def monthly_daily_totals(dictionary, time_input, unit_input):
#for use with masterdict (get_data.my_filtered_activities())
#01.29.18
#takes in number for how many months ago. Ex 0 is current, 1 is last month
x_list = []
y_list = []
#filters out only dates needed
for key in list(dictionary):
if key < get_time.FOM(time_input): #if older than first of month
del dictionary[key]
for key in list(dictionary):
if key > get_time.LOM(time_input): #if newer than first of month
del dictionary[key]
calculation_day_count = (
get_time.LOM(time_input) -
get_time.FOM(time_input)).days #how many days in the month
calculation_day_range = list(
range(1, calculation_day_count +
2)) #range of 1 to the days in the month - calculation days
mile_count = 0
mile_count_list = [] #list of miles
day_count_list = [] #list of days miles occurred
for day in calculation_day_range: #ex 1-31
for activity in dictionary:
if activity.day == day: #if the day of the activity matches the day in the list
mile_count = mile_count + float(
dictionary[activity][unit_input])
mile_count_list.append(mile_count) #add mile count
day_count_list.append(activity.day) #add day that count occurs
return dict(zip(day_count_list, mile_count_list))
def graph_per_month_running(master_dict,choice_dict,unit_dict,days_total):
input1 = days_total
input2 = 'distance_miles'
graph_dict = {}
for choice in choice_dict:
graph_dict[choice] = calc.full_running_totals(master_dict.copy(),input1,input2) #duplicates data dictionary into number of months given
for date_range,choice in zip(graph_dict,choice_dict):
for key in list(graph_dict[date_range].keys()):
if key < get_time.FOM(choice_dict[choice]) or key > get_time.LOM(choice_dict[choice]): #
del graph_dict[date_range][key] #eliminates keys older or newer than specified for each month
y_list = []
for key in sorted(graph_dict[date_range].keys()):
y_list.append(graph_dict[date_range][key]) #gets y values
x_list = list(range(1,len(list(graph_dict[date_range].keys()))+1)) #calculates x values based on y values
plt.plot(x_list,y_list,label=(get_time.what_month(get_time.FOM(choice_dict[choice]).month)+" "+str(get_time.FOM(choice_dict[choice]).year)))
plt.style.use('dark_background')
plt.rcParams['lines.linewidth'] = 1
plt.ylim(ymin=0)
plt.title('Running Total - ' + str(input1) + ' days, Unit: ' + input2)
plt.legend()
plt.show()
return df
weeks_to_calculate = list(range(0, 14))
week_dict = {}
for week in weeks_to_calculate:
week_dict[week] = master_dict.copy(
) #make a master dict for each week to calculate
for week in week_dict:
for key in list(week_dict[week]): #for each key in each master dictionary
if key < get_time.FOM(week):
del week_dict[week][key]
for key in list(week_dict[week]):
if key > get_time.LOM(week):
del week_dict[week][key]
#Mileage
miles_dict = {}
pace_dict = {}
hr_dict = {}
ele_dict = {}
tred_dict = {}
count_dict = {}
for week in week_dict:
if week_dict[week]: #check to see if any activites exist in the given week
import numpy as np
from pprint import pprint
master_dict = get_data.my_filtered_activities() #grabs dictionary of strava information
input1 = 90 #Blue
input4 = 365 #Red
input2 = 'distance_miles'
input3 = 12 #months back to graph
graph_dict_1 = {}
