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Print statements and other errors solved #29

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Print statements and other errors solved
AliHaider20 Nov 12, 2023
9b8042d
Updated
AliHaider20 Nov 12, 2023
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Binary file added __pycache__/functions.cpython-310.pyc
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Binary file added agent/__pycache__/__init__.cpython-310.pyc
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Binary file added agent/__pycache__/agent.cpython-310.pyc
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2 changes: 1 addition & 1 deletion agent/agent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ def act(self, state):
def expReplay(self, batch_size):
mini_batch = []
l = len(self.memory)
for i in xrange(l - batch_size + 1, l):
for i in range(l - batch_size + 1, l):
mini_batch.append(self.memory[i])

for state, action, reward, next_state, done in mini_batch:
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14 changes: 7 additions & 7 deletions evaluate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
import sys

if len(sys.argv) != 3:
print "Usage: python evaluate.py [stock] [model]"
print ("Usage: python evaluate.py [stock] [model]")
exit()

stock_name, model_name = sys.argv[1], sys.argv[2]
Expand All @@ -22,7 +22,7 @@
total_profit = 0
agent.inventory = []

for t in xrange(l):
for t in range(l):
action = agent.act(state)

# sit
Expand All @@ -31,19 +31,19 @@

if action == 1: # buy
agent.inventory.append(data[t])
print "Buy: " + formatPrice(data[t])
print ("Buy: " + formatPrice(data[t]))

elif action == 2 and len(agent.inventory) > 0: # sell
bought_price = agent.inventory.pop(0)
reward = max(data[t] - bought_price, 0)
total_profit += data[t] - bought_price
print "Sell: " + formatPrice(data[t]) + " | Profit: " + formatPrice(data[t] - bought_price)
print ("Sell: " + formatPrice(data[t]) + " | Profit: " + formatPrice(data[t] - bought_price))

done = True if t == l - 1 else False
agent.memory.append((state, action, reward, next_state, done))
state = next_state

if done:
print "--------------------------------"
print stock_name + " Total Profit: " + formatPrice(total_profit)
print "--------------------------------"
print ("--------------------------------")
print (stock_name + " Total Profit: " + formatPrice(total_profit))
print ("--------------------------------")
2 changes: 1 addition & 1 deletion functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@ def getState(data, t, n):
d = t - n + 1
block = data[d:t + 1] if d >= 0 else -d * [data[0]] + data[0:t + 1] # pad with t0
res = []
for i in xrange(n - 1):
for i in range(n - 1):
res.append(sigmoid(block[i + 1] - block[i]))

return np.array([res])
20 changes: 10 additions & 10 deletions train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,24 +3,24 @@
import sys

if len(sys.argv) != 4:
print "Usage: python train.py [stock] [window] [episodes]"
print ("Usage: python train.py [stock] [window] [episodes]")
exit()

stock_name, window_size, episode_count = sys.argv[1], int(sys.argv[2]), int(sys.argv[3])

agent = Agent(window_size)
data = getStockDataVec(stock_name)
data = cha(stock_name)
l = len(data) - 1
batch_size = 32

for e in xrange(episode_count + 1):
print "Episode " + str(e) + "/" + str(episode_count)
for e in range(episode_count + 1):
print ("Episode " + str(e) + "/" + str(episode_count))
state = getState(data, 0, window_size + 1)

total_profit = 0
agent.inventory = []

for t in xrange(l):
for t in range(l):
action = agent.act(state)

# sit
Expand All @@ -29,22 +29,22 @@

if action == 1: # buy
agent.inventory.append(data[t])
print "Buy: " + formatPrice(data[t])
print ("Buy: " + formatPrice(data[t]))

elif action == 2 and len(agent.inventory) > 0: # sell
bought_price = agent.inventory.pop(0)
reward = max(data[t] - bought_price, 0)
total_profit += data[t] - bought_price
print "Sell: " + formatPrice(data[t]) + " | Profit: " + formatPrice(data[t] - bought_price)
print ("Sell: " + formatPrice(data[t]) + " | Profit: " + formatPrice(data[t] - bought_price))

done = True if t == l - 1 else False
agent.memory.append((state, action, reward, next_state, done))
state = next_state

if done:
print "--------------------------------"
print "Total Profit: " + formatPrice(total_profit)
print "--------------------------------"
print ("--------------------------------")
print ("Total Profit: " + formatPrice(total_profit))
print ("--------------------------------")

if len(agent.memory) > batch_size:
agent.expReplay(batch_size)
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