Fixed convolutions

model.py

@@ -1,18 +1,17 @@
 import matplotlib
 import numpy as np
-from scipy.ndimage import convolve
 import util
 
 '''features to add:
-basic functionality
+
 '''
 
 
 #initialState: initial fire state matrix
 #tempHigh: vector of high temperatures over the next 14 days
 #tempLow: vector of low temperatures over the next 14 days
 #precipVec: vector of precipitation values (decimal) over the next 14 days
-#windVec: vector of wind speeds over the next 14 days (all northwesternly)
+#windVec: vector of wind speeds over the next 14 days (all southeasternly)
 #humidVec: vector of humidity values over the next 14 days
 #density: tree density
 #r: side length of partitions in km
@@ -36,13 +35,21 @@ def __init__(self, initialState, tempHigh, tempLow, precip, wind, humid, density
         self.temp = tempLow[0]      #figure this out in more detail later
         self.humid = humid[0]
         self.precip = precip[0]
+        self.mask = np.ones(initialState.shape)
     def fireSpread(self):
-        kernel = util.findKernel(self.state, self.wind, self.humid, self.precip)
-        self.state = convolve(self.state, kernel, mode='constant')
+        kernel = util.findKernel(self.state, self.wind, self.humid, self.precip) #calculate kernel for convolution
+        self.state = util.maskConvolve(self.state, kernel, self.mask) #convolve but skipping burnt out cells
+        self.burnout() #check if any regions are over 100% burned
 
-        #iterate over all matrix entries, randomly determine spread according to temperature, density, humiditiy, wind
+        #need to add sensitivity to wind, humidity, and preciptiation
 
+    def burnout(self):
+        for i in range(self.state.shape[0]):
+            for j in range(self.state.shape[1]):
+                if self.state[i,j] >= 1:
+                    self.state[i,j] = 0 
+                    self.mask[i,j] = 0
 
     def timeStep(self):
-        #fireSpread and fireGrow; increment t
-        pass
+        self.fireSpread()
+        self.t += 1

test.py

@@ -3,8 +3,8 @@
 import model
 import time
 
-initialState = np.zeros((5,5))
-initialState[2,0] = 0.1
+initialState = np.zeros((36,88))
+initialState[18,44] = 0.1
 
 tempHigh = np.array([94,87,86,97,98,89,92,96,98,99,103,103,97,91])
 tempLow = np.array([60,56,55,59,61,61,57,58,59,64,65,64,62,57])
@@ -18,7 +18,8 @@
 plt.imshow(testModel.state, cmap=plt.get_cmap('inferno'))
 plt.show
 for i in range(7):
-    testModel.fireSpread()
+    testModel.timeStep()
+    #print(testModel.state)
 
     plt.figure(i+2)
     plt.imshow(testModel.state, cmap=plt.get_cmap('inferno'))

util.py

@@ -1,4 +1,10 @@
 import numpy as np
+from scipy.ndimage import convolve
 
-def findKernel(state,wind,humidity,precip):
-    return np.ones((3,3))
+def findKernel(state,wind,humidity,precip): 
+    kernel = np.ones((3,3))
+    return kernel
+
+def maskConvolve(state,kernel,mask):
+    conv = convolve(state, kernel, mode='constant')
+    return np.where(mask, conv, state)