sam-thecoder

import pandas as pd
import os

train = pd.read_csv('train.csv')
landmarks = list(set(train['landmark_id'].tolist())) #use set to have only unique id's and turn it back to a list type again

#creates sub folders of landmark id in train and validation folder
train_folder = 'training_images'
validation_folder = 'validation_images'

sam-thecoder

from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense
from keras import backend as K
from keras.callbacks import EarlyStopping
from keras.callbacks import ModelCheckpoint


# dimensions of our images.

sam-thecoder

$ node
> const models = require('./../models');
sequelize deprecated String based operators are now deprecated. Please use Symbo
l based operators for better security, read more at http://docs.sequelizejs.com/
manual/tutorial/querying.html#operators node_modules\sequelize\lib\sequelize.js:
242:13
undefined
> Executing (default): CREATE TABLE IF NOT EXISTS `users` (`id` INTEGER PRIMARY
KEY AUTOINCREMENT, `username` VARCHAR(255), `loggedIn` TINYINT(1), `createdAt` D
ATETIME NOT NULL, `updatedAt` DATETIME NOT NULL);

sam-thecoder

$ node
> const models = require('../models');
sequelize deprecated String based operators are now deprecated. Please use Symbo
l based operators for better security, read more at http://docs.sequelizejs.com/
manual/tutorial/querying.html#operators node_modules\sequelize\lib\sequelize.js:
242:13
undefined
> Executing (default): CREATE TABLE IF NOT EXISTS `users` (`id` INTEGER PRIMARY
KEY AUTOINCREMENT, `username` VARCHAR(255), `loggedIn` TINYINT(1), `createdAt` D
ATETIME NOT NULL, `updatedAt` DATETIME NOT NULL);

sam-thecoder

def decider(row):
    if row['Drop 7'] < row['Up 7'] and row['Mean Change 7'] > 0 and row['Change'] > 0:
        return 0 #invest/hold or put in 100 investment if none
    #Withdraw 50%
    elif row['Drop 7'] < row['Up 7'] and row['Mean Change 7'] > 0 and row['Change'] < 0:
        return -50
    #Withdraw 75%
    elif row['Drop 7'] < row['Up 7'] and row['Mean Change 7'] < 0 or row['Change'] < 0:
        return -75
    #invest 50% more

sam-thecoder

def count_drop(numbers):
    return len([x for x in numbers if x < 0])

def count_up(numbers):
    return len([x for x in numbers if x > 0])
  
df['Change'] = df['Value USD'] - df['Value 2']
df.drop('Value 2', axis=1, inplace=True)
#Change for the past 7 days
df['Mean Change 7'] = df['Change'].rolling(7).mean()

sam-thecoder

main_key = 0
game_record = {}

##Add Reward Cycle last

def bitcoin_game(user_key=None, amount=1000, start_index=0, invest_amount=None, withdraw_amount=None):
    global main_key, game_record
    #print(user_key)
    if user_key == None:
        player_name = 'player_{0}'.format(main_key)

sam-thecoder

def player_1(start_index=0, miss_output=False, miss_plot=False, sleep=False, sleep_time=1, plot=False, output=True, hold_max=1000, withdraw_max=500, withdraw_min=10):
    user_key, day_info, amount, invested, profit, loss, game_active = bitcoin_game(start_index=start_index)
    prev_predict = day_info[-1]
    miss_colors = ['g']
    while game_active == False:
        #print(day_info[-1])
        if day_info[-1] == 0: #equilavent of 100 i.e. good odds
            #print('first option')
            if invested < 100: #invest 100
                user_key, day_info, amount, invested, profit, loss, game_active = bitcoin_game(user_key=user_key, invest_amount=withdraw_max/5)

sam-thecoder

def lazy_investor(start_index=0, output=False, plot=True, amount=1000):
    user_key, day_info, amount, invested, profit, loss, game_active = bitcoin_game(start_index=start_index)
    while game_active == False:
        if amount > 100:
            user_key, day_info, amount, invested, profit, loss, game_active = bitcoin_game(user_key=user_key, invest_amount=amount-100)
            #print(bitcoin_game(user_key=user_key, invest_amount=amount-100))
        else:
            try:
                user_key, day_info, amount, invested, profit, loss, game_active = bitcoin_game(user_key=user_key)
            except Exception as e:

sam-thecoder

def player_2(start_index=0, sleep=False, sleep_time=1, plot=False, output=True, miss_output=False, miss_plot=False, show_exception=True):
    user_key, day_info, amount, invested, profit, loss, game_active = bitcoin_game(start_index=start_index)

    peak_price = day_info[1]
    min_price = day_info[4]
    max_price = day_info[5]
    mean_price = day_info[6]
    invest = None
    max_profit = invested