def main_case_count_calculations(self):
"""This method calculates the entire Case Count KPIs set."""
if self.filtered_mdis.empty or self.filtered_scif.empty:
return
try:
self._prepare_data_for_calculation()
total_facings_per_brand_res = self._calculate_total_bottler_and_carton_facings(
)
self._save_results_to_db(total_facings_per_brand_res,
Ccc.TOTAL_FACINGS_KPI)
cases_per_brand_res = self._count_number_of_cases()
self._save_results_to_db(cases_per_brand_res, Ccc.CASE_COUNT_KPI)
unshoppable_brands_lst = self._non_shoppable_case_kpi()
self._save_results_to_db(unshoppable_brands_lst,
Ccc.NON_SHOPPABLE_CASES_KPI)
implied_shoppable_cases_kpi_res = self._implied_shoppable_cases_kpi(
)
self._save_results_to_db(implied_shoppable_cases_kpi_res,
Ccc.IMPLIED_SHOPPABLE_CASES_KPI)
total_cases_res = self._calculate_and_total_cases(
cases_per_brand_res + implied_shoppable_cases_kpi_res)
self._save_results_to_db(total_cases_res,
Ccc.TOTAL_CASES_KPI,
should_enter=False)
except Exception as err:
Log.error(
"DiageoUS Case Count calculation failed due to the following error: {}"
.format(err))
def main_case_count_calculations(self):
"""This method calculates the entire Case Count KPIs set."""
if not (self.filtered_scif.empty or self.matches.empty):
try:
if not self.filtered_mdis.empty:
self._prepare_data_for_calculation()
self._generate_adj_graphs()
facings_res = self._calculate_display_size_facings()
sku_cases_res = self._count_number_of_cases()
unshoppable_cases_res = self._non_shoppable_case_kpi()
implied_cases_res = self._implied_shoppable_cases_kpi()
else:
facings_res = self._calculate_display_size_facings()
sku_cases_res = self._count_number_of_cases()
unshoppable_cases_res = []
implied_cases_res = []
sku_cases_res = self._remove_nonshoppable_cases_from_shoppable_cases(
sku_cases_res, unshoppable_cases_res)
total_res = self._calculate_total_cases(sku_cases_res +
implied_cases_res +
unshoppable_cases_res)
placeholder_res = self._generate_placeholder_results(
facings_res, sku_cases_res, unshoppable_cases_res,
implied_cases_res)
self._save_results_to_db(facings_res + sku_cases_res +
unshoppable_cases_res +
implied_cases_res + total_res +
placeholder_res)
self._calculate_total_score_level_res(total_res)
except Exception as err:
Log.error(
"DiageoUS Case Count calculation failed due to the following error: {}"
.format(err))
def get_closest_point(origin_point, other_points_df):
"""This method gets a point (x & y coordinates) and checks what is the closet point the could be
found in the DataFrame that is being received.
@param: origin_point (tuple): coordinates of x and y
@param: other_points_df (DataFrame): A DF that has rect_x' and 'rect_y' columns
@return: A DataFrame with the closest points and the rest of the data
"""
other_points = other_points_df[['rect_x', 'rect_y']].values
# Euclidean geometry magic
distances = np.sum((other_points - origin_point) ** 2, axis=1)
# get the shortest hypotenuse
try:
closest_point = other_points[np.argmin(distances)]
except ValueError:
Log.error('Unable to find a matching opposite point for supplied anchor!')
return other_points_df
return other_points_df[
(other_points_df['rect_x'] == closest_point[0]) & (other_points_df['rect_y'] == closest_point[1])]