コード例 #1
0
ファイル: groupbuilder.py プロジェクト: ikybs/CLAtoolkit
def assign_groups_class(courseCode, max_size=5):
    course_qs = UnitOffering.objects.filter(code='%s' % courseCode)

    course_users = User.objects.filter(usersinunitoffering__in=course_qs)

    #print(course_users)

    group_n = 1
    max_grp_size = max_size
    group = []

    for index in range(
            1, (len(course_users) + 1)):  #range from 1 - n; instead of 0-n
        #print index
        #print course_users[index-1], course_users[index-1].id
        try:
            #e = User.objects.filter(pk=course_users[index-1])[0]
            #print e
            group.append((course_users[index - 1], group_n))
        except Exception as e:
            print(e)

        if (index % max_grp_size is 0):
            group_n = group_n + 1

    #print(group)

    for (user, group_id) in group:
        g = GroupMap(userId=user, course_code=courseCode, groupId=group_id)
        g.save()
        print("Mapped UserId: " + str(user.id) + " in course: " +
              str(courseCode) + " to group " + str(group_id))
コード例 #2
0
def assign_groups_class(courseCode, max_size=5):
    course_qs = UnitOffering.objects.filter(code = '%s' % courseCode)

    course_users = User.objects.filter(usersinunitoffering__in=course_qs)

    #print(course_users)

    group_n = 1
    max_grp_size = max_size
    group = []

    for index in range(1,(len(course_users)+1)): #range from 1 - n; instead of 0-n
        #print index
        #print course_users[index-1], course_users[index-1].id
        try:
            #e = User.objects.filter(pk=course_users[index-1])[0]
            #print e
            group.append((course_users[index-1], group_n))
        except Exception as e:
            print(e)

        if (index%max_grp_size is 0):
            group_n = group_n+1

    #print(group)

    for (user, group_id) in group:
        g = GroupMap(userId=user, course_code=courseCode, groupId=group_id)
        g.save()
        print("Mapped UserId: "+str(user.id)+" in course: "+str(courseCode)+" to group "+str(group_id));
コード例 #3
0
ファイル: views.py プロジェクト: aneesha/CLAtoolkit
def myclassifications(request):
    context = RequestContext(request)

    course_code = None
    platform = None

    user = request.user
    username = user.username
    uid = user.id

    course_code = request.GET.get('course_code')
    platform = request.GET.get('platform')

    #get enable_group_coi_classifier boolean flag from UnitOffering
    unit = UnitOffering.objects.filter(code=course_code).get()
    enable_group_coi_classifier = unit.enable_group_coi_classifier

    group_id_seed = None

    if enable_group_coi_classifier:
        # check if the user has a grp number assigned
        group_id_seed = GroupMap.objects.filter(userId=user, course_code=course_code).values_list('groupId')

        if len(group_id_seed)<0:

            # (Table GroupMap requires an associated UserProfile as a foreign key)
            grpmapentries = []

            # max_grp_size set to 5 for development. Easily made customisable by setting this value when creating a unit
            # which can then be pulled from the associated UnitOffering instance in the DB.
            max_grp_size = 5

            # Get the current highest group number (to assign user to unit group)
            # Default is 1 (i.e. no other groups have been created)
            highest_grp_num = 1

            # Find the most current group ID
            highest_grp_dict = GroupMap.objects.filter(course_code=unit.code).aggregate(Max('groupId'))
            if highest_grp_dict['groupId__max'] is not None:
                highest_grp_num = int(highest_grp_dict['groupId__max'])

            # Now we figure out if there's space in this group (constrained by var max_grp_size)
            members_in_hgrp = GroupMap.objects.filter(groupId=highest_grp_num).count()

            if members_in_hgrp < max_grp_size:
                grpmapentries.append((course_code, highest_grp_num))
            else:
                grpmapentries.append((course_code, highest_grp_num+1))

