def main():
start_time = time.time()
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(
file_path="data.csv",
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
sim = simulate.run_monte_carlo(orders_analysis=orders_analysis.orders,
runs=1,
period_length=12)
sim_window = simulate.summarize_window(simulation_frame=sim,
period_length=12)
sim_frame = simulate.summarise_frame(sim_window)
optimised = simulate.optimise_service_level(
service_level=95.0,
frame_summary=sim_frame,
orders_analysis=orders_analysis.orders,
runs=1,
percentage_increase=1.30)
for s in optimised:
print(s.orders_summary())
end_time = time.time()
elapsed = end_time - start_time
print(elapsed)
def setUp(self):
self.__skus = ['KR202-209', 'KR202-210', 'KR202-211']
self.__orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(
file_path=ABS_FILE_PATH['COMPLETE_CSV_SM'],
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv",
length=12)
self.__categories = ['excess_stock', 'shortages', 'revenue']
self.__abc_classification = ('AX', 'AY', 'AZ', 'BX', 'BY', 'BZ', 'CX',
'CY', 'CZ')
self.__analysis_summary = Inventory(
processed_orders=self.__orders_analysis)
self.__describe_sku = [
'excess_cost', 'percentage_contribution_revenue',
'markup_percentage', 'shortage_rank', 'unit_cost', 'max_order',
'retail_price', 'classification', 'excess_rank', 'average_orders',
'revenue_rank', 'excess_units', 'safety_stock_units',
'shortage_cost', 'revenue', 'min_order', 'safety_stock_rank',
'safety_stock_cost', 'sku_id', 'gross_profit_margin',
'shortage_units'
]
self.__abc_raw = self.__analysis_summary.abc_xyz_raw
def test_file_path_abcxyz_extension(self):
with self.assertRaises(expected_exception=Exception):
abc = model_inventory.analyse_orders_abcxyz_from_file(
file_path='test.ts',
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
def test_normal_distribution_mean(self):
""" Verifies mean and variance for random normal distribution.
"""
# arrange
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
# act
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(
file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
sim = monte_carlo.SetupMonteCarlo(
analysed_orders=orders_analysis.orders, period_length=1)
for sku in orders_analysis.orders:
item = sku.orders_summary()
if item['sku'] == 'KR202-209':
# assertd
diff = abs(
float(item['average_order']) - float(
np.mean(sim.normal_random_distribution[0]['KR202-209']
[0][0])))
self.assertLess(diff, float(item['standard_deviation']))
def main():
start_time = time.time()
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(
file_path="data.csv", z_value=Decimal(1.28), reorder_cost=Decimal(5000), file_type="csv"
)
sim = simulate.run_monte_carlo(orders_analysis=orders_analysis.orders, runs=1, period_length=12)
sim_window = simulate.summarize_window(simulation_frame=sim, period_length=12)
sim_frame = simulate.summarise_frame(sim_window)
optimised = simulate.optimise_service_level(
service_level=95.0,
frame_summary=sim_frame,
orders_analysis=orders_analysis.orders,
runs=1,
percentage_increase=1.30,
)
for s in optimised:
print(s.orders_summary())
end_time = time.time()
elapsed = end_time - start_time
print(elapsed)
def setUp(self):
self.__skus = ['KR202-209', 'KR202-210', 'KR202-211']
self.__orders_analysis = analyse_orders_abcxyz_from_file(file_path=ABS_FILE_PATH['COMPLETE_CSV_SM'],
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv",
length=12)
def setUp(self):
self.__skus = ['KR202-209', 'KR202-210', 'KR202-211']
self.__orders_analysis = analyse_orders_abcxyz_from_file(file_path=ABS_FILE_PATH['COMPLETE_CSV_SM'],
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv",
length=12)
self.sim = simulate.run_monte_carlo(orders_analysis=self.__orders_analysis, runs=1, period_length=12)
def test_file_path_abcxyz_extension(self):
# arrange, act
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.sv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
# assert
with self.assertRaises(expected_exception=Exception):
abc = model_inventory.analyse_orders_abcxyz_from_file(file_path=abs_file_path, z_value=Decimal(1.28),
reorder_cost=Decimal(5000), file_type="csv")
def test_abcxyz_classification(self):
abc = model_inventory.analyse_orders_abcxyz_from_file(file_path=ABS_FILE_PATH['COMPLETE_CSV_SM'],
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
for sku in abc:
item = sku.orders_summary()
if item['sku'] == 'KR202-209':
