def plot_full_render(self, first_render, wave_data_dict, plot_data_state,
plot_data_mol, plot_data_concentration, n_steps,
vessels: vessel.Vessel, step_num):
'''
Method to plot thermodynamic variables and spectral data.
Plots a significant amount of data for a more in-depth
understanding of the information portrayed.
Parameters
---------------
`first_render` : `boolean`
Indicates whether a plot has been already rendered
`wave_data_dict` : `dict`
A dictionary containing all the wave data
`plot_data_state` : `list`
A list containing the states to be plotted such as time,
temperature, volume, pressure, and reactant amounts
`plot_data_mol` : `list`
A list containing the molar amounts of reactants and products
`plot_data_concentration` : `list`
A list containing the concentration of reactants and products
`n_steps` : `int`
The number of increments into which the action is split
`vessels` : `vessel.Vessel`
A vessel containing methods to obtain thermodynamic data
`step_num` : `int`
The step number the environment is currently on
Returns
---------------
None
Raises
---------------
None
'''
num_list = [
plot_data_state[0][0], plot_data_state[1][0],
plot_data_state[2][0], plot_data_state[3][0]
] + self.get_ni_num()
reactants = []
for reactant in self.reactants:
name = reactant.replace("[", "").replace("]", "")
short_name = name[0:5]
reactants.append(short_name)
label_list = ['t', 'T', 'V', 'P'] + reactants
spectra_len = wave_data_dict["spectra_len"]
absorb = wave_data_dict["absorb"]
wave = wave_data_dict["wave"]
wave_min = wave_data_dict["wave_min"]
wave_max = wave_data_dict["wave_max"]
peak = CharacterizationBench().get_spectra_peak(
vessels, materials=self.materials)
dash_spectra = CharacterizationBench().get_dash_line_spectra(
vessels, materials=self.materials)
# The first render is required to initialize the figure
if first_render:
plt.close('all')
plt.ion()
self._plot_fig, self._plot_axs = plt.subplots(3,
3,
figsize=(24, 12))
# Time vs. Molar_Amount graph ********************** Index: (0, 0)
self._plot_lines_amount = np.zeros((self.n.shape[0], 2, 20))
for i in range(self.n.shape[0]):
self._plot_lines_amount[i][0][step_num -
1:] = (plot_data_state[0][0])
self._plot_lines_amount[i][1][step_num -
1:] = (plot_data_mol[i][0])
self._plot_axs[0, 0].plot(self._plot_lines_amount[i][0],
self._plot_lines_amount[i][1],
label=self.materials[i])
self._plot_axs[0, 0].set_xlim(
[0.0, vessels.get_defaultdt() * n_steps])
self._plot_axs[0, 0].set_ylim([0.0, np.mean(plot_data_mol)])
self._plot_axs[0, 0].set_xlabel('Time (s)')
self._plot_axs[0, 0].set_ylabel('Molar Amount (mol)')
self._plot_axs[0, 0].legend()
# Time vs. Molar_Concentration graph *************** Index: (0, 1)
self._plot_lines_concentration = np.zeros((self.n.shape[0], 2, 20))
total_conc = 0
for i in range(self.n.shape[0]):
total_conc += plot_data_concentration[i][0]
for i in range(self.n.shape[0]):
self._plot_lines_concentration[i][0][step_num - 1:] = (
plot_data_state[0][0])
self._plot_lines_concentration[i][1][step_num - 1:] = (
plot_data_concentration[i][0])
self._plot_axs[0, 1].plot(self._plot_lines_concentration[i][0],
self._plot_lines_concentration[i][1],
label=self.materials[i])
self._plot_axs[2, 0].plot(
self._plot_lines_concentration[i][0],
self._plot_lines_concentration[i][1] / total_conc,
label=self.materials[i])
self._plot_axs[0, 1].set_xlim(
[0.0, vessels.get_defaultdt() * n_steps])
self._plot_axs[0,
1].set_ylim([0.0,
np.mean(plot_data_concentration)])
self._plot_axs[0, 1].set_xlabel('Time (s)')
self._plot_axs[0, 1].set_ylabel('Molar Concentration (mol/L)')
self._plot_axs[0, 1].legend()
# Time vs. Temperature + Time vs. Volume graph *************** Index: (0, 2)
self._plot_lines_temp = np.zeros((1, 2, 20))
self._plot_lines_temp[0][0][step_num -
1:] = (plot_data_state[0][0])
self._plot_lines_temp[0][1][step_num -
1:] = (plot_data_state[1][0])
self._plot_axs[0, 2].plot(self._plot_lines_temp[0][0],
self._plot_lines_temp[0][1],
label='T')
