51 lines
1.2 KiB
Python
51 lines
1.2 KiB
Python
import matplotlib.pyplot as plt
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import matplotlib.dates as md
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import datetime as dt
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import time
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import random
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from common import *
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from db_handle import *
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from http_handle import *
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if __name__ == '__main__':
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C = get_db_connection()
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cur = C.cursor()
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## Fetch data
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days = 0
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delta = 30
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ts_high = time.mktime(time.localtime()) * 1000 - days*24*60*60*1000
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ts_low = ts_high - delta*60*60*24*1000
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coins = ['subaru']
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userids = ['c9b0830c-8cf7-4e1d-b8f3-60bbc85160fa', '990400b5-f0e2-4b91-8aa6-5a74dc16bcc5']
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hist = fetch_history(cur, ts_low, ts_high, coins, userids)
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# Analyse data
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T0, T1, Y0, Y1 = [], [], [], []
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for tr in hist:
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if tr['userid'][:5] == userids[0][:5]:
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Y0.append(tr["quantity"])
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T0.append(tr["timestamp"]// 1000)
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else:
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Y1.append(tr["quantity"])
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T1.append(tr["timestamp"]// 1000)
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dates0 = [dt.datetime.fromtimestamp(ts) for ts in T0]
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X0 = md.date2num(dates0)
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dates1 = [dt.datetime.fromtimestamp(ts) for ts in T1]
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X1 = md.date2num(dates1)
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ax=plt.gca()
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xfmt = md.DateFormatter('%H:%M:%S')
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ax.xaxis.set_major_formatter(xfmt)
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# Plot data
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plt.plot(X1, Y1, "r+")
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plt.plot(X0, Y0, "b+")
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plt.show()
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