Refactored by Sourcery (#145)

Co-authored-by: Sourcery AI <[email protected]>

Views.py

@@ -101,10 +101,10 @@ def check_account_fields(fields, new_user=True):
         'password2' : r'^.+$',
         'website' : r'.*$'
     }
-    good_fields = dict()
-    for field in regexes:
+    good_fields = {}
+    for field, value in regexes.items():
         field_input = fields.get(field)
-        if field_input and re.match(regexes[field], field_input) or field == 'website':
+        if field_input and re.match(value, field_input) or field == 'website':
             good_fields[field] = field_input
     uname, password1, password2 = \
         fields.get('username'), fields.get('password1'), fields.get('password2')
@@ -177,7 +177,7 @@ def show_find_pt(URL2):
 def case_to_dict(case):
     ''' Prepare case attributes to be passed to the template. '''
 
-    input_dict = dict()
+    input_dict = {}
     for attr in dir(case):
         try:
             input_dict[attr] = case.__getattribute__(attr)
@@ -274,7 +274,7 @@ def log_in(request):
         Otherwise, return an error page. '''
 
     username, password = request.POST.get('username'), request.POST.get('password')
-    if not username or not password:
+    if not (username and password):
         return incorrect_login(request)
     elif username in TerminatedAccounts.objects.values_list('username', flat=True):
         return error('This account was deleted.')
@@ -346,7 +346,7 @@ def create_account(request):
 
     input_dict = dict(csrf(request))
     if 'HTTP_REFERER' in request.META and '/reg_conditions/' in request.META.get('HTTP_REFERER'):
-        request.session['good_fields'] = dict()
+        request.session['good_fields'] = {}
         input_dict['first_time'] = True
     input_dict.update(request.session['good_fields'])
     return render_to_response('account_create.html', input_dict)
@@ -842,14 +842,35 @@ def testcase_admin(request):
     caselist = []
 
     for i in Case.objects.all():
-        inputlist = []
-        inputlist.append(i.id)
-        inputlist.append(i.case_name)
-        inputlist.append(i.Age)
-        inputlist.append(i.Sex)
-        inputlist.append('(' + str(i.upright_lat  ) + ',' + str(i.upright_lon ) + ');'+'(' + str(i.downright_lat) + ',' + str(i.downright_lon ) + ');'+'(' + str(i.upleft_lat) + ',' + str(i.upleft_lon ) + ');'+'(' + str(i.downleft_lat ) + ',' + str(i.downleft_lon) + ')')
-        inputlist.append('(' + str(i.findx) + ',' + str(i.findy ) + ')')
-        inputlist.append(str(i.UploadedLayers))
+        inputlist = [
+            i.id,
+            i.case_name,
+            i.Age,
+            i.Sex,
+            '('
+            + str(i.upright_lat)
+            + ','
+            + str(i.upright_lon)
+            + ');'
+            + '('
+            + str(i.downright_lat)
+            + ','
+            + str(i.downright_lon)
+            + ');'
+            + '('
+            + str(i.upleft_lat)
+            + ','
+            + str(i.upleft_lon)
+            + ');'
+            + '('
+            + str(i.downleft_lat)
+            + ','
+            + str(i.downleft_lon)
+            + ')',
+            '(' + str(i.findx) + ',' + str(i.findy) + ')',
+            str(i.UploadedLayers),
+        ]
+
         caselist.append(inputlist)
 
     return render_to_response('TestCaseMenu.html',{'case_list':caselist})
@@ -947,8 +968,8 @@ def evaluate(request):
 @login_required
 def completed_test(request):
     test_name = str(request.GET.get('name')).strip()
-    completed_lst = list(test.test_name for test in
-        request.session['active_model'].tests.all() if not test.active)
+    completed_lst = [test.test_name for test in
+            request.session['active_model'].tests.all() if not test.active]
 