self._plot_lines_vol = np.zeros((1, 2, 20))
self._plot_lines_vol[0][0][step_num - 1:] = (plot_data_state[0][0])
self._plot_lines_vol[0][1][step_num - 1:] = (plot_data_state[2][0])
self._plot_axs[0, 2].plot(self._plot_lines_vol[0][0],
self._plot_lines_vol[0][1],
label='V')
self._plot_axs[0, 2].set_xlim(
[0.0, vessels.get_defaultdt() * n_steps])
self._plot_axs[0, 2].set_ylim([0, 1.2])
self._plot_axs[0, 2].set_xlabel('Time (s)')
self._plot_axs[0, 2].set_ylabel('T and V (map to range [0, 1])')
self._plot_axs[0, 2].legend()
# Time vs. Pressure graph *************** Index: (1, 0)
self._plot_lines_pressure = np.zeros((1, 2, 20))
self._plot_lines_pressure[0][0][step_num -
1:] = (plot_data_state[0][0])
self._plot_lines_pressure[0][1][step_num -
1:] = (plot_data_state[3][0])
self._plot_axs[1, 0].plot(self._plot_lines_pressure[0][0],
self._plot_lines_pressure[0][1],
label='V')
self._plot_axs[1, 0].set_xlim(
[0.0, vessels.get_defaultdt() * n_steps])
self._plot_axs[1, 0].set_ylim([0, vessels.get_pmax()])
self._plot_axs[1, 0].set_xlabel('Time (s)')
self._plot_axs[1, 0].set_ylabel('Pressure (kPa)')
# Solid Spectra graph *************** Index: (1, 1)
__ = self._plot_axs[1, 1].plot(
wave, # wavelength space (ranging from wave_min to wave_max)
absorb # absorb spectra
)[0]
# dash spectra
for spectra in dash_spectra:
self._plot_axs[1, 1].plot(wave, spectra, linestyle='dashed')
# include the labelling when plotting spectral peaks
for i in range(len(peak)):
self._plot_axs[1, 1].scatter(peak[i][0],
peak[i][1],
label=peak[i][2])
self._plot_axs[1, 1].set_xlim([wave_min, wave_max])
self._plot_axs[1, 1].set_ylim([0, 1.2])
self._plot_axs[1, 1].set_xlabel('Wavelength (nm)')
self._plot_axs[1, 1].set_ylabel('Absorbance')
self._plot_axs[1, 1].legend()
# bar chart plotting the time, tempurature, pressure, and amount of each
# species left in hand *************** Index: (1, 2)
__ = self._plot_axs[1, 2].bar(range(len(num_list)),
num_list,
tick_label=label_list)[0]
self._plot_axs[1, 2].set_ylim([0, 1])
self._plot_axs[2, 0].set_xlim(
[0.0, vessels.get_defaultdt() * n_steps])
self._plot_axs[2, 0].set_ylim([0.0, 1.0])
self._plot_axs[2, 0].set_xlabel('Time (s)')
self._plot_axs[2, 0].set_ylabel('Purity')
self._plot_axs[2, 0].legend()
# draw and show the full graph
self._plot_fig.canvas.draw()
plt.show()
# All other renders serve to update the existing figure with the new current state;
# it is assumed that the above actions have already been carried out
else:
# set data for the Time vs. Molar_Amount graph *************** Index: (0, 0)
curent_time = plot_data_state[0][-1]
# update the lines data
total_conc = 0
for i in range(self.n.shape[0]):
total_conc += plot_data_concentration[i][0]
for i in range(self.n.shape[0]):
# populate the lines amount array with the updated number of mols
self._plot_lines_amount[i][0][step_num -
1:] = (plot_data_state[0][0])
self._plot_lines_amount[i][1][step_num -
1:] = (plot_data_mol[i][0])
self._plot_axs[0, 0].lines[i].set_xdata(
self._plot_lines_amount[i][0])
self._plot_axs[0, 0].lines[i].set_ydata(
self._plot_lines_amount[i][1])
# populate the lines concentration array with the updated number of concentration
self._plot_lines_concentration[i][0][step_num - 1:] = (
plot_data_state[0][0])
self._plot_lines_concentration[i][1][step_num - 1:] = (
plot_data_concentration[i][0])
self._plot_axs[0, 1].lines[i].set_xdata(
self._plot_lines_concentration[i][0])
self._plot_axs[0, 1].lines[i].set_ydata(
self._plot_lines_concentration[i][1])
self._plot_axs[2, 0].lines[i].set_xdata(
self._plot_lines_concentration[i][0])
self._plot_axs[2, 0].lines[i].set_ydata(
self._plot_lines_concentration[i][1] / total_conc)
# reset each plot's x-limit because the latest action occurred at a greater time-value
self._plot_axs[0, 0].set_xlim([0.0, curent_time])
self._plot_axs[0, 1].set_xlim([0.0, curent_time])
# reset each plot's y-limit in order to fit and show all materials on the graph
self._plot_axs[0, 0].set_ylim([0.0, np.mean(plot_data_mol)])
self._plot_axs[0,