self.assertEqual(item['ABC_XYZ_Classification'], 'BY')
def test_file_path_abcxyz(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
abc = model_inventory.analyse_orders_abcxyz_from_file(file_path=abs_file_path, z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
for sku in abc.orders:
item = sku.orders_summary()
if item['sku'] == 'KR202-209':
self.assertEqual(item['ABC_XYZ_Classification'], 'CZ')
def setUp(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data2.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
self.__skus = ['KR202-209', 'KR202-210', 'KR202-211']
self.__orders_analysis = analyse_orders_abcxyz_from_file(file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv",
length=12)
def setUp(self):
self.__skus = ["KR202-209", "KR202-210", "KR202-211"]
self.__orders_analysis = analyse_orders_abcxyz_from_file(
file_path=ABS_FILE_PATH["COMPLETE_CSV_SM"],
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv",
length=12,
)
self.__sim = monte_carlo.SetupMonteCarlo(analysed_orders=self.__orders_analysis, period_length=1)
def test_run_simulation(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data2.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
simulation_windows = simulate.run_monte_carlo(orders_analysis=orders_analysis, runs=1)
self.assertEqual(len(simulation_windows), 384)
def test_po_quantity_zero(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = analyse_orders_abcxyz_from_file(file_path=abs_file_path, z_value=Decimal(1.28),
reorder_cost=Decimal(5000), file_type="csv")
sim = simulate.run_monte_carlo(orders_analysis=orders_analysis.orders, runs=1, period_length=12)
for period in sim:
if int(period[0].get("closing_stock")) == 0:
self.assertGreater(int(period[0].get("po_quantity")), 0)
def test_summarize_simulation(self):
orders_analysis = analyse_orders_abcxyz_from_file(
file_path=ABS_FILE_PATH["COMPLETE_CSV_SM"],
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv",
)
simulation_windows = simulate.run_monte_carlo(orders_analysis=orders_analysis, runs=1, period_length=12)
collect_sim = []
for i in simulate.summarize_window(simulation_frame=simulation_windows):
collect_sim.append(i)
self.assertEqual(len(collect_sim), 39)
def test_summarize_simulation(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data2.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = analyse_orders_abcxyz_from_file(file_path=abs_file_path, z_value=Decimal(1.28),
reorder_cost=Decimal(5000), file_type="csv")
simulation_windows = simulate.run_monte_carlo(orders_analysis=orders_analysis, runs=1, period_length=12)
collect_sim = []
for i in simulate.summarize_window(simulation_frame=simulation_windows):
collect_sim.append(i)
self.assertEqual(len(collect_sim), 32)
def test_po_raised_regex(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
po_regex = re.compile('[P][O] \d+')
orders_analysis = analyse_orders_abcxyz_from_file(file_path=abs_file_path, z_value=Decimal(1.28),
reorder_cost=Decimal(5000), file_type="csv")
sim = simulate.run_monte_carlo(orders_analysis=orders_analysis.orders, runs=1, period_length=12)
for period in sim:
if int(period[0].get("closing_stock")) == 0 and int(period[0].get("backlog")) > 0:
self.assertRegex(period[0].get("po_raised"), expected_regex=po_regex, msg='True')
def test_run_simulation(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(
file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
simulation_windows = simulate.run_monte_carlo(
orders_analysis=orders_analysis.orders, runs=1)
self.assertEqual(len(simulation_windows), 384)
def test_po_quantity_zero(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = analyse_orders_abcxyz_from_file(
file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
sim = simulate.run_monte_carlo(orders_analysis=orders_analysis.orders,
runs=1,
period_length=12)
for period in sim:
if int(period[0].get("closing_stock")) == 0:
self.assertGreater(int(period[0].get("po_quantity")), 0)
def test_summarize_simulation(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = analyse_orders_abcxyz_from_file(
file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
simulation_windows = simulate.run_monte_carlo(
orders_analysis=orders_analysis.orders, runs=1, period_length=12)
collect_sim = []
for i in simulate.summarize_window(
simulation_frame=simulation_windows):
collect_sim.append(i)
self.assertEqual(len(collect_sim), 32)
