New model and data input

DataModels/GC.py

@@ -120,7 +120,7 @@ class GC(Cell):
     def run_vw(self):
         print("VOWPAL WABBIT")
         x, y = self.x, self.y
-        for i in range(20):
+        for i in range(1):
             action, position = get_predicted_move([x, y])
             if(action != "pick_garbage"):
                 x, y = position

VowpalWabbit/VowpalDataCache/constant_input.txt

@@ -1 +1 @@
-0 1.0 map20190605103058832675_auto|GC_Position 4,1 |GC_Area G(2,0) R(2,1) E(2,2) E(2,3) R(3,0) R(3,1) R(3,2) R(3,3) H(4,0) E(4,2) H(4,3) 
+1 | F00:0 F01:5 F02:1 F03:0 F10:1 F11:1 F12:1 F13:1 F20:4 F21:0 F23:2 

VowpalWabbit/VowpalDataCache/constant_output.txt

@@ -1 +1 @@
-2.412344 map20190605103058832675_auto
+2.731161

VowpalWabbit/generate_dataset.py

@@ -18,7 +18,7 @@ def generate_dataset(run_count, clear, model_name, learn):
     filename = "./VowpalWabbit/VowpalInputData/input_dataset" + str(datetime.datetime.now().strftime("%m%d%H%M")) + model_name
     print("Creating input file " + filename + ".txt... ", end = '')
         
-    input_file = open(filename,"w+")
+    input_file = open(filename,"a+")
     for pfile in glob.glob('./VowpalWabbit/VowpalInputData/input_map*.txt'):
         #print(pfile)
         partial_input = open(pfile, "r+")
@@ -35,4 +35,4 @@ def generate_dataset(run_count, clear, model_name, learn):
         wrap_ex("vw " + filename + ".txt -c --passes 2 -f " + model_file)
         print("Learning process complete, model saved to " + model_file)
 
-generate_dataset(6, True, "3k_001", True)
+generate_dataset(200, True, "teraz", True)

VowpalWabbit/vowpal_utils.py

@@ -1,9 +1,9 @@
-import re
+import re, os
 from config import MAP_NAME, GRID_WIDTH, GRID_HEIGHT, GC_X, GC_Y
 from VowpalWabbit.VowpalWrapper import wrapper
 
 #const
-RADIUS = 1
+RADIUS = 2
 ##
 
 COORDINATES_LIST = []
@@ -55,10 +55,10 @@ def parse_list(whole_result,current_x,current_y):
             moves.append(parser[f"[{x_subtraction},{y_subtraction}]"])
     #print(moves)
     MOVES_LIST = moves.copy()
-    generate_input(1.0)
+    generate_input()
     return moves
 
-def generate_input(importance):
+def generate_input():
     i = 1 #we'll use it to map coords to moves
     input_file_content = []
     for position in COORDINATES_LIST[:len(COORDINATES_LIST)-1]:
@@ -66,9 +66,13 @@ def generate_input(importance):
         coords = check_position(position, i) #set valid gc position
 
         #vowpal config goes here
+        importance = 1.0
         label = moves_mapping[MOVES_LIST[i]]
-        #" " + str(importance) +
+        if(label == 4 or label == 5):
-        input_line = str(label) +  " | "
+            importance = 3.0
+        elif(label == 1):
+            importance = 15.0
+        input_line = str(label) + " " + str(importance) + " | "
 
         area = get_gc_area(coords, RADIUS)
         for a in area:
@@ -80,15 +84,13 @@ def generate_input(importance):
     #save to file
     tag = re.findall("(map_[0-9]+|map[0-9]+_auto)", MAP_NAME)[0]
     filename = "./VowpalWabbit/VowpalInputData/input_" + str(tag) + ".txt"
-    input_file = open(filename,"w+")
+    input_file = open(filename,"a+")
     for line in input_file_content:
         input_file.write(line+"\n")
     input_file.close()
 
 def pass_input(position):
-    label = 0
+    input_line = "1 | "
-    gc_position = "|GC_Position "+str(position[0])+","+str(position[1])
-    input_line = str(label) + " 1.0 " + tag + gc_position+" | "
     area = get_gc_area(position, RADIUS)
     for a in area:
         input_line += a + " "
@@ -128,7 +130,7 @@ def check_position(position, i):
 def get_predicted_move(position):
     input_filename = pass_input(position)
     output_filename = "./VowpalWabbit/VowpalDataCache/constant_output.txt"
-    wrapper.wrap_ex("vw -i ./VowpalWabbit/VowpalModels/25k_002.model -t "+input_filename+" -p "+output_filename+" --quiet")
+    wrapper.wrap_ex("vw -i ./VowpalWabbit/VowpalModels/teraz.model -t "+input_filename+" -p "+output_filename+" ")
     with open( output_filename, 'r' ) as fout:
         prediction = float(list(fout.readline().split())[0])
     move = make_move_from_prediction(prediction)