File size: 3,699 Bytes
ecdea35 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 |
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
def make_attention_table(att, tokens, numb, token_idx = 0, layerNumb = -1):
token_att = att[layerNumb, token_idx, range(1, len(tokens))]
token_label=[]
token_numb=[]
for idx, token in enumerate(tokens[1:]) :
token_label.append(f"<b>{token}</b>")
token_numb.append(f"{idx}")
pair = list(zip(token_numb, token_att))
df = pd.DataFrame(pair, columns=["Amino acid", "Attention rate"])
df.to_csv(f"amino_acid_seq_attention_{numb}.csv", index=None)
top3_idx = sorted(range(len(token_att)), key=lambda i: token_att[i], reverse=True)[:3]
colors = ['cornflowerblue', ] * len(token_numb)
for i in top3_idx:
colors[i] = 'crimson'
fig = go.Figure(data=[go.Bar(
x=df["Amino acid"],
y=df["Attention rate"],
# range_y=[min(token_att), max(token_att)],
marker_color=colors # marker color can be a single color value or an iterable
)])
# fig = px.histogram(df, x="Amino acid", y="Attention rate", range_y=[min(token_att), max(token_att)])
fig.update_layout(plot_bgcolor="white")
fig.update_xaxes(linecolor='rgba(0,0,0,0.25)', gridcolor='rgba(0,0,0,0)',mirror=False)
fig.update_yaxes(linecolor='rgba(0,0,0,0.25)', gridcolor='rgba(0,0,0,0.07)',mirror=False)
fig.update_layout(title={'text': "<b>Attention rate of amino acid sequence token</b>",
'font':{'size':40},
'y': 0.96,
'x': 0.5,
'xanchor': 'center',
'yanchor': 'top'},
xaxis=dict(tickmode='array',
tickvals=token_numb,
ticktext=token_label
),
xaxis_title={'text': "Amino acid sequence",
'font':{'size':30}},
yaxis_title={'text': "Attention rate",
'font':{'size':30}},
font=dict(family="Calibri, monospace",
size=17
))
fig.write_image(f'figures/Amino_acid_seq_{numb}.png', width=1.5*1200, height=0.75*1200, scale=2)
fig.show()
def read_attention():
df = pd.read_csv("../amino_acid_seq_attention.csv")
# d_flow_values = np.asarray(d_read_flow_values)
fig = px.bar(df, x="Amino acid", y="Attention rate", range_y=[min(df["Attention rate"]), max(df["Attention rate"])])
fig.update_layout(plot_bgcolor="white")
fig.update_xaxes(linecolor='rgba(0,0,0,0.25)', gridcolor='rgba(0,0,0,0)',mirror=False)
fig.update_yaxes(linecolor='rgba(0,0,0,0.25)', gridcolor='rgba(0,0,0,0.07)',mirror=False)
fig.update_layout(title={'text': "<b>Attention rate of amino acid sequence token</b>",
'font':{'size':40},
'y': 0.96,
'x': 0.5,
'xanchor': 'center',
'yanchor': 'top'},
xaxis_title={'text': "Amino acid sequence",
'font':{'size':30}},
yaxis_title={'text': "Attention rate",
'font':{'size':30}},
font=dict(family="Calibri, monospace",
size=17
))
fig.write_image('figures/Amino_acid_seq.png', width=1.5*1200, height=0.75*1200, scale=2)
fig.show()
if __name__ == '__main__':
read_attention() |