qharlie

# coding: utf-8

# In[ ]:





# In[1]:

qharlie

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%matplotlib inline

qharlie

ValueError                                Traceback (most recent call last)
<ipython-input-7-5cf5b03019f2> in <module>()
     24 model.compile(loss='mean_squared_error', optimizer=optimizer)
     25 
---> 26 model.fit(X_train, y_train, epochs=100, verbose=2)

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/keras/models.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)
    868                               class_weight=class_weight,
    869                               sample_weight=sample_weight,
--> 870                               initial_epoch=initial_epoch)

qharlie

1 4 7 |3 6 5 |8 9 2 
6 9 5 |8 2 7 |4 1 3 
2 3 8 |9 1 4 |6 5 7 
------+------+------
9 5 1 |2 8 3 |7 4 6 
8 6 4 |1 7 9 |3 2 5 
3 7 2 |4 5 6 |9 8 1 
------+------+------
4 1 9 |6 3 2 |5 7 8 
7 8 6 |5 4 1 |2 3 9 

qharlie

from bs4 import BeautifulSoup
from urllib2 import urlopen
from datetime import datetime, timedelta
from time import sleep
import sys
import csv
 
# CONSTANTS
ESPN_URL = "http://scores.espn.go.com"
 

qharlie

(JFK, SFO, ATL, ORD) = symbols('JFK,SFO,ATL,ORD')
(C1, C2, C3, C4) = symbols('C1,C2,C3,C4')
(At, In) = symbols('At,In')
# (Load, Unload, Fly) = symbols('Load,Unload,Fly,At,In')
(P1, P2, P3) = symbols('P1,P2,P3')

qharlie

def air_cargo_p1() -> AirCargoProblem:
    cargos = [C1, C2]
    planes = [P1, P2]
    airports = [JFK, SFO]
    pos = [At(C1, SFO),
           At(C2, JFK),
           At(P1, SFO),
           At(P2, JFK),
           ]
    neg = [At(C2, SFO),

qharlie

object Solution {

  def buyTicket(seq: Array[Int]): Array[Int] = {    
    seq.drop(1) ++ seq.take(1).map(_ - 1 )
  }

  def waitingTime(ts : Array[Int], p : Int ) : Int = {
    var tickets = ts; var time_in_line = 0; var position = p

qharlie

l = [[1,2],[3,4]]
[x for y in l for x in y ]

qharlie

import backtrader as bt
import util.data as btu
import os



def run_stock_scanner(tickers, _from, _to, analyzers):
    cerebro = bt.Cerebro()
    for ticker in tickers:
        DataFactory = btu.get_store().getdata