Race day predictor based on training run data using Python.
High level design:
- Collect running data, for starters - distance + time ran + splits (time per mile)
- Grade the splits. 0 value for first split, then increasing + or - value the more splits there are
- Store race day distance
- Calculate simulated race day performance using split grade curve average applied to race day distance
- Collect running data
Input 1 training session: distance + time
def session(distance, time, splits):
distance = input("Add distance")
time = input("Add time taken")
splits = []
for i in range(0, distance):
split = split[i]
split = input(f"Add split for {i} mile")
splits.append(split[i])
session = {distance, time, splits[i]}
return session
# need to store this into a database as an entry
def time_convert(time):
# need to convert time into a standard metric based on input hours/minutes
def distance_conversion(distance):
# need to convert miles to KM based on input of mileage- grade the splits
def grade_splits(splits):
counter = 0
# this method grades values given
# index and split given by grade_split
for i in range(0, len(splits)):
split = split[i]
if i <= 2:
if split[i + 1] <= split[i]:
counter += 1
else:
counter -= 1
if i >= 3 and i <=6:
if split[i + 1] <= split[i]:
counter += 2
else:
counter -= 2
if i >= 7:
if split[i + 1] <= split[i]:
counter += 3
else:
counter -= 3
return counter
def process_splits(splits, counter):
graded_splits = []
final_grade = 0
"""
here i need to take the splits and index them into a tuple {index, split_time, grade}
then, i need to assign a +/- value based on the split index, which compares itself to the previous split
then calculate and return the grade total
"""
for index, split in enumerate(splits):
# index, time, run grade_splits(splits)
# calculate and return grade total
graded_splits.append(index, split, counter)
for grade[2] in graded_splits:
final_grade += grade[2]
return final_grade- store race day distance
def race(distance):
return race_distance = input("enter race distance")- calculate race day performance
def split_average(sessions):
for session in sessions:
# add up and average all the splits
return split_average
def distance_average(sessions):
for session in sessions:
# add up and then average all the distances
return distance_average
def simulator(race_distance, final_grade, distance_average, split_average):
# so if i have the full race distance, i.e. 10 miles
# and i have the grade. i need to do a few things
### compare distance average for training to race distance
### assign percentage
### take final grade score and multiply by percentage = race_diff
### use split average as starting split, then add race_diff exponentially to each split needed to
# complete race distance
class Race():
def simulator():
def race():
class Training(Race):
def session():
class Splits(Training):
def grade_splits():
def process_splits():
def split_average():