graph_dict_1 = calc.full_running_totals(master_dict.copy(),input1,input2)
for key in list(graph_dict_1.keys()):
if key < get_time.FOM(input3):
del graph_dict_1[key]
graph_dict_2 = {}
graph_dict_2 = calc.full_running_totals(master_dict.copy(),input4,input2)
for key in list(graph_dict_2.keys()):
if key < get_time.FOM(input3):
del graph_dict_2[key]
fig, (ax1,ax3,ax4) = plt.subplots(nrows=3, figsize=(13,9)) #figsize sets window
#plots top plot with shared x but different scale Y
def graph_per_month_total(master_dict,choice_dict,unit_dict):
input2 = 'distance_miles'
graph_dict = {}
for choice in choice_dict:
graph_dict[choice] = calc.monthly_daily_totals(master_dict.copy(),choice_dict[choice],input2) #calculates monthly totals for number of months chosen
#returns dictionary of all computed values - keys eliminated in the monthly_daily_totals function
for date_range,choice in zip(graph_dict,choice_dict): #for each month, graph values. Choice dict used for labels
plt.plot(list(graph_dict[date_range].keys()),list(graph_dict[date_range].values()),label=(get_time.what_month(get_time.FOM(choice_dict[choice]).month)+" "+str(get_time.FOM(choice_dict[choice]).year)))
plt.style.use('dark_background')
plt.rcParams['lines.linewidth'] = 1
plt.ylim(ymin=0)
plt.title('Monthly Totals - '+' Unit: ' + input2)
plt.legend()
plt.show()
def graph(master_dict,unit):
#elapsed_time, distance_miles, average_speed, kudos_count, max_heartrate, average_heartrate, max_speed, pace_dec, total_elevation_gain,
#athlete_count, average_temp, achivement_count
input1 = 7
input2 = 'distance_miles'
x_list = []
y_list = []
x2_list = []
y2_list = []
x3_list = []
y3_list = []
x4_list = []
y4_list = []
graph_dict = calc.full_running_totals(master_dict,input1,input2)
graph_dict1 = graph_dict.copy()
graph_dict2 = graph_dict.copy()
graph_dict3 = graph_dict.copy()
graph_dict4 = graph_dict.copy()
for key in list(graph_dict1):
if key < get_time.FOM(0):
del graph_dict1[key]
for key in list(graph_dict1):
if key > get_time.LOM(0):
del graph_dict1[key]
for key in sorted(graph_dict1.keys()):
x_list.append(key)
y_list.append(graph_dict1[key])
len_x = len(x_list)
x_list2 = range(len_x)
for key in list(graph_dict2):
if key < get_time.FOM(1):
del graph_dict2[key]
for key in list(graph_dict2):
if key > get_time.LOM(1):
del graph_dict2[key]
for key in sorted(graph_dict2.keys()):
x2_list.append(key)
y2_list.append(graph_dict2[key])
len_x2 = len(x2_list)
x2_list2 = range(len_x2)
for key in list(graph_dict3):
if key < get_time.FOM(2):
del graph_dict3[key]
for key in list(graph_dict3):
if key > get_time.LOM(2):
del graph_dict3[key]
for key in sorted(graph_dict3.keys()):
x3_list.append(key)
y3_list.append(graph_dict3[key])
len_x3 = len(x3_list)
x3_list2 = range(len_x3)
for key in list(graph_dict4):
if key < get_time.FOM(3):
del graph_dict4[key]
for key in list(graph_dict4):
if key > get_time.LOM(3):
del graph_dict4[key]
for key in sorted(graph_dict4.keys()):
x4_list.append(key)
y4_list.append(graph_dict4[key])
len_x4 = len(x4_list)
x4_list2 = range(len_x4)
plt.style.use('dark_background')
#plt.axis('off')
plt.rcParams['lines.linewidth'] = 1
plt.plot(x_list2,y_list, color='red')
plt.plot(x2_list2,y2_list, color='blue')
plt.plot(x3_list2,y3_list, color='green')
