Visual Debugging
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@ -67,7 +67,7 @@ class FixpointExperiment(Experiment):
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net.self_attack()
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net.self_attack()
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i += 1
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i += 1
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if run_id:
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if run_id:
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weights = net.get_weights()
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weights = net.get_weights_flat()
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self.add_trajectory_segment(run_id, weights)
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self.add_trajectory_segment(run_id, weights)
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self.count(net)
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self.count(net)
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7
code/latent_trajectory_plot.html
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7
code/latent_trajectory_plot.html
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File diff suppressed because one or more lines are too long
@ -173,6 +173,7 @@ class FeedForwardNetwork(_BaseNetwork):
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bar.update()
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bar.update()
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return losses
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return losses
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if __name__ == '__main__':
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if __name__ == '__main__':
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with Experiment() as exp:
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with Experiment() as exp:
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features, cells, layers = 2, 2, 2
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features, cells, layers = 2, 2, 2
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@ -83,6 +83,9 @@ class NeuralNetwork(PrintingObject):
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def get_weights(self):
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def get_weights(self):
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return self.model.get_weights()
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return self.model.get_weights()
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def get_weights_flat(self):
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return np.hstack([weight.flatten() for weight in self.get_weights()])
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def set_weights(self, new_weights):
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def set_weights(self, new_weights):
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return self.model.set_weights(new_weights)
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return self.model.set_weights(new_weights)
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@ -603,9 +606,9 @@ class TrainingNeuralNetworkDecorator(NeuralNetwork):
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if __name__ == '__main__':
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if __name__ == '__main__':
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if False:
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if True:
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with FixpointExperiment() as exp:
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with FixpointExperiment() as exp:
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for run_id in tqdm(range(1)):
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for run_id in tqdm(range(100)):
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# net = WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation='linear')
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# net = WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation='linear')
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# net = AggregatingNeuralNetwork(aggregates=4, width=2, depth=2)\
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# net = AggregatingNeuralNetwork(aggregates=4, width=2, depth=2)\
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net = FFTNeuralNetwork(aggregates=4, width=2, depth=2) \
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net = FFTNeuralNetwork(aggregates=4, width=2, depth=2) \
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7
code/plot.html
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7
code/plot.html
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@ -22,47 +22,42 @@ def build_args():
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def plot_latent_trajectories(data_dict, filename='latent_trajectory_plot'):
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def plot_latent_trajectories(data_dict, filename='latent_trajectory_plot'):
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# TODO Fist and Last Position Markers
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def norm(val, a=0, b=0.25):
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return (val - a) / (b - a)
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bupu = cl.scales['9']['seq']['BuPu']
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bupu = cl.scales['9']['seq']['BuPu']
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scale = cl.interp(bupu, len(data_dict)) # Map color scale to N bins
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scale = cl.interp(bupu, len(data_dict)+1) # Map color scale to N bins
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# Fit the mebedding space
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# Fit the mebedding space
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transformer = TSNE()
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transformer = TSNE()
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for trajectory in data_dict:
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for trajectory_id in data_dict:
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transformer.fit(trajectory)
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transformer.fit(np.asarray(data_dict[trajectory_id]))
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# Transform data accordingly and plot it
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# Transform data accordingly and plot it
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data = []
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data = []
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for t_id, trajectory in enumerate(data_dict):
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for trajectory_id in data_dict:
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transformed = transformer.fit(trajectory)
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transformed = transformer._fit(np.asarray(data_dict[trajectory_id]))
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line_trace = go.Scatter(
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line_trace = go.Scatter(
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x=transformed[:, 0],
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x=transformed[:, 0],
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y=transformed[:, 1],
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y=transformed[:, 1],
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text='Hovertext goes here'.format(),
