import os
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
from google.cloud.firestore_v1.base_query import FieldFilter
import pandas as pd
from datetime import datetime
import sys
import matplotlib.pyplot as plt
import numpy as np

cred = credentials.Certificate(os.getcwd() + '/' + 'keys/hpos-qa-firebase-adminsdk.json')
firebase_admin.initialize_app(cred)

db = firestore.client()

patient_collection = db.collection("patientData")
test_collection = db.collection("testData")
start_date = '2023-12-01' #sys.argv[1]
end_date = '2024-02-25' #sys.argv[2] 

query = test_collection.where(filter=FieldFilter("testTime", ">=", start_date)).where(filter=FieldFilter("testTime", "<", end_date))
docs = query.stream()

data = []
for doc in docs:
    doc_data = doc.to_dict()
    data.append(doc_data)

df = pd.DataFrame(data)
# print(df)
print(df.size)

import pandas as pd
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
from sklearn.preprocessing import StandardScaler

numeric_columns = ['led1Buffer', 'led3Average',
       'led3Sample', 'led4Average', 'calculatedRatio',
       'led4Sample', 'led2Sample', 'led3Buffer', 'deviceRatio',
       'led1Sample', 'led1Average', 'led4Buffer', 'led2Average',
       'led2Buffer']  #df.select_dtypes(include=[float, int]).columns
df_numeric = df[numeric_columns]#.dropna()
df_numeric.replace([np.inf, -np.inf], np.nan, inplace=True)
df_numeric.dropna(inplace=True)
print(df_numeric.corr())

if df_numeric.shape[0] > 0:
    scaler = StandardScaler()
    df_standardized = pd.DataFrame(scaler.fit_transform(df_numeric), columns=df_numeric.columns)

    tsne = TSNE(n_components=2, random_state=42)
    df_tsne = tsne.fit_transform(df_standardized)

    plt.scatter(df_tsne[:, 0], df_tsne[:, 1])
    plt.title("t-SNE Visualization")
    plt.xlabel("t-SNE Component 1")
    plt.ylabel("t-SNE Component 2")
    plt.show()
else:
    print("No samples found in the DataFrame after dropping NaN values.")

firebase_admin.delete_app(firebase_admin.get_app())