Fixed - "None" in BF RR was converted to NaN in pandas

optimamodel · Mar 18, 2024 · 4295089 · 4295089
1 parent 5c09bf0
commit 4295089
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Showing 6 changed files with 14 additions and 6 deletions.
diff --git a/inputs/en/demo_national_input.xlsx b/inputs/en/demo_national_input.xlsx
diff --git a/nutrition/data.py b/nutrition/data.py
@@ -318,7 +318,7 @@ def get_risk_dist(self):
         # self.calcscache.write_row('Nutritional status distribution', 14, 2, anaem[:])
 
         # for age, prev in anaem.items():  # Should work with commented out code above
-        for age, prev in anaem.iteritems():
+        for age, prev in anaem.items():
             self.risk_dist[_("Anaemia")][age] = dict()
             self.risk_dist[_("Anaemia")][age][_("Anaemic")] = prev
             self.risk_dist[_("Anaemia")][age][_("Not anaemic")] = 1.0 - prev
@@ -625,6 +625,8 @@ def make_dict2(self, mydict):
             for condCat in mydict[age].keys():
                 cond = condCat[0]
                 cat = condCat[1]
+                if type(cat) == float:
+                    cat = "None"
                 if res_dict[age].get(cat) is None:
                     res_dict[age][cat] = dict()  # CK TEST
                     res_dict[age][cat][cond] = mydict[age][condCat]
@@ -639,6 +641,8 @@ def make_dict3(self, mydict):
             res_dict[age] = sc.odict()
             for condCat in mydict[age].keys():
                 cat = condCat[1]
+                if type(cat) == float:
+                    cat = "None"
                 if res_dict[age].get(cat) is None:
                     res_dict[age][cat] = mydict[age][condCat]
         return res_dict
@@ -1237,6 +1241,8 @@ def make_dict2(self, mydict):
             for condCat in mydict[age].keys():
                 cond = condCat[0]
                 cat = condCat[1]
+                if type(cat) == float:
+                    cat = "None"
                 if res_dict[age].get(cat) is None:
                     res_dict[age][cat] = dict()  # CK TEST
                     res_dict[age][cat][cond] = mydict[age][condCat]
@@ -1251,6 +1257,8 @@ def make_dict3(self, mydict):
             res_dict[age] = sc.odict()
             for condCat in mydict[age].keys():
                 cat = condCat[1]
+                if type(cat) == float:
+                    cat = "None"
                 if res_dict[age].get(cat) is None:
                     res_dict[age][cat] = mydict[age][condCat]
         return res_dict

diff --git a/nutrition/programs.py b/nutrition/programs.py
@@ -297,8 +297,8 @@ def _wasting_prev_update(self, age_group):
                 # If SAM treatment is extended to MAM, then the coverage refers to SAM children, who are only a fraction of MAM children
                 newcov = min(1, self.annual_unrestr_cov[self.year] * age_group.frac_wasted(_('SAM')) / age_group.frac_wasted(_('MAM')))
                 newProb = get_new_prob(newcov, probWastedIfCovered, probWastedIfNotCovered)
-                print(self.year, age_group.age, newcov, probWastedIfCovered, newProb, oldProb,
-                      sc.safedivide(oldProb - newProb, oldProb, default=0.0), probWastedIfCovered - probWastedIfNotCovered)
+                # print(self.year, age_group.age, newcov, probWastedIfCovered, newProb, oldProb,
+                #       sc.safedivide(oldProb - newProb, oldProb, default=0.0), probWastedIfCovered - probWastedIfNotCovered)
             else:
                 newcov = self.annual_unrestr_cov[self.year]
                 newProb = get_new_prob(newcov, probWastedIfCovered, probWastedIfNotCovered)

diff --git a/tests/scen_results_test.xlsx b/tests/scen_results_test.xlsx
diff --git a/tests/test.prj b/tests/test.prj
diff --git a/tests/testdemo.py b/tests/testdemo.py
@@ -5,9 +5,9 @@
 import nutrition.ui as nu
 
 do_plot = True
-run_scen = False
-run_optim = True
-run_geo = False
+run_scen = True
+run_optim = False
+run_geo = True
 
 P = nu.demo(scens=run_scen, optims=run_optim, geos=run_geo)