     if test_name not in completed_lst:
         request.session['error'] = 'The test that you requested does not exist.'
@@ -1002,7 +1023,10 @@ def leaderboard(request):
                 model.save()
 
     input_dict['case_names'] = Case.objects.values_list('case_name', flat=True)
-    input_dict['case_categories'] = set(case.subject_category for case in Case.objects.all())
+    input_dict['case_categories'] = {
+        case.subject_category for case in Case.objects.all()
+    }
+
     input_dict['model_data'] = model_data
     input_dict['prev_filter'] = filter_choice
     return render_to_response('leaderboard.html', input_dict)
@@ -1323,10 +1347,7 @@ def Account_Profile(request):
     # get model descriptions
     modellst = []
     for i in active_account.account_models.all():
-        templst = []
-        templst.append(i.name_id)
-        templst.append(i.description)
-        templst.append(account_in)
+        templst = [i.name_id, i.description, account_in]
         modellst.append(templst)
 
     inputdic['modellst'] = modellst
@@ -1444,13 +1465,13 @@ def upload_casefile(request):
         except Case.DoesNotExist:
             find_case = None
         # Case does exist:
-        if find_case != None:
-            row.append("Ignored, name exists")
-        else:
+        if find_case is None:
             new_case.initialize()
             new_case.save()
             row.append("Success")
 
+        else:
+            row.append("Ignored, name exists")
     return render_to_response('bulkcasereg_complete.html', {'result': data})
 
 

arc-models/Get_distance_rings.py

@@ -263,7 +263,7 @@ def getpng(Subject_Category,EcoReg,Terrain):
 cursor = arcpy.da.SearchCursor(fctable, ["Name","State",
         "Subject_Ca","EcoRegion","Terrain","lat","long_"])
 for row in cursor:
-       
+
         namelist.append(row[0]);
         stateabbrv.append(row[1]);
         subject_category.append(row[2]);
@@ -280,33 +280,36 @@ def getpng(Subject_Category,EcoReg,Terrain):
         for val in nameval:
             if (val >='0' and val <= '9'):
                 keystr = keystr + val     
-                   
+
         keyval = keystr;
         totname = stateabbrv[value] + keyval
         key.append(totname);
         keystr = ''
-#transform to integers        
-for i in range(len(cat_list)):
-	raster_name = "C:/Users/Eric Cawi/Documents/SAR/tifs/" + cat_list[i] + ".tif"
-	transform_name = "C:/Users/Eric Cawi/Documents/SAR/tifs/transform" + cat_list[i] + ".tif"
-	conversion_name = "C:/Users/Eric Cawi/Documents/SAR/16bittifs/" + cat_list[i] + ".tif"
-	png_name = "C:/Users/Eric Cawi/Documents/SAR/pngs"
-	transform_raster = 5*Int(Log2(raster_name))+255
-
-	transform_raster.save(transform_name)
-	arcpy.CopyRaster_management(transform_name, conversion_name,"DEFAULTS","","","","","16_BIT_UNSIGNED","NONE")
-	arcpy.RasterToOtherFormat_conversion(conversion_name,png_name, "PNG")
+png_name = "C:/Users/Eric Cawi/Documents/SAR/pngs"
+#transform to integers
+for cat in cat_list:
+    raster_name = "C:/Users/Eric Cawi/Documents/SAR/tifs/" + cat + ".tif"
+    transform_name = (
+        "C:/Users/Eric Cawi/Documents/SAR/tifs/transform" + cat + ".tif"
+    )
+
+    conversion_name = "C:/Users/Eric Cawi/Documents/SAR/16bittifs/" + cat + ".tif"
+    transform_raster = 5*Int(Log2(raster_name))+255
+
+    transform_raster.save(transform_name)
+    arcpy.CopyRaster_management(transform_name, conversion_name,"DEFAULTS","","","","","16_BIT_UNSIGNED","NONE")
+    arcpy.RasterToOtherFormat_conversion(conversion_name,png_name, "PNG")
 
