From 95bab46cf06ccd1e8e41ebfc8a3bc16f74ef9d13 Mon Sep 17 00:00:00 2001 From: Unknown Date: Wed, 24 Jun 2020 14:22:21 -0400 Subject: [PATCH] Delete unused tests --- translater/utils.py | 241 +------------------------------------------- 1 file changed, 1 insertion(+), 240 deletions(-) diff --git a/translater/utils.py b/translater/utils.py index dc2d2dd..df32aa6 100644 --- a/translater/utils.py +++ b/translater/utils.py @@ -278,57 +278,13 @@ def make_str(value): return str(value) -def load_umi_template_objects(filename): - """Reads - - Args: - filename (str): path of template file - - Returns: - dict: Dict of umi_objects - """ - with open(filename) as f: - umi_objects = json.load(f) - return umi_objects - - -def umi_template_object_to_dataframe(umi_dict, umi_object): - """Returns flattened DataFrame of umi_objects - - Args: - umi_dict (dict): dict of umi objects - umi_object (str): umi_object name - - Returns: - pandas.DataFrame: flattened DataFrame of umi_objects - """ - return json_normalize(umi_dict[umi_object]) - - -def get_list_of_common_umi_objects(filename): - """Returns list of common umi objects - - Args: - filename (str): path to umi template file - - Returns: - dict: Dict of common umi objects - """ - umi_objects = load_umi_template(filename) - components = OrderedDict() - for umi_dict in umi_objects: - for x in umi_dict: - components[x] = umi_dict[x].columns.tolist() - return components - - def newrange(previous, following): """Takes the previous DataFrame and calculates a new Index range. Returns a DataFrame with a new index Args: previous (pandas.DataFrame): previous DataFrame - following (pandas.DataFrame): follwoing DataFrame + following (pandas.DataFrame): following DataFrame Returns: pandas.DataFrame: DataFrame with an incremented new index @@ -345,170 +301,6 @@ def newrange(previous, following): return following -def type_surface(row): - """Takes a boundary and returns its corresponding umi-type - - Args: - row: - - Returns: - str: The umi-type of boundary - """ - - # Floors - if row["Surface_Type"] == "Floor": - if row["Outside_Boundary_Condition"] == "Surface": - return 3 - if row["Outside_Boundary_Condition"] == "Ground": - return 2 - if row["Outside_Boundary_Condition"] == "Outdoors": - return 4 - else: - return np.NaN - - # Roofs & Ceilings - if row["Surface_Type"] == "Roof": - return 1 - if row["Surface_Type"] == "Ceiling": - return 3 - # Walls - if row["Surface_Type"] == "Wall": - if row["Outside_Boundary_Condition"] == "Surface": - return 5 - if row["Outside_Boundary_Condition"] == "Outdoors": - return 0 - return np.NaN - - -def label_surface(row): - """Takes a boundary and returns its corresponding umi-Category - - Args: - row: - """ - # Floors - if row["Surface_Type"] == "Floor": - if row["Outside_Boundary_Condition"] == "Surface": - return "Interior Floor" - if row["Outside_Boundary_Condition"] == "Ground": - return "Ground Floor" - if row["Outside_Boundary_Condition"] == "Outdoors": - return "Exterior Floor" - else: - return "Other" - - # Roofs & Ceilings - if row["Surface_Type"] == "Roof": - return "Roof" - if row["Surface_Type"] == "Ceiling": - return "Interior Floor" - # Walls - if row["Surface_Type"] == "Wall": - if row["Outside_Boundary_Condition"] == "Surface": - return "Partition" - if row["Outside_Boundary_Condition"] == "Outdoors": - return "Facade" - return "Other" - - -def layer_composition(row): - """Takes in a series with $id and thickness values and return an array of - dict of the form {'Material': {'$ref': ref}, 'thickness': thickness} If - thickness is 'nan', it returns None. - - Returns (list): List of dicts - - Args: - row (pandas.Series): a row - """ - array = [] - ref = row["$id", "Outside_Layer"] - thickness = row["Thickness", "Outside_Layer"] - if np.isnan(ref): - pass - else: - array.append({"Material": {"$ref": str(int(ref))}, "Thickness": thickness}) - for i in range(2, len(row["$id"]) + 1): - ref = row["$id", "Layer_{}".format(i)] - if np.isnan(ref): - pass - else: - thickness = row["Thickness", "Layer_{}".format(i)] - array.append( - {"Material": {"$ref": str(int(ref))}, "Thickness": thickness} - ) - return array - - -def schedule_composition(row): - """Takes in a series with $id and \*_ScheduleDay_Name values and return an - array of dict of the form {'$ref': ref} - - Args: - row (pandas.Series): a row - - Returns: - list: list of dicts - """ - # Assumes 7 days - day_schedules = [] - days = [ - "Monday_ScheduleDay_Name", - "Tuesday_ScheduleDay_Name", - "Wednesday_ScheduleDay_Name", - "Thursday_ScheduleDay_Name", - "Friday_ScheduleDay_Name", - "Saturday_ScheduleDay_Name", - "Sunday_ScheduleDay_Name", - ] # With weekends last (as defined in - # umi-template) - # Let's start with the `Outside_Layer` - for day in days: - try: - ref = row["$id", day] - except: - pass - else: - day_schedules.append({"$ref": str(int(ref))}) - return day_schedules - - -def year_composition(row): - """Takes in a series with $id and ScheduleWeek_Name_{} values and return an - array of dict of the form {'FromDay': fromday, 'FromMonth': frommonth, - 'Schedule': {'$ref': int( ref)}, 'ToDay': today, 'ToMonth': tomonth} - - Args: - row (pandas.Series): a row - - Returns: - list: list of dicts - """ - parts = [] - for i in range(1, 26 + 1): - try: - ref = row["$id", "ScheduleWeek_Name_{}".format(i)] - except: - pass - else: - if ~np.isnan(ref): - fromday = row["Schedules", "Start_Day_{}".format(i)] - frommonth = row["Schedules", "Start_Month_{}".format(i)] - today = row["Schedules", "End_Day_{}".format(i)] - tomonth = row["Schedules", "End_Month_{}".format(i)] - - parts.append( - { - "FromDay": fromday, - "FromMonth": frommonth, - "Schedule": {"$ref": str(int(ref))}, - "ToDay": today, - "ToMonth": tomonth, - } - ) - return parts - - def date_transform(date_str): """Simple function transforming one-based hours (1->24) into zero-based hours (0->23) @@ -790,23 +582,6 @@ def write_lines(file_path, lines): temp_idf_file.close() -def load_umi_template(json_template): - """ - Args: - json_template: Absolute or relative filepath to an umi json_template - - Returns: - pandas.DataFrame: 17 DataFrames, one for each component groups - """ - if os.path.isfile(json_template): - with open(json_template) as f: - dicts = json.load(f, object_pairs_hook=OrderedDict) - - return [{key: json_normalize(value)} for key, value in dicts.items()] - else: - raise ValueError("File {} does not exist".format(json_template)) - - def check_unique_name(first_letters, count, name, unique_list, suffix=False): """Making sure new_name does not already exist @@ -983,20 +758,6 @@ def lcm(x, y): return lcm -def reduce(function, iterable, **attr): - """ - Args: - function: - iterable: - **attr: - """ - it = iter(iterable) - value = next(it) - for element in it: - value = function(value, element, **attr) - return value - - def _unpack_tuple(x): """Unpacks one-element tuples for use as return values