Not completely sure why it doesn't open the chart on the web browser when i
type this in the windows command prompt (cmd) python -m SimpleHTTPServer port
80.So first i type python ml.py data/sample.csv in cmd windows and then python
-m SimpleHTTPServer port 80, but it's not proceeding to the graph in html??
See attached image for screenshoot and complete .py file
"""
Find the support/resistance lines in a chart
JonV / May 16 2015
"""
import sys
import pandas
import numpy as np
import json
from sklearn.cluster import MeanShift, estimate_bandwidth
def main(filename):
# read csv files with daily data per tick
df = pandas.read_csv('sample.csv', parse_dates=[0], index_col=0,
names=['Date_Time', 'Buy', 'Sell'],
date_parser=lambda x: pandas.to_datetime(x,
format="%d/%m/%y %H:%M:%S"))
# group by day and drop NA values (usually weekends)
grouped_data = df.dropna()
ticks_data = grouped_data['Sell'].resample('24H').ohlc()
# use 'ask'
sell_data = grouped_data.as_matrix(columns=['Sell'])
# calculate bandwidth (expirement with quantile and samples)
bandwidth = estimate_bandwidth(sell_data, quantile=0.1, n_samples=100)
ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)
# fit the data
ms.fit(sell_data)
ml_results = []
for k in range(len(np.unique(ms.labels_))):
my_members = ms.labels_ == k
values = sell_data[my_members, 0]
# find the edges
ml_results.append(min(values))
ml_results.append(max(values))
# export the data for the visualizations
ticks_data.to_json('ticks.json', date_format='iso', orient='index')
# export ml support resisistance
with open('ml_results.json', 'w') as f:
f.write(json.dumps(ml_results))
print "Done. Goto 0.0.0.0:8000/chart.html"
if __name__ == "__main__":
if (len(sys.argv) < 2):
print 'ml.py <inputfile.csv>'
sys.exit(2)
main(sys.argv[1])
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