Merge pull request #2 from foarsitter/development

Development

.gitignore

@@ -2,3 +2,7 @@ data/
 .idea/
 model-settings.xml
 *.pyc
+model/__pycache__/
+model/helpers/__pycache__/
+model/observers/__pycache__/
+sample_data/

.travis.yml

@@ -3,7 +3,7 @@ python:
   - "3.5"
 # command to run tests
 install:
-  - pip install codecov coverage codeclimate-test-reporter
+  - pip install codecov coverage codeclimate-test-reporter scipy
 script: nosetests --with-coverage --cover-erase
 after_success:
   - coverage

decide-gui.py

@@ -8,13 +8,14 @@
 from tkinter import messagebox
 from tkinter import ttk
 
+import decimal
+
 from model.base import AbstractModel
-from model.helpers import csvParser
+from model.helpers import csvparser
 from model.helpers.helpers import ModelLoop
 from model.observers.exchanges_writer import ExchangesWriter
 from model.observers.externalities import Externalities
 from model.observers.issue_development import IssueDevelopment
-from model.observers.logger import Logger
 from model.observers.observer import Observable, Observer
 
 
@@ -201,6 +202,9 @@ def __init__(self, parent, *args, **kwargs):
         self.salience_weight = tk.DoubleVar()
         self.salience_weight.set(0.4)
 
+        self.randomized_value = tk.DoubleVar()
+        self.randomized_value.set(0.1)
+
         self.fixed_weight = tk.DoubleVar()
         self.fixed_weight.set(0.1)
 
@@ -231,6 +235,8 @@ def __init__(self, parent, *args, **kwargs):
         self.E1 = ttk.Entry(parent, textvariable=self.iterations)
         self.E1.grid(row=row, column=1, sticky=tk.W)
 
+        self.entry_row("Model repetitions", self.repetitions)
+
         row = self.row()
         self.label("Exchange type", row=row)
         r1 = ttk.Radiobutton(parent, text="Equal Exchange Rate", variable=self.model, value="equal")
@@ -239,7 +245,7 @@ def __init__(self, parent, *args, **kwargs):
         r2 = ttk.Radiobutton(parent, text="Random Exchange Rate", variable=self.model, value="random")
         r2.grid(row=self.row(), column=1, sticky=tk.W)
 
-        self.entry_row("Model repetitions", self.repetitions)
+        self.entry_row("Randomized equal gain value", self.randomized_value)
         self.entry_row("Salience Weight", self.salience_weight)
         self.entry_row("Fixed Weight", self.fixed_weight)
 
@@ -274,8 +280,8 @@ def input(self):
 
             model = AbstractModel()
 
-            from model.helpers import csvParser
-            csv_parser = csvParser.Parser(model)
+            from model.helpers import csvparser
+            csv_parser = csvparser.CsvParser(model)
 
             model = csv_parser.read(self.input_file.get())
 
@@ -290,9 +296,6 @@ def output(self):
 
         self.output_dir.set(selected_dir)
 
-    def model_type(self):
-        print(self.model.get())
-
     @staticmethod
     def col():
         ret = MainApplication.GRID_COLUMN
@@ -342,7 +345,10 @@ def to_xml(self):
         for key, value in self.__dict__.items():
             if isinstance(value, tk.Variable) and key not in ignore:
                 child = ET.Element(key)
-                child.text = str(value.get())
+                try:
+                    child.text = str(value.get())
+                except tk.TclError:
+                    child.text = str('')
                 element.append(child)
 
         return element
@@ -367,18 +373,22 @@ def run(self):
 
         if self.model.get() == "equal":
             from model.equalgain import EqualGainModel as Model
+            try:
+                model = Model(randomized_value=decimal.Decimal(self.randomized_value.get()))
+            except tk.TclError:
+                model = Model(randomized_value=None)
         else:
             from model.randomrate import RandomRateModel as Model
+            model = Model()
 
         # The event handlers for logging and writing the results to the disk.
 
         output_directory = os.path.join(self.output_dir.get(), self.input_file.get().split("/")[-1].split(".")[0], self.model.get())
 
-        model = Model()
         event_handler = Observable(model_ref=model, output_directory=output_directory)
         event_handler.log(message="Start calculation at {0}".format(start_time))
 
-        csv_parser = csvParser.Parser(model_ref=model)
+        csv_parser = csvparser.CsvParser(model_ref=model)
 
         if not os.path.isdir(output_directory):
             os.makedirs(output_directory)

model.py

@@ -1,15 +1,17 @@
-import os
-from datetime import datetime
-
-from model.helpers import helpers, csvParser
-from model.helpers.helpers import ModelLoop
-from model.observers.exchanges_writer import ExchangesWriter
-from model.observers.externalities import Externalities
-from model.observers.issue_development import IssueDevelopment
-from model.observers.observer import Observable
+import decimal
 
 if __name__ == "__main__":
 
+    import os
+    from datetime import datetime
+
+    from model.helpers import helpers, csvparser
+    from model.helpers.helpers import ModelLoop
+    from model.observers.exchanges_writer import ExchangesWriter
+    from model.observers.externalities import Externalities
+    from model.observers.issue_development import IssueDevelopment
+    from model.observers.observer import Observable
+
     args = helpers.parse_arguments()
     input_file = args.input
     output_dir = args.output
@@ -21,19 +23,26 @@
         os.makedirs(output_directory)
 
     if args.model == "equal":
-        from model.equalgain import EqualGainModel as Model
+        import model.equalgain as Model
+
+        if args.p != 'None':
+            p = decimal.Decimal(args.p)
+        else:
+            p = None
+
+        model = Model.EqualGainModel(randomized_value=p)
     else:
-        from model.randomrate import RandomRateModel as Model
+        import model.randomrate as Model
 
-    startTime = datetime.now()
+        model = Model.RandomRateModel()
 
-    model = Model()
+    startTime = datetime.now()
 
     # The event handlers for logging and writing the results to the disk.
     eventHandler = Observable(model_ref=model, output_directory=output_directory)
     eventHandler.log(message="Start calculation at {0}".format(startTime))
 
-    csvParser = csvParser.Parser(model)
+    csvParser = csvparser.CsvParser(model)
 
     Externalities(eventHandler)
     ExchangesWriter(eventHandler)