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text='Hovertext goes here'.format(),
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line=dict(color=scale[t_id]),
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line=dict(color=scale[trajectory_id]),
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# legendgroup='Position -{}'.format(pos),
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# legendgroup='Position -{}'.format(pos),
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# name='Position -{}'.format(pos),
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# name='Position -{}'.format(pos),
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showlegend=False,
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showlegend=False,
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# hoverinfo='text',
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# hoverinfo='text',
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mode='lines')
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mode='lines')
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line_start = go.Scatter(mode='markers', x=transformed[0, 0], y=transformed[0, 1],
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line_start = go.Scatter(mode='markers', x=[transformed[0, 0]], y=[transformed[0, 1]],
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marker=dict(
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marker=dict(
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color='rgb(255, 0, 0)',
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color='rgb(255, 0, 0)',
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size=2
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size=4
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),
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),
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showlegend=False
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showlegend=False
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)
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)
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line_end = go.Scatter(mode='markers', x=transformed[-1, 0], y=transformed[-1, 1],
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line_end = go.Scatter(mode='markers', x=[transformed[-1, 0]], y=[transformed[-1, 1]],
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marker=dict(
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marker=dict(
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color='rgb(0, 0, 0)',
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color='rgb(0, 0, 0)',
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size=2
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size=4
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),
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),
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showlegend=False
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showlegend=False
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)
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)
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data.extend([line_trace, line_start, line_end])
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data.extend([line_trace, line_start, line_end])
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layout = dict(title='{} - Latent Trajectory Movement'.format('Penis'),
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layout = dict(title='{} - Latent Trajectory Movement'.format('Penis'),
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@ -74,30 +69,30 @@ def plot_latent_trajectories(data_dict, filename='latent_trajectory_plot'):
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pass
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pass
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def plot_latent_trajectories_3D(param_dict, filename='plot'):
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def plot_latent_trajectories_3D(data_dict, filename='plot'):
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def norm(val, a=0, b=0.25):
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def norm(val, a=0, b=0.25):
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return (val - a) / (b - a)
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return (val - a) / (b - a)
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bupu = cl.scales['9']['seq']['BuPu']
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bupu = cl.scales['9']['seq']['BuPu']
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scale = cl.interp(bupu, len(param_dict.get('trajectories', []))) # Map color scale to N bins
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scale = cl.interp(bupu, len(data_dict)+1) # Map color scale to N bins
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max_len = max([len(trajectory) for trajectory in param_dict.get('trajectories', [])])
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max_len = max([len(trajectory) for trajectory in data_dict.values()])
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# Fit the mebedding space
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# Fit the mebedding space
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transformer = TSNE()
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transformer = TSNE()
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for trajectory in param_dict.get('trajectories', []):
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for trajectory_id in data_dict:
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transformer.fit(trajectory)
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transformer.fit(data_dict[trajectory_id])
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# Transform data accordingly and plot it
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# Transform data accordingly and plot it
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data = []
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data = []
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for t_id, trajectory in enumerate(param_dict.get('trajectories', [])):
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for trajectory_id in data_dict:
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transformed = transformer.fit(trajectory)
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transformed = transformer._fit(np.asarray(data_dict[trajectory_id]))
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trace = go.Scatter3d(
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trace = go.Scatter3d(
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x=transformed[:, 0],
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x=transformed[:, 0],
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y=transformed[:, 1],
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y=transformed[:, 1],
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z=np.arange(max(max_len)),
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z=np.arange(transformed.shape[0]),
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text='Hovertext goes here'.format(),
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text='Hovertext goes here'.format(),
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line=dict(color=scale[t_id]),
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line=dict(color=scale[trajectory_id]),
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# legendgroup='Position -{}'.format(pos),
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# legendgroup='Position -{}'.format(pos),
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# name='Position -{}'.format(pos),
