def com_data(request):
passed_data_name = request.session.get('passed_data_name')
passed_json_columns = request.session.get('passed_json_columns')
passed_column_name = request.session.get('passed_column_name')
# generate dataTable data
json_header_table = []
for i in range(len(passed_column_name)):
json_header_table.append({"title": str(passed_column_name[i]), "targets": i})
# get user input
chosen_mode = request.POST['chose_mode']
mode_id = chosen_mode.replace("mode", "")
json_parameter = {}
json_parameter["chose_mode"] = chosen_mode
json_parameter["tuple_n"] = request.POST['tuple_N_m' + mode_id]
json_parameter["categorical_atts"] = request.POST.getlist('checks_m' + mode_id)
json_parameter["candidate_atts"] = request.POST.getlist('key_checks_m' + mode_id)
# json_parameter["categorical_threshold"] = request.POST['cate_threshold_m' + mode_id]
json_parameter["seed"] = request.POST['seed_m' + mode_id]
mode_name = ""
if mode_id != "1":
json_parameter["histogram_size"] = request.POST['hist_size_m' + mode_id]
json_parameter["epsilon"] = request.POST['epsilon_m' + mode_id]
user_type_atts = {}
for atti in passed_column_name:
user_type_atts[atti] = request.POST[atti + "_m" + mode_id]
json_parameter["type_atts"] = user_type_atts
if mode_id == "3":
json_parameter["max_degree"] = request.POST['max_degree']
if mode_id == "1":
mode_name = "Random Mode"
if mode_id == "2":
mode_name = "Independent Attribute Mode"
if mode_id == "3":
mode_name = "Correlated Attribute Mode"
request.session["mode_name"] = mode_name
# save user input parameters to server
json_parameter_outputfn = passed_data_name + "_parameters.json"
with open(json_parameter_outputfn, 'w') as outfile:
json.dump(json_parameter, outfile, indent=4)
wrapper.generate_data(passed_data_name)
synthetic_data_name = passed_data_name + "_synthetic_data.csv"
description_file = passed_data_name + "_description.json"
wrapper.get_plot_data(passed_data_name + ".csv", synthetic_data_name, description_file)
passed_download_data = synthetic_data_name.split("/media/")[1]
passed_download_desp = description_file.split("/media/")[1]
request.session["passed_download_data"] = passed_download_data
request.session["passed_download_desp"] = passed_download_desp
context = {'passed_data_name': passed_data_name, "passed_json_columns": passed_json_columns,
"passed_json_columns_header": json_header_table, "mode_name": mode_name,
"passed_download_data": passed_download_data, "passed_download_desp": passed_download_desp}
return render(request, 'synthesizer/com_data.html', context)
def proc_data_dash(request):
passed_data_name = request.session.get('passed_data_name')
up_data = DataDescriberUI()
up_data.read_dataset_from_csv(passed_data_name)
up_data.get_dataset_meta_info()
up_data.get_json_data()
json_header = []
att_list = up_data.dataset_description['meta']['attribute_list']
for i in range(len(att_list)):
json_header.append({"data": str(att_list[i])})
request.session['passed_json_columns'] = json_header
request.session['passed_column_name'] = att_list
json_cate_info = wrapper.get_dataset_info(passed_data_name + ".csv")
cat_att_list = json_cate_info["categorical_attributes"]
data_type_list = []
for i in att_list:
data_type_list.append(json_cate_info["attribute_datatypes"][i])
tuple_n = json_cate_info["number_of_tuples"]
context = {
'passed_data_name': passed_data_name,
"passed_json_columns": json_header,
"passed_column_name": att_list,
"passed_cat_atts": cat_att_list,
"passed_att_types": data_type_list,
"tuple_n": tuple_n
}
return render(request, "synthesizer/proc_data_dash.html", context)
def proc_data_dash(request):
passed_data_name = request.session.get('passed_data_name')
json_cate_info = wrapper.get_dataset_info(passed_data_name + ".csv")
att_list = json_cate_info["attribute_list"]
cat_att_list = json_cate_info["categorical_attributes"]
key_att_list = json_cate_info['candidate_attributes']
# json_header = []
# for i in range(len(att_list)):
# json_header.append({"data": str(att_list[i])})
# initialize json data and header for dataTables
json_data_table = []
json_header_table = []
for i in range(len(att_list)):
json_data_table.append({"data": str(att_list[i])})
json_header_table.append({"title": str(att_list[i]), "targets": i})
request.session['passed_json_columns'] = json_data_table
request.session['passed_column_name'] = att_list
data_type_list = []
for i in att_list:
data_type_list.append(json_cate_info["attribute_datatypes"][i])
tuple_n = json_cate_info["number_of_tuples"]
context = {'passed_data_name': passed_data_name, "passed_json_columns": json_data_table,
"passed_column_name": att_list, "passed_json_columns_header": json_header_table,
"passed_cat_atts": cat_att_list, "passed_att_types": data_type_list, "tuple_n": tuple_n,
"passed_key_atts": key_att_list}
return render(request, "synthesizer/proc_data_dash.html", context)
def com_histogram(request):
passed_data = request.session.get('passed_data_name')
passed_json_columns = request.session.get('passed_json_columns')
passed_column_name = request.session.get('passed_column_name')
mode_name = request.session.get('mode_name')
passed_download_data = request.session.get('passed_download_data')
passed_download_desp = request.session.get('passed_download_desp')
# get categorical attributes list
cate_atts = wrapper.get_categorical_attributes(passed_data + '_plot.json')
draw_atts = wrapper.get_drawable_attributes(passed_data + '_plot.json')
context = {'passed_data_name': passed_data, "passed_json_columns": passed_json_columns,
"passed_column_name": passed_column_name, "cate_column_name": cate_atts,
"mode_name": mode_name, "drawable_atts": draw_atts,
"passed_download_data": passed_download_data, "passed_download_desp": passed_download_desp}
return render(request, 'synthesizer/com_histogram.html', context)