tidying things up

exposure_module/exposure.py

@@ -1,46 +1,43 @@
 import numpy as np
-from flask import Flask, render_template, request
-from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
-import matplotlib
-matplotlib.use('Agg')
-import matplotlib.pyplot as plt
-import io
-import base64
+from flask import render_template, request
 from functions import *
 from . import blueprint
 
 # 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 = 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', 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)
+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')
 for i in range(nPoly):
     polymers[i] = PolyData[i][0].decode('UTF-8')
 
+# load the index page for the exposure module
 @blueprint.route('/exposure', methods=['GET'])
 def exposure():
     return render_template('exposure_index.html', polymers=polymers)
 
+# build the report page for the exposure module
 @blueprint.route('/exposure', methods=['POST'])
 def exp_post():
     amount = float(request.form["amount"])
@@ -68,10 +65,15 @@ def exp_post():
     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((assume1, assume2, assume3, assume4, assume5))
 
-    release, diff = calcexposure(MW, amount, vol, area, time, pIndex, PolyData)
+    Ap = PolyData[pIndex][1]
+    if not np.isnan(Ap):
+        diff = piringer(MW, Ap)
+    else:
+        diff = wilkechang(MW)
+
+    release = SheetRelease(amount, vol, area, time, diff)
 
     MOS = TTC / release
 
@@ -79,19 +81,10 @@ def exp_post():
     MOS = sigfigs(MOS, 2)
     diff = sigfigs(diff, 2)
 
-    fig, ax = plt.subplots(figsize=(6, 4))
-    plt.subplots_adjust(left=0.15, bottom=0.15, right=0.95, top=0.95, wspace=0.0, hspace=0.0)
-    tarray = np.arange(1.,31.,1.)
-    rates = calcrates(MW, amount, vol, area, tarray, pIndex, PolyData)
-    ax.plot(tarray,rates,'o')
-    ax.set(
-        xlabel='time (days)',
-        ylabel='release rate (mg/day)',
-    )
-    pngImage = io.BytesIO()
-    FigureCanvas(fig).print_png(pngImage)
-    pngImageB64String = "data:image/png;base64,"
-    pngImageB64String += base64.b64encode(pngImage.getvalue()).decode('utf8')
+    # Generate the rate plot using matplotlib
+    tarray = np.arange(1., 31., 1.)
+    rates = SheetRates(amount, vol, area, tarray, diff)
+    pngImageB64String = RatePlot(tarray, rates)
 
     return render_template('exposure_report.html', polymers=polymers, pIndex=pIndex, release=release,
                            assume=assume, area=area, vol=vol, amount=amount, diff=diff, time=time, exposure=exposure, TTC=TTC,

functions.py

@@ -1,18 +1,28 @@
 import math
 import numpy as np
+from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+import io
+import base64
 
 def sigfigs(number, n):
+
     return round(number, n - int(math.floor(math.log10(math.fabs(number)))) - 1)
 
-def calcexposure(MW, amount, vol, area, time, pIndex, PolyData):
-    Ap = np.array((16.9, 11.7, 8.2, 2.6))
-    L = vol / area
-    if PolyData[pIndex][1] < 4:
-        D = 1e4 * np.exp(Ap[PolyData[pIndex][1]] - 0.1351 * MW ** (2. / 3.) + 0.003 * MW - 10454. / 310.)
-    else:
-        Va = 4.76 + 1.32 * MW
-        D = 7.4e-8 * (18. * 2.6) ** 0.5 * 310. / 0.6913 / Va ** 0.6
+def piringer(Mw, Ap):
+
+    return 1e4 * np.exp(Ap - 0.1351 * Mw ** (2. / 3.) + 0.003 * Mw - 10454. / 310.)
+
+def wilkechang(Mw):
+
+    Va = 4.76 + 1.32 * Mw
+    return 7.4e-8 * (18. * 2.6) ** 0.5 * 310. / 0.6913 / Va ** 0.6
 
+def SheetRelease(amount, vol, area, time, D):
+
+    L = vol / area
     D = D * 3600.
     tau = D * time / L ** 2.
     if tau <= 0.5:
@@ -20,17 +30,12 @@ def calcexposure(MW, amount, vol, area, time, pIndex, PolyData):
     else:
         release = amount * (1. - (8. / (np.pi ** 2.)) * np.exp(-tau * np.pi ** 2. / 4.))
 
-    return release, D
+    return release
+
+def SheetRates(amount, vol, area, time, D):
 
-def calcrates(MW, amount, vol, area, time, pIndex, PolyData):
-    Ap = np.array((16.9, 11.7, 8.2, 2.6))
-    L = vol / area
-    if PolyData[pIndex][1] < 4:
-        D = 1e4 * np.exp(Ap[PolyData[pIndex][1]] - 0.1351 * MW ** (2. / 3.) + 0.003 * MW - 10454. / 310.)
-    else:
-        Va = 4.76 + 1.32 * MW
-        D = 7.4e-8 * (18. * 2.6) ** 0.5 * 310. / 0.6913 / Va ** 0.6
     D = D * 86400.
+    L = vol / area
 
     rates = np.zeros(len(time))
     tau = D * time[0] / L ** 2.
@@ -46,4 +51,38 @@ def calcrates(MW, amount, vol, area, time, pIndex, PolyData):
         else:
             rates[i] = amount * (1. - (8. / (np.pi ** 2.)) * np.exp(-tau * np.pi ** 2. / 4.)) - np.sum(rates[:i])
 
-    return rates
+    return rates
+
+def RatePlot(tarray, rates):
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    plt.subplots_adjust(left=0.15, bottom=0.15, right=0.95, top=0.95, wspace=0.0, hspace=0.0)
+    ax.plot(tarray, rates, 'o')
+    ax.set(
+        xlabel='time (days)',
+        ylabel='release rate (mg/day)',
+    )
+    pngImage = io.BytesIO()
+    FigureCanvas(fig).print_png(pngImage)
+    pngImageB64String = "data:image/png;base64,"
+    pngImageB64String += base64.b64encode(pngImage.getvalue()).decode('utf8')
+
+    return pngImageB64String
+
+def calcexposure(MW, amount, vol, area, time, pIndex, PolyData):
+    Ap = np.array((16.9, 11.7, 8.2, 2.6))
+    L = vol / area
+    if PolyData[pIndex][1] < 4:
+        D = 1e4 * np.exp(Ap[PolyData[pIndex][1]] - 0.1351 * MW ** (2. / 3.) + 0.003 * MW - 10454. / 310.)
+    else:
+        Va = 4.76 + 1.32 * MW
+        D = 7.4e-8 * (18. * 2.6) ** 0.5 * 310. / 0.6913 / Va ** 0.6
+
+    D = D * 3600.
+    tau = D * time / L ** 2.
+    if tau <= 0.5:
+        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, D