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# name='Position -{}'.format(pos),
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showlegend=False,
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showlegend=False,
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@ -106,9 +101,9 @@ def plot_latent_trajectories_3D(param_dict, filename='plot'):
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data.append(trace)
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data.append(trace)
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layout = go.Layout(scene=dict(aspectratio=dict(x=2, y=2, z=1),
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layout = go.Layout(scene=dict(aspectratio=dict(x=2, y=2, z=1),
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xaxis=dict(tickwidth=1, title='Number of Cells'),
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xaxis=dict(tickwidth=1, title='Transformed X'),
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yaxis=dict(tickwidth=1, title='Number of Layers'),
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yaxis=dict(tickwidth=1, title='transformed Y'),
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zaxis=dict(tickwidth=1, title='Position -pX')),
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zaxis=dict(tickwidth=1, title='Epoch')),
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title='{} - Latent Trajectory Movement'.format('Penis'),
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title='{} - Latent Trajectory Movement'.format('Penis'),
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width=800, height=800,
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width=800, height=800,
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margin=dict(l=0, r=0, b=0, t=0))
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margin=dict(l=0, r=0, b=0, t=0))
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@ -125,18 +120,18 @@ def plot_histogram(bars_dict_list, filename='histogram_plot'):
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data = []
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data = []
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for bar_id, bars_dict in bars_dict_list:
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for bar_id, bars_dict in bars_dict_list:
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hist = go.Histogram(
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hist = go.Histogram(
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histfunc="count",
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histfunc="count",
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y=bars_dict.get('value', 14),
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y=bars_dict.get('value', 14),
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x=bars_dict.get('name', 'gimme a name'),
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x=bars_dict.get('name', 'gimme a name'),
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showlegend=False,
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showlegend=False,
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marker=dict(
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marker=dict(
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color=ryb[bar_id]
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color=ryb[bar_id]
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),
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),
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)
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)
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data.append(hist)
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data.append(hist)
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layout=dict(title='{} Histogram Plot'.format('Experiment Name Penis'),
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layout=dict(title='{} Histogram Plot'.format('Experiment Name Penis'),
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height=400, width=400, margin=dict(l=0, r=0, t=0, b=0))
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height=400, width=400, margin=dict(l=0, r=0, t=0, b=0))
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fig = go.Figure(data=data, layout=layout)
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fig = go.Figure(data=data, layout=layout)
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pl.offline.plot(fig, auto_open=True, filename=filename)
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pl.offline.plot(fig, auto_open=True, filename=filename)
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@ -161,7 +156,7 @@ def line_plot(line_dict_list, filename='lineplot'):
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marker=dict(color="#444"),
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marker=dict(color="#444"),
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line=dict(width=0),
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line=dict(width=0),
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fillcolor=rdylgn_background[line_id],
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fillcolor=rdylgn_background[line_id],
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)
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)
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trace = go.Scatter(
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trace = go.Scatter(
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x=line_dict['x'],
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x=line_dict['x'],
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@ -183,7 +178,7 @@ def line_plot(line_dict_list, filename='lineplot'):
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data.extend([upper_bound, trace, lower_bound])
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data.extend([upper_bound, trace, lower_bound])
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layout=dict(title='{} Line Plot'.format('Experiment Name Penis'),
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layout=dict(title='{} Line Plot'.format('Experiment Name Penis'),
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height=800, width=800, margin=dict(l=0, r=0, t=0, b=0))
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height=800, width=800, margin=dict(l=0, r=0, t=0, b=0))
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fig = go.Figure(data=data, layout=layout)
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fig = go.Figure(data=data, layout=layout)
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pl.offline.plot(fig, auto_open=True, filename=filename)
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pl.offline.plot(fig, auto_open=True, filename=filename)
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@ -195,4 +190,8 @@ if __name__ == '__main__':
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in_file = args.in_file[0]
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in_file = args.in_file[0]
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out_file = args.out_file
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out_file = args.out_file
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with open(in_file, 'rb') as in_f:
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experiment = dill.load(in_f)
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plot_latent_trajectories_3D(experiment.data_storage)
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print('aha')
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print('aha')
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