 for i in range(len(key)):
-        
+
         sc = subject_category[i]
         ecoreg = ecoregion_domain[i]
         terr = terrain[i]
         fname = getpng(sc,ecoreg,terr)#gets the appropriate distance tif for each point in the pointlist
         #transform to integers
-        
+
         point_name = "C:/Users/Eric Cawi/Documents/SAR/test_cases/Distance_" + key[i]+".png" # the proper format for the thingy
-        
+
         shutil.copy(fname,point_name)#this should work
 
 exit;

arc-models/motion_model.py

@@ -95,8 +95,7 @@ def avg_speed(current_cell, new_theta,dr, walking_speeds, res):
         newx, newy = oldx+dx, oldy+dy
         first_speed = walking_speeds[oldy][oldx]
         last_speed = walking_speeds[newy][newx]
-        speed = (first_speed+last_speed)/2
-        return speed
+        return (first_speed+last_speed)/2
 
 def main():
 

data_analysis/hours_plot-1.py

@@ -55,12 +55,11 @@ def bootstrap_resample(X, n=None):
 
     From http://nbviewer.ipython.org/gist/aflaxman/6871948
     """
-    if n == None:
+    if n is None:
         n = len(X)
 
     resample_i = np.floor(np.random.rand(n) * len(X)).astype(int)
-    X_resample = X[resample_i]
-    return X_resample
+    return X[resample_i]
 
 
 def percent_survival(lst):

data_analysis/hours_plot.py

@@ -65,12 +65,11 @@ def bootstrap_resample(X, n=None):
 
     From http://nbviewer.ipython.org/gist/aflaxman/6871948
     """
-    if n == None:
+    if n is None:
         n = len(X)
 
     resample_i = np.floor(np.random.rand(n) * len(X)).astype(int)
-    X_resample = X[resample_i]
-    return X_resample
+    return X[resample_i]
 
 
 mapping = dict()  # Key: hours, value: list of subject statuses
@@ -106,7 +105,7 @@ def is_doa(x):
     return 0
 
 x = list(sorted(mapping.keys()))
-y = list(percent_survival(mapping[hours]) for hours in x)
+y = [percent_survival(mapping[hours]) for hours in x]
 N = [len(mapping[hours]) for hours in x]
 for hours, survival_rate, n in zip(x, y, N):
     print('Survival rate at {} hours = {:.1f}% (N={})'.format(hours, survival_rate, N))
@@ -137,8 +136,8 @@ def is_doa(x):
 elif '-B' in sys.argv:
     data, positions, widths = list(), list(), list()
     for (lowerbound, upperbound), increment in bin_scheme.items():
-        bin_x = list(hours for hours in x if lowerbound < hours <= upperbound)
-        bin_y = list(y[x.index(hours)] for hours in bin_x)
+        bin_x = [hours for hours in x if lowerbound < hours <= upperbound]
+        bin_y = [y[x.index(hours)] for hours in bin_x]
         data.append(bin_y)
         positions.append(np.average(bin_x))
         widths.append(min(20, (upperbound - lowerbound) // 1.5))

data_analysis/hours_plot_cat2.py

@@ -43,7 +43,7 @@ def read_cases(filename, sheet_index=0):
 
 
 def group_by_category(hours_slice, status_slice, category_slice):
-    category_map = dict()
+    category_map = {}
     cases = zip(hours_slice, status_slice, category_slice)
     for hours, status, category in cases:
         if hours != '' and category != '':
@@ -105,12 +105,11 @@ def bootstrap_resample(X, n=None):
 