def setUp(self):
self.__skus = ['KR202-209', 'KR202-210', 'KR202-211']
self.__orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(file_path=ABS_FILE_PATH['COMPLETE_CSV_SM'],
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv",
length=12)
self.__categories = ['excess_stock', 'shortages', 'revenue']
self.__abc_classification = ('AX', 'AY', 'AZ', 'BX', 'BY', 'BZ', 'CX', 'CY', 'CZ')
self.__analysis_summary = Inventory( processed_orders =self.__orders_analysis)
self.__describe_sku = ['excess_cost', 'percentage_contribution_revenue', 'markup_percentage',
'shortage_rank', 'unit_cost', 'max_order', 'retail_price', 'classification',
'excess_rank', 'average_orders', 'revenue_rank', 'excess_units', 'safety_stock_units',
'shortage_cost', 'revenue', 'min_order', 'safety_stock_rank', 'safety_stock_cost',
'sku_id', 'gross_profit_margin', 'shortage_units']
self.__abc_raw = self.__analysis_summary.abc_xyz_raw
def test_build_window(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(
file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
period_length = 12
sim_collection = []
for k in range(0, 1):
simulation = monte_carlo.SetupMonteCarlo(
analysed_orders=orders_analysis.orders)
random_demand = simulation.generate_normal_random_distribution(
period_length=period_length)
for sim_window in simulation.build_window(
random_normal_demand=random_demand,
period_length=period_length):
sim_dict = {
"index":
"{:.0f}".format(sim_window.index),
"period":
"{:.0f}".format(sim_window.position),
"sku_id":
sim_window.sku_id,
"opening_stock":
"{:.0f}".format(sim_window.opening_stock),
"demand":
"{:.0f}".format(sim_window.demand),
"closing_stock":
"{:.0f}".format(sim_window.closing_stock),
"delivery":
"{:.0f}".format(sim_window.purchase_order_receipt_qty),
"backlog":
"{:.0f}".format(sim_window.backlog)
}
sim_collection.append([sim_dict])
self.assertEqual(len(sim_collection), 1)
def test_normal_distribution_mean(self):
""" Verifies mean and variance for random normal distribution.
"""
# arrange
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
# act
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
sim = monte_carlo.SetupMonteCarlo(analysed_orders=orders_analysis.orders, period_length=1)
for sku in orders_analysis.orders:
item = sku.orders_summary()
if item['sku'] == 'KR202-209':
# assertd
diff = abs(
float(item['average_order']) - float(np.mean(sim.normal_random_distribution[0]['KR202-209'][0][0])))
self.assertLess(diff, float(item['standard_deviation']))
def test_po_raised_regex(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
po_regex = re.compile('[P][O] \d+')
orders_analysis = analyse_orders_abcxyz_from_file(
file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
sim = simulate.run_monte_carlo(orders_analysis=orders_analysis.orders,
runs=1,
period_length=12)
for period in sim:
if int(period[0].get("closing_stock")) == 0 and int(
period[0].get("backlog")) > 0:
self.assertRegex(period[0].get("po_raised"),
expected_regex=po_regex,
msg='True')
def test_build_window(self):
app_dir = os.path.dirname(__file__, )
rel_path = 'supplychainpy/data2.csv'
abs_file_path = os.path.abspath(os.path.join(app_dir, '..', rel_path))
orders_analysis = model_inventory.analyse_orders_abcxyz_from_file(file_path=abs_file_path,
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
period_length = 12
sim_collection = []
for k in range(0, 1):
simulation = monte_carlo.SetupMonteCarlo(analysed_orders=orders_analysis)
random_demand = simulation.generate_normal_random_distribution(period_length=period_length)
for sim_window in simulation.build_window(random_normal_demand=random_demand, period_length=period_length):
sim_dict = {"index": "{:.0f}".format(sim_window.index), "period": "{:.0f}".format(sim_window.position),
"sku_id": sim_window.sku_id, "opening_stock": "{:.0f}".format(sim_window.opening_stock),
"demand": "{:.0f}".format(sim_window.demand),
"closing_stock": "{:.0f}".format(sim_window.closing_stock),
"delivery": "{:.0f}".format(sim_window.purchase_order_receipt_qty),
"backlog": "{:.0f}".format(sim_window.backlog)}
sim_collection.append([sim_dict])
self.assertEqual(len(sim_collection), 1)
def test_file_path_abcxyz_extension(self):
with self.assertRaises(expected_exception=Exception):
abc = model_inventory.analyse_orders_abcxyz_from_file(file_path='test.ts',
z_value=Decimal(1.28),
reorder_cost=Decimal(5000),
file_type="csv")
