Merge lp:~openbig/bigconsulting/solved_stock_minimum_calculator into lp:bigconsulting

[gpa(OpenERP)]

Improvement in stock_minimum_calculator module

[lp:~openbig/bigconsulting/solved_stock_minimum_calculator]

48. By gpa(OpenERP) on 2010-07-07

solved problem in stock minimum calculator

=== modified file 'stock_minimum_calculator/wizard/stock_order_point_calculator.py'
--- stock_minimum_calculator/wizard/stock_order_point_calculator.py	2010-06-24 08:01:22 +0000
+++ stock_minimum_calculator/wizard/stock_order_point_calculator.py	2010-07-07 06:36:41 +0000
@@ -66,7 +66,8 @@
                     'string': 'Season of Consumption', 
                     'type': 'many2one', 
                     'relation': 'product.seasonal', 
-                    'required': True
+                    'required': True,
+                    'help':'Use this field as index. Reference index is Main Season with 1.00. If you want to change the orderpoint rules you are able to define new season with a seasonal index. This index should reference to 1.00. For example if you expect - 10% consumption for autumn season in comparition to main season enter 0.90.'
                     },
                         
             'date_start': {
@@ -104,16 +105,18 @@
     pool = pooler.get_pool(cr.dbname)
 
     warehouse_id = pool.get('stock.warehouse').search(cr, uid, [])[0]
-    location_id = pool.get('stock.location').search(cr, uid, [('name','=','Stock')])[0]
+    seasonal_id = pool.get('product.seasonal').search(cr, uid, [])[0]
 
+    w = pool.get('stock.warehouse').browse(cr,uid,warehouse_id, context)
+    location_id = w.lot_stock_id.id
+    
     from_date = now().strftime('%Y-%m-%d')
     from_date = mx.DateTime.strptime(from_date, '%Y-%m-%d') - RelativeDateTime(months=3)
     from_date = from_date.strftime('%Y-%m-%d')
 
-    return {'warehouse_id': warehouse_id, 'location_id':location_id,'date_start':from_date}
+    return {'warehouse_id': warehouse_id, 'location_id':location_id,'date_start':from_date,'seasonal_id':seasonal_id}
 
 def _do_calculate(self, cr, uid, data, context):
-
         pool = pooler.get_pool(cr.dbname)
 
         purchase_obj = pool.get('purchase.order')
@@ -122,12 +125,17 @@
         supp_obj = pool.get('product.supplierinfo')
         supp_cost_opt_obj = pool.get('supplier.cost.opti.lead.time')
         min_rule_obj = pool.get('stock.warehouse.orderpoint')
-
+        seasonal_obj = pool.get('product.seasonal')
         ##### Calculation of purchase lead time 
         purchase_lead_time = 0.0
         company = pool.get('res.users').browse(cr, uid, uid, context).company_id
         purchase_lead_time = company.po_lead
         
+        ##### get seasonal factor
+        seasonal_id = data['form']['seasonal_id']
+        seasonal_data = seasonal_obj.browse(cr, uid, seasonal_id)
+        seasonal_factor = seasonal_data.seasonal_factor
+        
         ##### Calculation of supplier lead time
 
         for id in data['ids']:
@@ -152,9 +160,8 @@
                         sale_line_data= sale_line_obj.browse(cr,uid,line_id)
                         consum_qty += sale_line_data.product_uom_qty
                        ###here cosume quantity is total of selected produdct
-                        
             ##################calculation of date difference between first and last sale order
-            sale_ids = sale_obj.search(cr,uid,[])
+            sale_ids = sale_obj.search(cr,uid,[('date_order','>=',date_start),('date_order','<=',date_stop)])
             if sale_ids:
                 start_sale_id = min(sale_ids)
                 last_sale_id =  max(sale_ids)
@@ -165,11 +172,14 @@
                 diff_day = (last_date-first_date)/(3600*24)
                 if diff_day > 0:
                     average_daily_consumption = consum_qty / diff_day
-            
             ###### Calculation of plan_average_daily_consumption
             plan_average_daily_consumption = 0.0
             if product_id.plan_avg_consume:
                 plan_average_daily_consumption = product_id.plan_avg_consume
+            
+            ####### get location #####
+            location_id = data['form']['location_id']
+            
             ########## calculation historical consumption of products and open sales orders“
             ### total sale qty with open state
             
@@ -193,22 +203,20 @@
                 first_date = time.mktime(time.strptime(first_purchase_date,'%Y-%m-%d'))
                 last_date = time.mktime(time.strptime(last_purchase_date,'%Y-%m-%d'))
                 pur_diff_day = (last_date-first_date)/(3600*24)
-                        
             product_max_qty = 0.0 
             product_min_qty = 0.0
             
-            
             if data['form']['method_qty_calculation'] == 'his_cons_with_product':
-                product_min_qty = int(math.ceil(average_daily_consumption *  (supplier_lead_time + purchase_lead_time)))
+                product_min_qty = int(math.ceil(average_daily_consumption *  (supplier_lead_time + purchase_lead_time) * seasonal_factor))
                 product_max_qty = 2 * product_min_qty
             
             elif data['form']['method_qty_calculation'] == 'his_cons_without_product':
-                product_min_qty =  int(math.ceil(plan_average_daily_consumption * (supplier_lead_time + purchase_lead_time)))
+                product_min_qty =  int(math.ceil(plan_average_daily_consumption * (supplier_lead_time + purchase_lead_time) * seasonal_factor))
                 product_max_qty = 2 * product_min_qty
             
             else:
                 try:
-                    product_min_qty =  int(math.ceil((consum_qty + sale_qty) / pur_diff_day * (supplier_lead_time + purchase_lead_time)))
+                    product_min_qty =  int(math.ceil((consum_qty + sale_qty) / pur_diff_day * (supplier_lead_time + purchase_lead_time) * seasonal_factor))
                 except Exception,e:
                      product_min_qty = 0.0
                 product_max_qty = 2 * product_min_qty
@@ -228,7 +236,7 @@
                                 'name': name,
                                 'active': True,
                                 'warehouse_id': data['form']['warehouse_id'],
-                                'location_id': product_id.property_stock_inventory.id,
+                                'location_id': location_id,
                                 'product_id': id,
                                 'product_min_qty': product_min_qty,
                                 'product_max_qty': product_max_qty,