     From http://nbviewer.ipython.org/gist/aflaxman/6871948
     """
-    if n == None:
+    if n is None:
         n = len(X)
 
     resample_i = np.floor(np.random.rand(n) * len(X)).astype(int)
-    X_resample = X[resample_i]
-    return X_resample
+    return X[resample_i]
 
 
 def add_trendline(x, y, N, color):
@@ -125,14 +124,14 @@ def main():
         exit(CMD_LINE_HELP.strip().format(sys.argv[0]))
     else:
         filename = sys.argv[1]
-    
+
     hours_slice, status_slice, category_slice = read_cases(filename)
     print('Number of cases: {}'.format(len(hours_slice)))
-    
+
     # Key: category, value: list of (hours, status) points
     category_map = group_by_category(hours_slice, status_slice, category_slice)
     category_groups = list(get_category_groups(category_map))
-    
+
     # Key: (lowerbound inclusive, upperbound), value: increment size
     bin_scheme = {
         (0, 12): 1, 
@@ -141,23 +140,23 @@ def main():
         (48, 96): 12, 
         (96, float('inf')): 48
     }
-    
+
     colors = 'rgbcyk'
     legend_patches, legend_labels = list(), list()
     for index, category_group in enumerate(category_groups):
         print('Group {}: {}'.format(index + 1, ', '.join(category_group)))
-        
+
         # Key: binned hours, value: list of integers where 
         # "1" means the subject(s) was/were DOA, "0" means otherwise
-        outcomes = dict()
+        outcomes = {}
         for category in category_group:
             for (hours, status) in category_map[category]:
                 binned_hours = binify(hours, bin_scheme)
                 try:
                     outcomes[binned_hours].append(is_doa(status))
                 except KeyError:
                     outcomes[binned_hours] = [is_doa(status)]
-        
+
         # Lists for each number of total hours
         _x, _y, _N = list(), list(), list()
         for hours in sorted(outcomes.keys()):
@@ -167,14 +166,14 @@ def main():
             _N.append(len(DOA_list))
             print('Survival rate at {} hours = {:.1f}% (N={})'.format(
                 _x[-1], _y[-1], _N[-1]))
-        
+
         # Lists for each (lowerbound, upperbound)
         x, y, N = list(), list(), list()
-        boxplot_data = list()
+        boxplot_data = []
         for lowerbound, upperbound in bin_scheme:
-            selected_hours = list(hours for hours in _x
-                        if lowerbound <= hours < upperbound)
-            survival_rates = list(_y[_x.index(hours)] for hours in selected_hours)
+            selected_hours = [hours for hours in _x
+                                    if lowerbound <= hours < upperbound]
+            survival_rates = [_y[_x.index(hours)] for hours in selected_hours]
             x.append(np.average(selected_hours))
             y.append(np.average(survival_rates))
             N.append(sum(_N[_x.index(hours)] for hours in selected_hours))
@@ -184,7 +183,7 @@ def main():
                     ecolor=colors[index], alpha=0.2)
             elif '-B' in sys.argv:
                 boxplot_data.append(survival_rates)
-        
+
         # The points and variations ploted are for the
         # data within each (lowerbound, upperbound).
         plt.scatter(x, y, c=colors[index], s=N, alpha=0.5)
@@ -196,13 +195,13 @@ def main():
         legend_labels.append(label)
         if '-T' in sys.argv[2:]:
             add_trendline(_x, _y, _N, colors[index])
-        
+
         if '-B' in sys.argv[2:] and '-E' not in sys.argv[2:]:
             # To set the whiskers to the 95% range, 
             # use the optional argument whis=[2.5, 97.5]
             # Only works in matplotlib version > 1.4
             plt.boxplot(boxplot_data, positions=x, widths=[10] * len(x))
-    
+
     plt.title('Total Hours vs. Survival Rate')
     plt.xlabel('Total Hours (hours)')
     plt.ylabel('Survival Rate (percent)')

data_analysis/resample.py

@@ -29,9 +29,8 @@ def bootstrap_resample(X, n=None):
 
     From http://nbviewer.ipython.org/gist/aflaxman/6871948
     """
-    if n == None:
+    if n is None:
         n = len(X)
 
     resample_i = np.floor(np.random.rand(n) * len(X)).astype(int)
-    X_resample = X[resample_i]
-    return X_resample
+    return X[resample_i]