import sys
sys.path.append('C:\\MyPythonPackages\\dynamic_stock_model-master\\dynamic_stock_model\\') 

from dynamic_stock_model import DynamicStockModel

import numpy as np
TestDSM = DynamicStockModel(t = np.arange(1,11,1), i = np.arange(2.5,12.5,1), lt = {'Type': 'Normal', 'Mean': np.array([5]), 'StdDev': np.array([1.5]) })

TestDSM.t

TestDSM.i

TestDSM.lt

CheckStr, ExitFlag = TestDSM.dimension_check()
print(CheckStr)

Stock_by_cohort, ExitFlag = TestDSM.compute_s_c_inflow_driven()
print(Stock_by_cohort)

S, ExitFlag   = TestDSM.compute_stock_total()
print(S)

O_C, ExitFlag = TestDSM.compute_o_c_from_s_c()
print(O_C)

O, ExitFlag   = TestDSM.compute_outflow_total()
print(O)

DS, ExitFlag  = TestDSM.compute_stock_change()
print(DS)

print(TestDSM.dimension_check()[0]) # dimension_check returns two variables, but we only print the first one, which has index 0.

Bal, ExitFlag = TestDSM.check_stock_balance()
print(Bal)

%matplotlib inline
# this is only for the IPython notebook, not part of the python script!

import matplotlib.pyplot as plt
plt.imshow(TestDSM.s_c, interpolation='nearest')
plt.xlabel('age-cohort')
plt.ylabel('year')
plt.title('Stock by age-cohort')
plt.show();

plt.imshow(TestDSM.o_c,interpolation='nearest')
plt.xlabel('age-cohort')
plt.ylabel('year')
plt.title('Outflow by age-cohort')
plt.show();

TestDSMX = DynamicStockModel(t = np.arange(1,11,1), s = np.array([  2.5,   6. ,  10.5,  16. ,  22.5,  27.5,  32.5,  37.5,  42.5,  47.5]), lt = {'Type': 'Normal', 'Mean': np.array([4]), 'StdDev': np.array([1.0]) })
CheckStr, ExitFlag = TestDSMX.dimension_check()
print(CheckStr)

S_C, O_C, I, ExitFlag = TestDSMX.compute_stock_driven_model()
O, ExitFlag   = TestDSMX.compute_outflow_total()
DS, ExitFlag  = TestDSMX.compute_stock_change()
Bal, ExitFlag = TestDSMX.check_stock_balance()
print(Bal)

plt1, = plt.plot(TestDSMX.t, TestDSMX.i)
plt2, = plt.plot(TestDSMX.t, TestDSMX.s)
plt3, = plt.plot(TestDSMX.t, TestDSMX.o)
plt.xlabel('Year')
plt.ylabel('tons')
plt.title('Stock parameters')
plt.legend([plt1,plt2,plt3], ['Inflow','Stock','Outflow'], loc = 2)
plt.show();

plt.imshow(TestDSMX.s_c,interpolation='nearest')
plt.xlabel('age-cohort')
plt.ylabel('year')
plt.title('Stock by age-cohort')
plt.show();

plt.imshow(TestDSMX.o_c,interpolation='nearest')
plt.xlabel('age-cohort')
plt.ylabel('year')
plt.title('Outflow by age-cohort')
plt.show();