1].set_ylim([0.0,
np.mean(plot_data_concentration)])
# set data for Time vs. Temp and Time vs. Volume graphs *************** Index: (0, 2)
self._plot_lines_temp[0][0][step_num -
1:] = (plot_data_state[0][0])
self._plot_lines_temp[0][1][step_num -
1:] = (plot_data_state[1][0])
self._plot_lines_vol[0][0][step_num - 1:] = (plot_data_state[0][0])
self._plot_lines_vol[0][1][step_num - 1:] = (plot_data_state[2][0])
self._plot_axs[0,
2].lines[0].set_xdata(self._plot_lines_temp[0][0])
self._plot_axs[0,
2].lines[0].set_ydata(self._plot_lines_temp[0][1])
self._plot_axs[0, 2].lines[1].set_xdata(self._plot_lines_vol[0][0])
self._plot_axs[0, 2].lines[1].set_ydata(self._plot_lines_vol[0][1])
# reset xlimit since t extend
self._plot_axs[0, 2].set_xlim([0.0, curent_time])
# set data for Time vs. Pressure graph *************** Index: (1, 0)
self._plot_lines_pressure[0][0][step_num -
1:] = (plot_data_state[0][0])
self._plot_lines_pressure[0][1][step_num -
1:] = (plot_data_state[3][0])
self._plot_axs[1, 0].lines[0].set_xdata(
self._plot_lines_pressure[0][0])
self._plot_axs[1, 0].lines[0].set_ydata(
self._plot_lines_pressure[0][1])
self._plot_axs[1, 0].set_xlim([0.0, curent_time
]) # reset xlime since t extend
self._plot_axs[1,
0].set_ylim([0.0,
np.max(plot_data_state[3]) * 1.1])
# reset the Solid Spectra graph
self._plot_axs[1, 1].cla()
__ = self._plot_axs[1, 1].plot(
wave, # wavelength space (ranging from wave_min to wave_max)
absorb, # absorb spectra
)[0]
# obtain the new dash spectra data
for __, item in enumerate(dash_spectra):
self._plot_axs[1, 1].plot(wave, item, linestyle='dashed')
# reset the spectra peak labelling
for i in range(len(peak)):
self._plot_axs[1, 1].scatter(peak[i][0],
peak[i][1],
label=peak[i][2])
self._plot_axs[1, 1].set_xlim([wave_min, wave_max])
self._plot_axs[1, 1].set_ylim([0, 1.2])
self._plot_axs[1, 1].set_xlabel('Wavelength (nm)')
self._plot_axs[1, 1].set_ylabel('Absorbance')
self._plot_axs[1, 1].legend()
# bar chart
self._plot_axs[1, 2].cla()
__ = self._plot_axs[1, 2].bar(
range(len(num_list)),
num_list,
tick_label=label_list,
)[0]
self._plot_axs[1, 2].set_ylim([0, 1])
# re-draw the graph
self._plot_fig.canvas.draw()
plt.pause(0.000001)
def plotting_step(self, t, tmax, vessels: vessel.Vessel):
'''
Set up a method to handle the acquisition of the necessary plotting parameters
from an input vessel.
Parameters
---------------
`t` : `float`
Current amount of time
`tmax` : `float`
Maximum time allowed
`vessels` : `vessel.Vessel`
A vessel containing methods to acquire the necessary parameters
Returns
---------------
`plot_data_state` : `list`
A list containing the states to be plotted such as time,
temperature, volume, pressure, and reactant amounts
`plot_data_mol` : `list`
A list containing the molar amounts of reactants and products
`plot_data_concentration` : `list`
A list containing the concentration of reactants and products
Raises
---------------
None
'''
# acquire the necessary parameters from the vessel
T = vessels.get_temperature()
V = vessels.get_volume()
# V = 0.0025
# create containers to hold the plotting parameters
plot_data_state = [[], [], [], []]
plot_data_mol = [[] for _ in range(self.n.shape[0])]
plot_data_concentration = [[] for _ in range(self.n.shape[0])]
# Record time data
plot_data_state[0].append(t / tmax)
# record temperature data
Tmin = vessels.get_Tmin()
Tmax = vessels.get_Tmax()
plot_data_state[1].append((T - Tmin) / (Tmax - Tmin))
# record volume data
Vmin = vessels.get_min_volume()
Vmax = vessels.get_max_volume()
plot_data_state[2].append((V - Vmin) / (Vmax - Vmin))
# record pressure data
P = vessels.get_pressure()
plot_data_state[3].append(P / vessels.get_pmax())
# calculate and record the molar concentrations of the reactants and products
C = vessels.get_concentration(materials=self.materials)
for j in range(self.n.shape[0]):
plot_data_mol[j].append(self.n[j])
plot_data_concentration[j].append(C[j])
return plot_data_state, plot_data_mol, plot_data_concentration