            #Once the UserProfile has been saved, we can assign user to unit groups
            for (unit,grp_num) in grpmapentries:
                grpmap = GroupMap(userId=user, course_code=unit, groupId=grp_num)
                grpmap.save()

            group_id_seed = GroupMap.objects.filter(userId=user, course_code=course_code).values_list('groupId')

    inner_q = UserClassification.objects.filter(username=username).values_list('classification_id')
    #Need to add unique identifier to models to distinguish between classes
    classifier_name = "nb_%s_%s.model" % (course_code,platform)
    kwargs = {'classifier':classifier_name, 'xapistatement__course_code': course_code}
    if enable_group_coi_classifier:
        kwargs['xapistatement__username'] = username
    classifications_list = list(Classification.objects.filter(**kwargs).exclude(id__in = inner_q))

    if enable_group_coi_classifier:
        random.seed(group_id_seed)
        random.shuffle(classifications_list)

    context_dict = {'course_code':course_code, 'platform':platform, 'title': "Community of Inquiry Classification", 'username':username, 'uid':uid, 'classifications': classifications_list }
    return render_to_response('dashboard/myclassifications.html', context_dict, context)
コード例 #4
0
def myclassifications(request):
    context = RequestContext(request)

    course_code = None
    platform = None

    user = request.user
    username = user.username
    uid = user.id

    course_code = request.GET.get('course_code')
    platform = request.GET.get('platform')

    #get enable_group_coi_classifier boolean flag from UnitOffering
    unit = UnitOffering.objects.filter(code=course_code).get()
    enable_group_coi_classifier = unit.enable_group_coi_classifier

    group_id_seed = None

    if enable_group_coi_classifier:
        # check if the user has a grp number assigned
        group_id_seed = GroupMap.objects.filter(
            userId=user, course_code=course_code).values_list('groupId')

        if len(group_id_seed) < 0:

            # (Table GroupMap requires an associated UserProfile as a foreign key)
            grpmapentries = []

            # max_grp_size set to 5 for development. Easily made customisable by setting this value when creating a unit
            # which can then be pulled from the associated UnitOffering instance in the DB.
            max_grp_size = 5

            # Get the current highest group number (to assign user to unit group)
            # Default is 1 (i.e. no other groups have been created)
            highest_grp_num = 1

            # Find the most current group ID
            highest_grp_dict = GroupMap.objects.filter(
                course_code=unit.code).aggregate(Max('groupId'))
            if highest_grp_dict['groupId__max'] is not None:
                highest_grp_num = int(highest_grp_dict['groupId__max'])

            # Now we figure out if there's space in this group (constrained by var max_grp_size)
            members_in_hgrp = GroupMap.objects.filter(
                groupId=highest_grp_num).count()

            if members_in_hgrp < max_grp_size:
                grpmapentries.append((course_code, highest_grp_num))
            else:
                grpmapentries.append((course_code, highest_grp_num + 1))

            #Once the UserProfile has been saved, we can assign user to unit groups
            for (unit, grp_num) in grpmapentries:
                grpmap = GroupMap(userId=user,
                                  course_code=unit,
                                  groupId=grp_num)
                grpmap.save()

            group_id_seed = GroupMap.objects.filter(
                userId=user, course_code=course_code).values_list('groupId')

    inner_q = UserClassification.objects.filter(
        username=username).values_list('classification_id')
    #Need to add unique identifier to models to distinguish between classes
    classifier_name = "nb_%s_%s.model" % (course_code, platform)
    kwargs = {
        'classifier': classifier_name,
        'xapistatement__course_code': course_code
    }
    if enable_group_coi_classifier:
        kwargs['xapistatement__username'] = username
    classifications_list = list(
        Classification.objects.filter(**kwargs).exclude(id__in=inner_q))

    if enable_group_coi_classifier:
        random.seed(group_id_seed)
        random.shuffle(classifications_list)

    context_dict = {
        'course_code': course_code,
        'platform': platform,
        'title': "Community of Inquiry Classification",
        'username': username,
        'uid': uid,
        'classifications': classifications_list
    }
    return render_to_response('dashboard/myclassifications.html', context_dict,
                              context)