def visualise(project_id=str(),
max_distance=False,
critical_concentration=None,
heatmap=False,
simulation_number=str(),
concentration=False):
if max_distance:
maximal_distances = json.load(
open(
'Dataset/Maximal_distances/' + str(project_id) + '/' +
str(critical_concentration), 'r'))
Visualiser.plot_scatter_2d(x=numpy.arange(
len(maximal_distances['concentrated'])),
y=maximal_distances['concentrated'],
project_id=project_id,
info=str(critical_concentration))
if heatmap:
info = json.load(open(project_id, 'r'))
lattice = Lattice.load(project_id=project_id,
simulation_number=simulation_number)
print(lattice.cells)
# critical_concentration = str(critical_concentration)
if critical_concentration:
Visualiser.concentration_heatmap(
lattice=lattice,
simulation_number=simulation_number,
critical_concentration=critical_concentration)
else:
Visualiser.concentration_heatmap(
lattice=lattice, simulation_number=simulation_number)
if concentration:
data = []
# for simulation_number in [50, 100, 150, 300, 400, 450, 499]:
# for simulation_number in [50, 100, 150, 200, 250, 300, 350, 400, 450, 499]:
info = json.load(open(project_id, 'r')),
lattice = Lattice.load(project_id=project_id,
simulation_number=str(300))
# lattice.critical_concentration = 3500
# lattice.update_critical()
val = dict()
for cell in lattice.cells.values():
val[cell.index.x_axis] = cell.get_concentration()
od = OrderedDict(sorted(val.items()))
x = []
y = []
for key, val in od.items():
x.append(key)
y.append(val)
# if x or y:
# x.insert(0,x[0])
# y.insert(0,0)
# x.append(x[-1])
# y.append(0)
data.append([x, y, simulation_number])
Visualiser.plot_scatter_2d(data=data, project_id=project_id)
def inspect_lattice(self, project_id=str(), critical_concentration=None):
info = dict()
info = json.load(open(project_id, 'r'))
lattice = Lattice()
lattice.critical_concentration = int(1e5) * critical_concentration
i = 0
while True:
if os.path.exists('Dataset/Lattices/' + project_id + '/' + str(i)):
print(str(i))
# loading state
lattice.cells = Lattice.load(cells_only=True,
project_id=project_id,
simulation_number=i)
# inspecting loaded state
lattice.update_critical()
lattice.sort_critical()
lattice.update_maximal_distances(dimension=info['dimension'])
i += 1
else:
break
json.dump(
lattice.maximal_distances,
open(
'Dataset/Maximal_distances/' + info['project_id'] + '/' +
str(critical_concentration), 'w'))
def inspect_lattice(self, critical_concentration):
info = dict()
info = json.load(open(str(self.id) + self.sub_id + 'info', 'r'))
lattice = Lattice()
lattice.critical_concentration = critical_concentration
i = 0
while True:
if os.path.exists(self.id + self.sub_id + 'Lattices/' + str(i)):
print(str(i))
lattice.cells = Lattice.load(cells_only=True,
project_id=self.id,
sub_id=self.sub_id,
simulation_number=i,
implementation=True)
lattice.update_critical()
lattice.update_maximal_distances(dimension=info['dimension'],
check_area=False)
i += 1
else:
break
json.dump(
lattice.maximal_distances['concentrated'],
open(
self.id + self.sub_id + 'Maximal_distances/' +
str(critical_concentration) + 'n2', 'w'))
def get_data(self, simulation_number=int()):
data = np.zeros((int(self.y_max-self.y_min), int(self.x_max-self.x_min)))
cells = Lattice.load(project_id=self.project_id, simulation_number=simulation_number, cells_only=True)
for cell in cells.values():
if cell.get_concentration() > self.critical_c:
if cell.position(1).x_axis > self.x_min and cell.position(1).x_axis < self.x_max:
if cell.position(1).y_axis > self.y_min and cell.position(1).y_axis < self.y_max:
data[int((cell.index.y_axis-self.y_min)), int((cell.index.x_axis-self.x_min))] = cell.counter
return data
def visualise(self,
heatmap=False,
max_distance=False,
critical_concentration=float(),
simulation_number=None):
if heatmap:
x_max = 60
x_min = -60
y_max = 60
y_min = -60
y_size = int((y_max - y_min)) + 1
x_size = int((x_max - x_min)) + 1
data = np.zeros((y_size, x_size))
plot_data = []
for i in range(10, 700, 50):
lattice = Lattice.load(project_id=self.id,
sub_id=self.sub_id,
simulation_number=i,
implementation=True)
for cell in lattice.cells.values():
if cell.get_concentration() > critical_concentration:
if cell.position(1).x_axis > x_min and cell.position(
1).x_axis < x_max:
if cell.position(
1).y_axis > y_min and cell.position(
1).y_axis < y_max:
data[int((cell.index.y_axis - y_min)),
int((cell.index.x_axis -
x_min))] = cell.counter
graph_x_axis = list(
range(int(x_min * lattice.density),
int(x_max * lattice.density)))
graph_y_axis = list(
range(int(y_min * lattice.density),
int(y_max * lattice.density)))
trace = go.Heatmap(z=data, x=graph_x_axis, y=graph_y_axis)
plot_data.append(trace)
fig = tools.make_subplots(rows=4, cols=4)
