Daniel Ching danielcwq

## StravaToSheets.py
from oauth2client.service_account import ServiceAccountCredentials
import gspread
import pytz
from datetime import datetime
import requests
import json
import time
import os
from datetime import datetime

## trainingpace2.csv

          
            Intensity
            Time To Exhaustion
            Rate of Perceived Exertion

            
              Very Easy / Easy
               5+ Hours
              0-2

            
              Easy/Moderate -> Moderate
               3-4 Hours
              3-4

            
              Easy Tempo
               2 Hours (Long Run Pace)
              5

            
              Tempo(LT1)
               1 Hour / Marathon Pace (elites)
              6

            
              Threshold(LT2)
               40-50 minutes/ Half-marathon pace (elites)
              7

            
              Critical Velocity(CV)
               30-40 minutes
              7.5-8

            
              Aerobic Power
               5k Race Pace (<20 minutes)
               8-9

            
              VO2Max
               2.4k-3k Race Pace(5-8 minutes)
              9

            
              Anaerobic Endurance
               1.5k to Mile Race Pace (4-6 minutes)
               9.5

## trainingpaces.csv

          
            Intensity
            Ease of Talking
            Rate of Perceived Exertion

            
              Very Easy / Easy
               Sustained Conversation (without shortness of breath)
              0-2

            
              Easy/Moderate -> Moderate
               Sustained Conversation (interspersed with deep breathing)
              3-4

            
              Easy Tempo
               Few phrases/ strung out sentences
              5

            
              Tempo(LT1)
               Few words
              6

            
              Threshold(LT2)
               Few words
              7

            
              Critical Velocity(CV)
               Hard to talk
              7.5-8

            
              Aerobic Power
               Unable to talk
               8-9

            
              VO2Max
               Unable to talk
              9

            
              Anaerobic Endurance
              Unable to talk
               9.5

## exclude.py
df.drop(df.index[2447:2500], inplace = True)
df.drop(df.index[3054:3080], inplace = True)
df.drop(df.index[3080:3108], inplace = True)

## unzip.py
!kaggle datasets list -s ["Medical Transcriptions"]
!kaggle datasets download -d "tboyle10/medicaltranscriptions"
!unzip medicaltranscriptions.zip

## importfromkaggle.py
from google.colab import files
files.upload()
!pip install -q kaggle
# The Kaggle API client expects this file to be in ~/.kaggle,
# so move it there.
!mkdir -p ~/.kaggle
!cp kaggle.json ~/.kaggle/
# This permissions change avoids a warning on Kaggle tool startup.
!chmod 600 ~/.kaggle/kaggle.json

## formatted.py
x = dls.vocab
image = (path/'images/00000181_035.png') #some random image from the database
def match(raw, vocab):
    return [[vocab[0],(raw[0].item()*100)],[vocab[1],(raw[1].item()*100)],[vocab[2],(raw[2].item()*100)],[vocab[3],(raw[3].item()*100)],[vocab[4],(raw[4].item()*100)],[vocab[5],(raw[5].item()*100)],[vocab[6],(raw[6].item()*100)],[vocab[7],(raw[7].item()*100)],[vocab[8],(raw[8].item()*100)],[vocab[9],(raw[9].item()*100)],[vocab[10],(raw[10].item()*100)],[vocab[11],(raw[11].item()*100)],[vocab[12],(raw[12].item()*100)],[vocab[13],(raw[13].item()*100)],[vocab[14],(raw[14].item()*100)]]
def list_preds(img_path):
  prediction, indice, losses = learn.predict(img_path)
  arr = match(losses, x)
  return(arr)
list_preds(image)

## getxngety.py
def get_x(r): return path/'images'/r['Image Index']
def get_y(r): return r['Finding Labels'].split('|')

## initkaggle.py
from google.colab import files
files.upload()
!ls -lha kaggle.json
!pip install -q kaggle --upgrade
# The Kaggle API client expects this file to be in ~/.kaggle,
# so move it there.
!mkdir -p ~/.kaggle
!cp kaggle.json ~/.kaggle/

