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plots.py
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plots.py
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import numpy as np
import plotly.graph_objects as go
class DataViz:
def plotHist(self, activations, unit, layer):
u_act=[i[unit] for i in activations]
print (u_act)
fig = go.Figure(data=[go.Histogram(x=u_act)])
fig.update_layout(
title=go.layout.Title(
text="Activations histogram for unit " +str(unit)+ " in the hidden layer" +str(layer),
xref="paper",
),
xaxis=go.layout.XAxis(
title=go.layout.xaxis.Title(
text="Activations",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
),
yaxis=go.layout.YAxis(
title=go.layout.yaxis.Title(
text="Count",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
)
)
fig.show()
return
def plotLoss(self, loss, val_loss, i):
fig = go.Figure()
fig.add_trace(go.Scatter( y=loss,
mode='lines',
name='Training loss'))
fig.add_trace(go.Scatter( y=val_loss,
mode='lines+markers',
name='Validation Loss'))
fig.update_layout(
title=go.layout.Title(
text="Model loss",
xref="paper",
),
xaxis=go.layout.XAxis(
title=go.layout.xaxis.Title(
text=i,
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
),
yaxis=go.layout.YAxis(
title=go.layout.yaxis.Title(
text="Loss",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
)
)
fig.show()
return
def plotAcc(self, accuracy, v_acc):
fig = go.Figure()
fig.add_trace(go.Scatter(y=accuracy,
mode='lines',
name='Training'))
fig.add_trace(go.Scatter(y=v_acc,
mode='lines+markers',
name='Validation'))
fig.update_layout(
title=go.layout.Title(
text="Model accuracy",
xref="paper",
),
xaxis=go.layout.XAxis(
title=go.layout.xaxis.Title(
text="Iterations",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
),
yaxis=go.layout.YAxis(
title=go.layout.yaxis.Title(
text="Accuracy",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
)
)
fig.show()
return
def plotWeights(self, w, node, layer):
def unit_vector(vector):
""" Returns the unit vector of the vector. """
return vector / np.linalg.norm(vector)
def angle_between(v1, v2):
""" Returns the angle in radians between vectors 'v1' and 'v2'::
"""
v1_u = unit_vector(v1)
v2_u = unit_vector(v2)
return np.arccos(np.clip(np.dot(v1_u, v2_u), -1.0, 1.0))
def angles_w(weights, n):
ang=[]
for i in range(len(weights)-1):
ang.append(angle_between(weights[i][n], weights[i+1][n]))
return ang
a = angles_w(w, node)
x = [i for i in range(1, len(a)+1)]
fig = go.Figure(data=go.Scatter(x=x, y=a))
fig.update_layout(
title=go.layout.Title(
text="Weights of hidden layer " + str(layer) + "," +str(node) +" evolution through iterations",
xref="paper",
),
xaxis=go.layout.XAxis(
title=go.layout.xaxis.Title(
text="Iterations",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
),
yaxis=go.layout.YAxis(
title=go.layout.yaxis.Title(
text="Angle",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
)
)
fig.show()
return