plt.plot(x4_list2,y4_list, color='yellow')
plt.ylim(ymin=0)
plt.title('Previous 4 Months - ' + str(input1) + ' days total, Unit: ' + input2)
#print(plt.style.available)
plt.legend([get_time.what_month(get_time.FOM(0).month), get_time.what_month(get_time.FOM(1).month), get_time.what_month(get_time.FOM(2).month), get_time.what_month(get_time.FOM(3).month)], loc='best')
plt.show()
plt.plot(x_list,y_list,label=(get_time.what_month(get_time.FOM(choice_dict[choice]).month)+" "+str(get_time.FOM(choice_dict[choice]).year)))
plt.style.use('dark_background')
plt.rcParams['lines.linewidth'] = 1
plt.ylim(ymin=0)
plt.title('Running Total - ' + str(input1) + ' days, Unit: ' + input2)
plt.legend()
plt.show()
unit_dict = {1:'distance_miles', 2:'elapsed_time', 3:'average_speed', 4:'kudos_count', 5:'max_heartrate', 6:'average_heartrate', 7:'max_speed', 8:'pace_dec', 9:'total_elevation_gain', \
10:'athlete_count', 11:'average_temp', 12:'achivement_count'}
list1 = list(range(0,30)) #past 15 months
list2 = []
for x in list1:
list2.append(str(get_time.what_month(get_time.FOM(x).month)) +" "+str(get_time.FOM(x).year)) #generates month and years
for x,y in zip(list1,list2):
print(str(x)+" - "+str(y)) #prints out nice list
q2 = int(input("Running Graph or Total? \n 1 - Total \n 2 - Running \n"))
q1 = int(input("How many months would you like to graph? "))
#for option in unit_dict:
#print(str(option)+" - "+unit_dict[option])
choice_dict = {}
full_choice_dict = {1:0,2:1,3:2,4:3,5:4,6:5,7:6,8:7,9:8,10:9,11:10,12:11,13:12,14:13,15:14}
chosen_unit_dict = {}
if q1 == 15:
if q2 == 1: #total choice
input1 = 365 #Blue
input2 = 90 #Red
input3 = 30 #
input4 = 8 #
input5 = 7
input6 = 1
months_back = 15
graph_dict_1 = {}
graph_dict_1 = calc.full_running_totals(master_dict.copy(), input1,
'distance_miles')
for key in list(graph_dict_1.keys()):
if key < get_time.FOM(months_back):
del graph_dict_1[key]
#
graph_dict_2 = {}
graph_dict_2 = calc.full_running_totals(master_dict.copy(), input2,
'distance_miles')
for key in list(graph_dict_2.keys()):
if key < get_time.FOM(months_back):
del graph_dict_2[key]
#
graph_dict_3 = {}
graph_dict_3 = calc.full_running_totals(master_dict.copy(), input3,
'distance_miles')
def running_totals():
input1 = 365 #Blue
input2 = 90 #Red
input3 = 30 #
input4 = 8 #
input5 = 7
input6 = 1
months_back = 15
graph_dict_1 = {}
graph_dict_1 = calc.full_running_totals(master_dict.copy(), input1,
'distance_miles')
for key in list(graph_dict_1.keys()):
if key < get_time.FOM(months_back):
del graph_dict_1[key]
#
graph_dict_2 = {}
graph_dict_2 = calc.full_running_totals(master_dict.copy(), input2,
'distance_miles')
for key in list(graph_dict_2.keys()):
if key < get_time.FOM(months_back):
del graph_dict_2[key]
#
graph_dict_3 = {}
graph_dict_3 = calc.full_running_totals(master_dict.copy(), input3,
'distance_miles')
for key in list(graph_dict_3.keys()):
if key < get_time.FOM(months_back):
del graph_dict_3[key]
#
graph_dict_4 = {}
graph_dict_4 = calc.full_running_totals(master_dict.copy(), input4,
'distance_miles')
for key in list(graph_dict_4.keys()):
if key < get_time.FOM(months_back):
del graph_dict_4[key]
#
graph_dict_5 = {}
graph_dict_5 = calc.full_running_totals(master_dict.copy(), input5,
'distance_miles')
