broke out exposure calculation into different functions, added comments, and moved polymer input to a separate .py file

CHRIS.py

@@ -1,35 +1,10 @@
 from flask import Flask, render_template, request
 import numpy as np
-import math
-
-
-def sigfigs(number, n):
-    return round(number, n - int(math.floor(math.log10(math.fabs(number)))) - 1)
-
-
-# Named polymer matrices and category numbers
-nPoly = 20
-PolyData = np.zeros((nPoly,), dtype=[('name', 'a75'), ('Category', 'i')])
-PolyData[0] = ('Silicone', 0)
-PolyData[1] = ('Polyethylene (density <= 0.94 g/cm3)', 1)
-PolyData[2] = ('Polyethylene (density > 0.94 g/cm3)', 2)
-PolyData[3] = ('Polyethylene terephthalate', 3)
-PolyData[4] = ('Polyurethane (polyether)', 1)
-PolyData[5] = ('Polycarbonate', 3)
-PolyData[6] = ('Polyoxymethylene', 2)
-PolyData[7] = ('Poly(methyl methacrylate)', 3)
-PolyData[8] = ('Acrylonitrile butadiene styrene', 2)
-PolyData[9] = ('Polyether block amide', 1)
-PolyData[10] = ('Polyamide', 3)
-PolyData[11] = ('Polystyrene', 3)
-PolyData[12] = ('Polyvinyl chloride (plasticized)', 0)
-PolyData[13] = ('Polytetrafluoroethylene', 2)
-PolyData[14] = ('Polyvinyl acetate', 1)
-PolyData[15] = ('Polypropylene', 2)
-PolyData[16] = ('Polybutylene terephthalate', 3)
-PolyData[17] = ('Polyetheretherketone', 3)
-PolyData[18] = ('Fluorinated ethylene propylene', 2)
-PolyData[19] = ('Other polymer', 4)
+from functions import SigFigs, Piringer, WilkeChang, SheetRelease
+from polymers import Polymers
+
+# load polymer data including Ap values
+polymers, Ap = Polymers()
 
 # Named color additives, TI values, and Mw
 nCA = 14
@@ -49,10 +24,6 @@ caData[11] = ('Other metal oxide color additive', 1.0, 1100.0)
 caData[12] = ('Other non-metal oxide color additive', 1.0, 1100.0)
 caData[13] = ('Other compound (non-color additive)', 1.0, 1100.0)
 
-polymers = np.zeros(nPoly, dtype='object')
-for i in range(nPoly):
-    polymers[i] = PolyData[i][0].decode('UTF-8')
-
 CAs = np.zeros(nCA, dtype='object')
 caMW = np.zeros(nCA, dtype='object')
 for i in range(nCA):
@@ -61,7 +32,7 @@ for i in range(nCA):
     caMW[i] = caData[i][2]
 
 app = Flask(__name__)
-app.debug = False
+app.debug = True
 
 
 @app.route('/', methods=['GET'])
@@ -114,15 +85,16 @@ def app_post():
     else:
         TTC = 0.0015
 
-    assume1 = request.form.get("assume1") is not None
-    assume2 = request.form.get("assume2") is not None
-    assume3 = request.form.get("assume3") is not None
-    assume4 = request.form.get("assume4") is not None
-    assume5 = request.form.get("assume5") is not None
+    assume = np.array((request.form.get("assume1") is not None, request.form.get("assume2") is not None,
+                       request.form.get("assume3") is not None, request.form.get("assume4") is not None,
+                       request.form.get("assume5") is not None))
 
-    assume = np.array((assume1, assume2, assume3, assume4, assume5))
+    if not np.isnan(Ap[pIndex]):
+        diff = Piringer(MW, Ap[pIndex])
+    else:
+        diff = WilkeChang(MW)
 