for i in range(len(plot_data)):
print(plot_data[i]['z'])
# fig.append_trace(plot_data[i], i//4+1, i%4+1)
# plotly.offline.plot(fig, filename='H' + str(simulation_number) + '.html',
# image_filename='2D-h' + str(simulation_number) ,
# image_width=800, image_height=800, image='png', auto_open=True)
# Visualiser.concentration_heatmap(lattice=lattice, simulation_number=simulation_number, critical_concentration=critical_concentration)
if max_distance:
maximal_distances = json.load(
open(
str(self.id) + self.sub_id + 'Maximal_distances/' +
str(critical_concentration) + 'n2', 'r'))
print(maximal_distances)
trace = go.Scatter(
x=np.arange(len(maximal_distances)),
y=maximal_distances,
mode='markers',
)
data = [trace]
layout = go.Layout(
title='',
xaxis=dict(title='Počet iteračných krokov',
titlefont=dict(family='Courier New, monospace',
size=14,
color='#7f7f7f')),
yaxis=dict(title='Polomer oblasti s kritickou koncentráciou',
titlefont=dict(family='Courier New, monospace',
size=14,
color='#7f7f7f')))
fig = go.Figure(data=data, layout=layout)
plotly.offline.plot(fig,
filename='impl2-2D-1e5-R(n)' +
str(critical_concentration) + 'n2' + '.html')
def visualise(self,
heatmap=False,
max_distance=False,
critical_concentration=float(),
simulation_number=None):
if heatmap:
lattice = Lattice.load(project_id=self.id,
sub_id=self.sub_id,
simulation_number=simulation_number,
implementation=True)
print(lattice.dictionary())
Visualiser.concentration_heatmap(
lattice=lattice,
simulation_number=simulation_number,
critical_concentration=critical_concentration)
# if heatmap:
# x_max = 80
# x_min = -80
# y_max = 0
# y_min = 0
#
# fig = tools.make_subplots(rows=7, cols=1, print_grid=False)
#
# y_size = int((y_max - y_min)) + 1
# x_size = int((x_max - x_min)) + 1
# data = np.zeros((y_size, x_size))
#
# for i in range(50,700,100):
# lattice = Lattice.load(project_id=self.id, sub_id=self.sub_id, simulation_number=i, implementation=True)
#
# for cell in lattice.cells.values():
# if cell.get_concentration() > critical_concentration:
# if cell.position(1).x_axis > x_min and cell.position(1).x_axis < x_max:
# data[int((cell.index.y_axis - y_min)), int((cell.index.x_axis - x_min))] = cell.counter
#
# graph_x_axis = list(range(int(x_min * lattice.density), int(x_max * lattice.density)))
# graph_y_axis = list(range(int(y_min * lattice.density), int(y_max * lattice.density)))
#
# # colorscale = [
# # [0, 'rgb(0, 0, 0)'],
# # [0.1, 'rgb(0, 0, 0)'],
# # [0.1, 'rgb(20, 20, 20)'],
# # [0.2, 'rgb(20, 20, 20)'],
# # [0.2, 'rgb(40, 40, 40)'],
# # [0.3, 'rgb(40, 40, 40)'],
# #
# # [0.3, 'rgb(60, 60, 60)'],
# # [0.4, 'rgb(60, 60, 60)'],
# #
# # [0.4, 'rgb(80, 80, 80)'],
# # [0.5, 'rgb(80, 80, 80)'],
# #
# # [0.5, 'rgb(100, 100, 100)'],
# # [0.6, 'rgb(100, 100, 100)'],
# #
# # [0.6, 'rgb(120, 120, 120)'],
# # [0.7, 'rgb(120, 120, 120)'],
# #
# # [0.7, 'rgb(140, 140, 140)'],
# # [0.8, 'rgb(140, 140, 140)'],
# #
# # [0.8, 'rgb(160, 160, 160)'],
# # [0.9, 'rgb(160, 160, 160)'],
# #
# # [0.9, 'rgb(180, 180, 180)'],
# # [1.0, 'rgb(180, 180, 180)']]
# trace = go.Heatmap(z=data, x=graph_x_axis, y=graph_y_axis)
# fig.append_trace(trace, int(i/100+0.5), 1)
# # , colorscale=colorscale)
#
# layout = go.Layout(title='Rozloženie koncentrácie pre 1D prípad',
# xaxis=dict(title='Priestorová súradnica x'),
# # titlefont=dict(family='Courier New, monospace', size=18, color='#7f7f7f')),
# yaxis=dict(title='y = 0'),)
# # titlefont=dict(family='Courier New, monospace', size=18, color='#7f7f7f')))
#
#
# fig['layout'].update(height=1000, width=1000, title='Multiple Subplots')
# # fig = go.Figure(data=plot_data, layout=layout)
# plotly.offline.plot(fig, filename='H'+str(simulation_number)+'.html',
# image_filename='h'+str(simulation_number), image_width=800, image_height=800, image='png',
# auto_open=True)
# # Visualiser.concentration_heatmap(lattice=lattice, simulation_number=simulation_number, critical_concentration=critical_concentration)
if max_distance:
maximal_distances = json.load(
open(
str(self.id) + self.sub_id + '/Maximal_distances/' +
str(critical_concentration) + 'n2A', 'r'))
print(maximal_distances)
trace = go.Scatter(
x=np.arange(len(maximal_distances)),
y=maximal_distances,
mode='lines+markers',
)
data = [trace]
layout = go.Layout(
title='',
xaxis=dict(title='Počet iteračných krokov',
titlefont=dict(family='Courier New, monospace',
size=14,
color='#7f7f7f')),
yaxis=dict(title='Polomer oblasti s kritickou koncentráciou',
titlefont=dict(family='Courier New, monospace',
size=14,
color='#7f7f7f')))
fig = go.Figure(data=data, layout=layout)
plotly.offline.plot(fig,
filename='impl1-2D-1e5-R(n)' +
str(critical_concentration) + 'n2A' + '.html')