for key in list(graph_dict_5.keys()):
if key < get_time.FOM(months_back):
del graph_dict_5[key]
#
graph_dict_6 = {}
graph_dict_6 = calc.full_running_totals(master_dict.copy(), input6,
'distance_miles')
for key in list(graph_dict_6.keys()):
if key < get_time.FOM(months_back):
del graph_dict_6[key]
fig, (ax1, ax2, ax3, ax4, ax5,
ax6) = plt.subplots(nrows=6,
figsize=mass_figsize) #figsize sets window
ax1.plot(list(graph_dict_1.keys()), list(graph_dict_1.values()), 'red')
ax1.set_title(str(input1) + " Running Days Total")
ax1.grid(True)
ax2.plot(list(graph_dict_2.keys()), list(graph_dict_2.values()),
'blue') #set up third
ax2.set_title(str(input2) + " Running Days Total")
ax2.grid(True)
ax3.plot(list(graph_dict_3.keys()), list(graph_dict_3.values()),
'green') #set up fourth graph
ax3.set_title(str(input3) + " Running Days Total")
ax3.grid(True)
ax4.plot(list(graph_dict_4.keys()), list(graph_dict_4.values()),
'red') #set up fourth graph
ax4.set_title(str(input4) + " Running Days Total")
ax4.grid(True)
ax5.plot(list(graph_dict_5.keys()), list(graph_dict_5.values()),
'blue') #set up fourth graph
ax5.set_title(str(input5) + " Running Days Total")
ax5.grid(True)
ax6.plot(list(graph_dict_6.keys()), list(graph_dict_6.values()),
'green') #set up fourth graph
ax6.set_title(str(input6) + " Running Days Total")
ax6.grid(True)
fig.subplots_adjust(hspace=0.3)
fig.tight_layout()
append_image("Running_Totals", plt)
def monthly_compare():
weeks_to_calculate = list(range(0, 14))
week_dict = {}
for week in weeks_to_calculate:
week_dict[week] = master_dict.copy(
) #make a master dict for each week to calculate
for week in week_dict:
for key in list(
week_dict[week]): #for each key in each master dictionary
if key < get_time.FOM(week):
del week_dict[week][key]
for key in list(week_dict[week]):
if key > get_time.LOM(week):
del week_dict[week][key]
#Mileage
miles_dict = {}
pace_dict = {}
hr_dict = {}
ele_dict = {}
tred_dict = {}
count_dict = {}
for week in week_dict:
if week_dict[
week]: #check to see if any activites exist in the given week
mile_list = []
pace_list = []
hr_list = []
ele_list = []
tred_list = []
count_list = []
for activity in week_dict[week]:
count_list.append(1)
mile_list.append(
float(week_dict[week][activity]['distance_miles']))
pace_list.append(float(week_dict[week][activity]['pace_dec']))
if float(week_dict[week][activity]['average_heartrate']
) != 0: #don't cound the 0's in runs i manually enter
hr_list.append(
float(week_dict[week][activity]['average_heartrate']))
#print(week_dict[week][activity]['average_heartrate'])
if 'total_elevation_feet' in week_dict[week][activity]:
ele_list.append(
float(
week_dict[week][activity]['total_elevation_feet']))
ele_dict[get_time.FOM(week)] = sum(
ele_list) #/len(ele_list)
# else:
# ele_dict[get_time.FOM(week)] = 0
if 'treadmill_flagged' in week_dict[week][activity]:
if week_dict[week][activity]['treadmill_flagged'] == 'yes':
tred_list.append(1)
# else:
# tred_list.append(0)
hr_dict[get_time.FOM(week)] = sum(hr_list) / len(hr_list)
miles_dict[get_time.FOM(week)] = sum(mile_list)
pace_dict[get_time.FOM(week)] = sum(pace_list) / len(pace_list)
tred_dict[get_time.FOM(week)] = sum(tred_list)
count_dict[get_time.FOM(week)] = sum(count_list)
