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993103f 42acaf4 993103f 42acaf4 d0f8e2d 42acaf4 d0f8e2d 42acaf4 d0f8e2d 42acaf4 d0f8e2d 42acaf4 993103f | 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 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 | import plost
import streamlit as st
import pandas as pd
import numpy as np
import jsonlines as jsl
import datetime
import altair as alt
from utils import *
trade_ibkr_dict = {
'usd_cad':['USDCAD',False,'normal'],
'usd_chf':['CHFUSD',True,'normal'],
'usdt_chf':['CHFUSD',True,'normal'],
'dai_usdt':['stable',False,'stable'],
'eur_usd':['EURUSD',False,'normal'],
'usdt_eur':['EURUSD',True,'normal'],
'usdt_cad':['USDCAD',False,'normal'],
'usdc_eur':['EURUSD',True,'normal'],
'usdt_gbp':['GBPUSD',True,'normal'],
'gbp_usd':['GBPUSD',False,'normal'],
'eur_chf':['cross',False,'cross'],
'aud_usd':['AUDUSD',False,'normal'],
'dai_eur':['EURUSD',True,'normal'],
'usdc_usdt':['stable',False,'stable'],
'usdt_aud':['AUDUSD',True,'normal'],
'dai_usd':['stable',False,'stable'],
'eur_gbp':['cross',False,'cross'],
'usdc_gbp':['GBPUSD',True,'normal'],
'usdt_usd':['stable',False,'stable'],
'usdc_usd':['stable',False,'stable'],
'paxg_eur':['cross',False,'cross'],
'usdc_aud':['AUDUSD',True,'normal'],
'paxg_usd':['XAUUSD',False,'normal']
}
balance_df,keys = get_balance_data()
st.title("Assets Changes")
options = st.multiselect(
'Select Assets',
list(keys),)
plost.line_chart(
balance_df,
x='timestamp',
y=(options),
# 👈 This is magic!
)
trade_df = get_trade_parquet()
ibkr_df = get_ibkr_parquet()
st.title('Trades')
st.markdown('**Premium**')
trade_opt = st.selectbox(
'Select Trade Pair',
list(trade_df.currency_pair.unique())
)
params = trade_ibkr_dict[trade_opt]
trade_for_vis = trade_df[trade_df.currency_pair==trade_opt]
if params[2] == 'normal':
tmp_df = fx_pair(trade_df,ibkr_df,trade_opt,params[0],inv=params[1])
min_y = tmp_df.premium.min()
max_y = tmp_df.premium.max()
c = alt.Chart(tmp_df).mark_circle().encode(
x='time', y=alt.Y('premium', scale=alt.Scale(domain=[min_y, max_y])),
size='amount', color='side', tooltip=['time', 'premium', 'side','amount'])
#st.altair_chart(c.interactive(), use_container_width=True)
if params[1]:
ibkr_tmp = 1/ibkr_df[ibkr_df.currency_pair==params[0]][['price']].resample('60s').agg('last')
else:
ibkr_tmp = ibkr_df[ibkr_df.currency_pair==params[0]][['price']].resample('60s').agg('last')
ibkr_tmp['time'] = ibkr_tmp.index
min_ibkr = ibkr_tmp.price.min()
max_ibkr = ibkr_tmp.price.max()
line = alt.Chart(ibkr_tmp).mark_line(stroke='#c95785').encode(
alt.Y('price',
axis=alt.Axis(title='Price', titleColor='#c95785'),scale=alt.Scale(domain=[min_ibkr, max_ibkr]))
,alt.X('time'))
#st.altair_chart(line.interactive(),use_container_width=True)
op = alt.layer(c, line).resolve_scale(
y = 'independent'
)
st.altair_chart(op.interactive(),use_container_width=True)
elif params[2] == 'stable':
tmp_df = trade_df[trade_df.currency_pair==trade_opt]
min_y = tmp_df.price.min()
max_y = tmp_df.price.max()
c = alt.Chart(tmp_df).mark_circle().encode(
x='time', y=alt.Y('price', scale=alt.Scale(domain=[min_y, max_y])),
size='amount', color='side', tooltip=['time', 'price', 'side','amount'])
st.altair_chart(c.interactive(), use_container_width=True)
elif params[2] == 'cross':
composite = get_cross(trade_opt,ibkr_df)
tmp_df = fx_pair(trade_df,ibkr_df,trade_opt,'cross',composite)
min_y = tmp_df.premium.min()
max_y = tmp_df.premium.max()
c = alt.Chart(tmp_df).mark_circle().encode(
x='time', y=alt.Y('premium', scale=alt.Scale(domain=[min_y, max_y])),
size='amount', color='side', tooltip=['time', 'premium', 'side','amount'])
composite = composite.resample('60s').agg('last')
min_fp = composite.fp.min()
max_fp = composite.fp.max()
line = alt.Chart(composite).mark_line(stroke='#c95785').encode(
alt.Y('fp',
axis=alt.Axis(title='Price', titleColor='#c95785'),scale=alt.Scale(domain=[min_fp, max_fp]))
,alt.X('time'))
#st.altair_chart(line.interactive(),use_container_width=True)
op = alt.layer(c, line).resolve_scale(
y = 'independent'
)
st.altair_chart(op.interactive(), use_container_width=True)
if params[2] != 'stable':
st.markdown('**Price**')
trade_for_vis = trade_for_vis.loc[str(ibkr_df.index[0]):str(ibkr_df.index[-1])]
trade_min = trade_for_vis['price'].min()
trade_max = trade_for_vis['price'].max()
trade_sc = alt.Chart(trade_for_vis).mark_circle().encode(
x='time', y=alt.Y('price', scale=alt.Scale(domain=[trade_min, trade_max])),
size='amount', color='side', tooltip=['time', 'price', 'side','amount']
)
layered = alt.layer(trade_sc,line)
st.altair_chart(layered.interactive(),use_container_width=True)
#show_df = trade_df[trade_df.currency_pair==trade_opt]
# plost.scatter_chart(
# data=show_df,
# x='time',
# y=show_df[['buy','sell']]['price'],
# size='amount',
# )
st.title('Prediction Data')
resample_rate = st.slider('Set Resample Rate(In Minutes)', 1,30,1)
vol_data,fp_data,vol_keys,fp_keys,vol_time,fp_time = get_predict_data()
vol_opts = st.selectbox(
'Select Volatility Pair',
list(vol_keys),
)
vol_df = pd.DataFrame({vol_opts:vol_data[vol_opts]})
vol_df['time'] = pd.to_datetime(vol_time[vol_opts],utc=False) - datetime.timedelta(hours=8)
vol_df.index = vol_df.time
vol_df = vol_df.resample(f'{resample_rate*60}s').agg('last')
plost.line_chart(
vol_df,
x='time',
y=(vol_opts),
opacity=0.5
)
fp_opts = st.selectbox(
'Select FP Prediction',
list(fp_keys),
)
fp_df = pd.DataFrame({fp_opts:fp_data[fp_opts]})
fp_df['time'] = pd.to_datetime(fp_time[fp_opts],utc=False)- datetime.timedelta(hours=8)
fp_df.index = fp_df.time
fp_df = fp_df.resample(f'{resample_rate*60}s').agg('last')
plost.line_chart(
fp_df,
x='time',
y=(fp_opts),
opacity=0.5
)
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