-    release, diff = calcexposure(MW, amount, vol, area, time, pIndex)
+    release = SheetRelease(amount, vol, area, time, diff)
 
     if caIndex > 10:
         MOS = TTC / release
@@ -131,11 +103,11 @@ def app_post():
 
     iMOS = TTC / impurity
 
-    release = sigfigs(release, 2)
-    MOS = sigfigs(MOS, 2)
-    diff = sigfigs(diff, 2)
-    iMOS = sigfigs(iMOS, 2)
-    impurity = sigfigs(impurity, 2)
+    release = SigFigs(release, 2)
+    MOS = SigFigs(MOS, 2)
+    diff = SigFigs(diff, 2)
+    iMOS = SigFigs(iMOS, 2)
+    impurity = SigFigs(impurity, 2)
 
     return render_template('report.html', polymers=polymers, pIndex=pIndex, caIndex=caIndex, release=release,
                            assume=assume,

functions.py

@@ -0,0 +1,35 @@
+import math
+import numpy as np
+
+
+def SigFigs(number, n):
+
+    return round(number, n - int(math.floor(math.log10(math.fabs(number)))) - 1)
+
+def Piringer(Mw, Ap):
+    # Semi-empirical model for D(Mw) given polymer property Ap- Toxicol. Sci. 2019, 172 (1), 201–212.
+    T = 310.
+    return 1e4 * np.exp(Ap - 0.1351 * Mw ** (2. / 3.) + 0.003 * Mw - 10454. / T)
+
+def WilkeChang(Mw):
+    # Semi-empirical model for D(Mw) assuming diffusion in water
+    Va = 4.76 + 1.32 * Mw # molecular volume as a function of Mw assuming linear alkanes as worst case
+    T = 310.
+    MwH2O = 18.
+    viscosity = 0.6913
+    alpha = 2.6
+
+    return 7.4e-8 * (MwH2O * alpha) ** 0.5 * T / viscosity / Va ** 0.6
+
+def SheetRelease(amount, vol, area, time, D):
+
+    # analytical solution(s) to Fick's law for a plane sheet
+    L = vol / area
+    D = D * 3600. # convert seconds to hours
+    tau = D * time / L ** 2. # dimensionless time
+    if tau <= 0.2:
+        release = 2. * amount * np.sqrt(tau / np.pi)
+    else:
+        release = amount * (1. - (8. / (np.pi ** 2.)) * np.exp(-tau * np.pi ** 2. / 4.))
+
+    return release

polymers.py

@@ -0,0 +1,36 @@
+import numpy as np
+
+def Polymers():
+
+	# Named polymer matrices and Ap values
+	nPoly = 20
+	PolyData = np.zeros((nPoly,), dtype=[('name', 'a75'), ('Ap', 'f')])
+	PolyData[0] = ('Silicone', 16.9)
+	PolyData[1] = ('Polyethylene (density <= 0.94 g/cm3)', 11.7)
+	PolyData[2] = ('Polyethylene (density > 0.94 g/cm3)', 8.2)
+	PolyData[3] = ('Polyethylene terephthalate', 2.6)
+	PolyData[4] = ('Polyurethane (polyether)', 11.7)
+	PolyData[5] = ('Polycarbonate', 2.6)
+	PolyData[6] = ('Polyoxymethylene', 8.2)
+	PolyData[7] = ('Poly(methyl methacrylate)', 3)
+	PolyData[8] = ('Acrylonitrile butadiene styrene', 8.2)
+	PolyData[9] = ('Polyether block amide', 11.7)
+	PolyData[10] = ('Polyamide', 2.6)
+	PolyData[11] = ('Polystyrene', 2.6)
+	PolyData[12] = ('Polyvinyl chloride (plasticized)', 16.9)
+	PolyData[13] = ('Polytetrafluoroethylene', 8.2)
+	PolyData[14] = ('Polyvinyl acetate', 11.7)
+	PolyData[15] = ('Polypropylene', 8.2)
+	PolyData[16] = ('Polybutylene terephthalate', 2.6)
+	PolyData[17] = ('Polyetheretherketone', 2.6)
+	PolyData[18] = ('Fluorinated ethylene propylene', 8.2)
+	PolyData[19] = ('Other polymer', None)
+
+	# Convert the list to a format the html likes
+	polymers = np.zeros(nPoly, dtype='object')
+	Ap = np.zeros(nPoly)
+	for i in range(nPoly):
+		polymers[i] = PolyData[i][0].decode('UTF-8')
+		Ap[i] = PolyData[i][1]
+
+	return polymers, Ap