = [ax1, ax2, ax3, ax4, ax5, ax6]
cmap = plt.get_cmap('jet')
cNorm = colors.Normalize(vmin=0, vmax=T)
ScalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
colorbar = fig.add_axes([0.90, 0.15, 0.02, 0.7])
colorbar.set_title('time')
cb = matplotlib.colorbar.ColorbarBase(colorbar, cmap=cmap, norm=cNorm)
for i in range(6):
ax = axess[i]
plot_time = plot_times[i]
sol = sols[i]
grid = np.linspace(-2.1, 2.1, 100)
for i in plot_time:
particles = sol['y'][:, i]
profile = blob(particles, grid, masses, moll_eps)
true_time = (T / (max(plot_time) - 1)) * i
linecolor = ScalarMap.to_rgba(true_time)
ax.plot(grid, profile, color=linecolor)
ax.plot([y0, y1], [0, 0], 'ro')
return fig