# This permissions change avoids a warning on Kaggle tool startup.

## valid.py
valid_x = torch.cat([valid_2_tens, valid_9_tens]).view(-1, 28*28)
valid_y = tensor([1]*len(valid_2_tens) +[0]*len(valid_9_tens)).unsqueeze(1)
valid_dset = list(zip(valid_x,valid_y))
	from oauth2client.service_account import ServiceAccountCredentials
	import gspread
	import pytz
	from datetime import datetime
	import requests
	import json
	import time
	import os
	from datetime import datetime
Intensity	Time To Exhaustion	Rate of Perceived Exertion
Very Easy / Easy	5+ Hours	0-2
Easy/Moderate -> Moderate	3-4 Hours	3-4
Easy Tempo	2 Hours (Long Run Pace)	5
Tempo(LT1)	1 Hour / Marathon Pace (elites)	6
Threshold(LT2)	40-50 minutes/ Half-marathon pace (elites)	7
Critical Velocity(CV)	30-40 minutes	7.5-8
Aerobic Power	5k Race Pace (<20 minutes)	8-9
VO2Max	2.4k-3k Race Pace(5-8 minutes)	9
Anaerobic Endurance	1.5k to Mile Race Pace (4-6 minutes)	9.5
Intensity	Ease of Talking	Rate of Perceived Exertion
Very Easy / Easy	Sustained Conversation (without shortness of breath)	0-2
Easy/Moderate -> Moderate	Sustained Conversation (interspersed with deep breathing)	3-4
Easy Tempo	Few phrases/ strung out sentences	5
Tempo(LT1)	Few words	6
Threshold(LT2)	Few words	7
Critical Velocity(CV)	Hard to talk	7.5-8
Aerobic Power	Unable to talk	8-9
VO2Max	Unable to talk	9
Anaerobic Endurance	Unable to talk	9.5
	df.drop(df.index[2447:2500], inplace = True)
	df.drop(df.index[3054:3080], inplace = True)
	df.drop(df.index[3080:3108], inplace = True)
	!kaggle datasets list -s ["Medical Transcriptions"]
	!kaggle datasets download -d "tboyle10/medicaltranscriptions"
	!unzip medicaltranscriptions.zip
	from google.colab import files
	files.upload()
	!pip install -q kaggle
	# The Kaggle API client expects this file to be in ~/.kaggle,
	# so move it there.
	!mkdir -p ~/.kaggle
	!cp kaggle.json ~/.kaggle/
	# This permissions change avoids a warning on Kaggle tool startup.
	!chmod 600 ~/.kaggle/kaggle.json
	x = dls.vocab
	image = (path/'images/00000181_035.png') #some random image from the database
	def match(raw, vocab):
	return [[vocab[0],(raw[0].item()100)],[vocab[1],(raw[1].item()100)],[vocab[2],(raw[2].item()100)],[vocab[3],(raw[3].item()100)],[vocab[4],(raw[4].item()100)],[vocab[5],(raw[5].item()100)],[vocab[6],(raw[6].item()100)],[vocab[7],(raw[7].item()100)],[vocab[8],(raw[8].item()100)],[vocab[9],(raw[9].item()100)],[vocab[10],(raw[10].item()100)],[vocab[11],(raw[11].item()100)],[vocab[12],(raw[12].item()100)],[vocab[13],(raw[13].item()100)],[vocab[14],(raw[14].item()*100)]]
	def list_preds(img_path):
	prediction, indice, losses = learn.predict(img_path)
	arr = match(losses, x)
	return(arr)
	list_preds(image)
	def get_x(r): return path/'images'/r['Image Index']
	def get_y(r): return r['Finding Labels'].split('\|')
	from google.colab import files
	files.upload()
	!ls -lha kaggle.json
	!pip install -q kaggle --upgrade
	# The Kaggle API client expects this file to be in ~/.kaggle,
	# so move it there.
	!mkdir -p ~/.kaggle
	!cp kaggle.json ~/.kaggle/

	# This permissions change avoids a warning on Kaggle tool startup.
	valid_x = torch.cat([valid_2_tens, valid_9_tens]).view(-1, 28*28)
	valid_y = tensor([1]len(valid_2_tens) +[0]len(valid_9_tens)).unsqueeze(1)
	valid_dset = list(zip(valid_x,valid_y))