# else:
# miles_dict[get_time.FOM(week)] = 0
# pace_dict[get_time.FOM(week)] = 0
# hr_dict[get_time.FOM(week)] = 0
# count_dict[get_time.FOM(week)] = 0
x_list = []
y_list = []
for month in miles_dict:
x_list.append(month)
y_list.append(miles_dict[month])
x2_list = []
y2_list = []
for month in pace_dict:
x2_list.append(month)
y2_list.append(pace_dict[month])
x3_list = []
y3_list = []
for month in hr_dict:
x3_list.append(month)
y3_list.append(hr_dict[month])
x4_list = []
y4_list = []
for month in ele_dict:
x4_list.append(month)
y4_list.append(ele_dict[month])
x5_list = []
y5_list = []
for month in tred_dict:
x5_list.append(month)
y5_list.append(tred_dict[month])
x6_list = []
y6_list = []
for month in count_dict:
x6_list.append(month)
y6_list.append(count_dict[month])
########
fig, (ax1, ax2, ax4,
ax5) = plt.subplots(nrows=4, figsize=(13, 8)) #figsize sets window
myFmt = mdates.DateFormatter('%m/%y')
ax1df = trend_line(x_list, y_list)
ax1.bar(x_list, y_list, align='center', width=25)
ax1slope = format_number(
float(ax1df['y_trend'].iloc[0]) - float(ax1df['y_trend'].iloc[-1]))
ax1.plot_date(ax1df.dates,
ax1df.y_trend,
'red',
ls='--',
marker='None',
label=ax1slope)
ax1.set_ylabel('Miles Ran', color='b')
ax1.set_yticks(range(int(max(y_list)) + 1), 3)
ax1.tick_params('y', colors='b')
ax1.yaxis.grid(True)
ax1.legend()
ax1.set_xticks(x_list)
labels = ax1.set_xticklabels(x_list)
for i, label in enumerate(labels):
label.set_y(label.get_position()[1] - (i % 2) * 0.09)
ax1.xaxis.set_major_formatter(myFmt)
ax2.plot(x2_list, y2_list, color='g', label='Pace', linewidth=2)
ax2.set_ylabel('Pace (Decimal)', color='g')
ax2.tick_params('y', colors='g')
ax2.yaxis.grid(True)
ax3 = ax2.twinx()
ax3.plot(x3_list, y3_list, color='r', label='Avg HR')
ax3.set_ylabel('Avg of Avg HR', color='r')
ax3.tick_params('y', colors='r')
ax2.set_xticks(x2_list)
labels = ax2.set_xticklabels(x2_list)
for i, label in enumerate(labels):
label.set_y(label.get_position()[1] - (i % 2) * 0.09)
ax2.xaxis.set_major_formatter(myFmt)
ax4.bar(x6_list,
y6_list,
align='center',
width=25,
color='b',
label='Outdoor') #total runs
ax4.bar(x5_list,
y5_list,
align='center',
width=25,
color='#fc5e02',
label='Treadmill') #treadmill runs
ax4.set_ylabel('Runs Per Week', color='b')
ax4.set_yticks(range(max(y6_list) + 1))
ax4.tick_params('y', colors='b')
ax4.yaxis.grid(True)
ax4.legend()
ax4.set_xticks(x5_list)
labels = ax4.set_xticklabels(x6_list)
for i, label in enumerate(labels):
label.set_y(label.get_position()[1] - (i % 2) * 0.09)
ax4.xaxis.set_major_formatter(myFmt)
ax5.plot(x4_list, y4_list, label='Total')
ax5.set_ylabel('Total Elevation (Feet)')
#ax5.set_yticks(range(int(max(y4_list)+1)),20)
ax5.yaxis.grid(True)
ax5.legend()
ax5.set_xticks(x4_list)
labels = ax5.set_xticklabels(x4_list)
for i, label in enumerate(labels):
label.set_y(label.get_position()[1] - (i % 2) * 0.09)
ax5.xaxis.set_major_formatter(myFmt)
plt.setp(ax1.get_xticklabels(), rotation=0, horizontalalignment='center')
plt.setp(ax2.get_xticklabels(), rotation=0, horizontalalignment='center')
plt.setp(ax4.get_xticklabels(), rotation=0, horizontalalignment='center')
plt.setp(ax5.get_xticklabels(), rotation=0, horizontalalignment='center')
fig.tight_layout()
fig.subplots_adjust(hspace=0.3)
append_image("Monthly_Compare", plt)
def main():
global button_2_status
button_2_status = "All"
my_dataset = dataset.copy()
global dict_time_dist
global dict_time_pace
dict_time_dist,dict_time_pace = calc.filter(my_dataset)
running_week_dict = calc.var_calc_loop_single(get_time.running_week(0),my_dataset)
this_week_dict = calc.var_calc_loop_single(get_time.LM(0),my_dataset)
last_week_dict = calc.var_calc_loop_double(get_time.LM(1),get_time.LS(0),my_dataset)
this_month_dict = calc.var_calc_loop_single(get_time.FOM(0),my_dataset)
last_month_dict = calc.var_calc_loop_double(get_time.FOM(1),get_time.LOM(1),my_dataset)
YTD_dict = calc.var_calc_loop_single(get_time.FOY(),my_dataset)
label1= v['label1']
label1.text = this_week_dict['miles']
label2= v['label2']
label2.text = this_week_dict['pace']
label3= v['label3']
label3.text = this_week_dict['count']
label4= v['label4']
label4.text = this_month_dict['miles']
label5= v['label5']
label5.text = this_month_dict['pace']
label6= v['label6']
label6.text = this_month_dict['count']
label7= v['label7']
label7.text = running_week_dict['miles']
label8= v['label8']
label8.text = running_week_dict['pace']
label9= v['label9']
label9.text = running_week_dict['count']
label11= v['label11']
label11.text = last_week_dict['miles']
label12= v['label12']
label12.text = last_week_dict['pace']
label13= v['label13']
label13.text = last_week_dict['count']
label14= v['label14']
label14.text = last_month_dict['miles']
label15= v['label15']
label15.text = last_month_dict['pace']
label16= v['label16']
label16.text = last_month_dict['count']
label17= v['label17']
label17.text = YTD_dict['miles']
label18= v['label18']
label18.text = YTD_dict['pace']
label19= v['label19']
label19.text = YTD_dict['count']
label81= v['label81']
label81.text = this_week_dict['date']
label82= v['label82']
label82.text = this_month_dict['date']
label82= v['label83']
label82.text = running_week_dict['date']
label83= v['label84']
label83.text = last_week_dict['date']
label84= v['label85']
label84.text = last_month_dict['date']
label85= v['label86']
label85.text = YTD_dict['date']
def button_action_1(sender):
if button1.selected_index == 0:
#red is 90, blue is 91 - current month is red past month is blue
v['label90'].text = "This Week"
v['label91'].text = "Last Week"
v['label92'].text = button_2_status
b = graph_dual_dictionary(calc.running_totals_single(dict_time_dist,button_3_status,get_time.LM(0)),calc.running_totals_double(dict_time_dist,button_3_status,get_time.LM(2),get_time.LS(1)))
v['imageview1'].image = ui.Image.from_data(b.getvalue())
if button1.selected_index == 1:
v['label90'].text ='This Month'
v['label91'].text ='Last Month'
v['label92'].text = button_2_status
b = graph_dual_dictionary(calc.running_totals_single(dict_time_dist,button_3_status,get_time.FOM(0)),calc.running_totals_double(dict_time_dist,button_3_status,get_time.FOM(1),get_time.LOM(1)))
v['imageview1'].image = ui.Image.from_data(b.getvalue())
elif button1.selected_index == 2:
v['label90'].text ='2017 To Date'
v['label91'].text =''
v['label92'].text = button_2_status
b = graph_single_dictionary(calc.running_totals_single(dict_time_dist,button_3_status,get_time.FOY()))
v['imageview1'].image = ui.Image.from_data(b.getvalue())