Campfireman/temperature_pred

1import gradio as gr2import hopsworks3import joblib4import pandas as pd5import numpy as np6import folium7import sklearn.preprocessing as proc8import json9import time10from datetime import timedelta, datetime11from branca.element import Figure12 13from functions import decode_features, get_weather_data, get_weather_df, get_weather_json_quick14##################15 16def greet(total_pred_days):    17    str1 = ""18    19    if(total_pred_days == ""):20        return "Empty input"21    22    count = int(total_pred_days) 23    if count > 14:24        str1 += "Warning: 14 days at most. " + '\n'25        count = 1426    if count <0:27        str1 = "Invalid input."28        return str129    count = count + 130    31    X = pd.DataFrame()32    33    for i in range(count+1):34        # Get, rename column and rescale35        next_day_date = datetime.today() + timedelta(days=i)36        next_day = next_day_date.strftime ('%Y-%m-%d')37        json = get_weather_json_quick(next_day)38        temp = get_weather_data(json)39        X = X.append(temp, ignore_index=True)40    41    42    # X reshape43    44    X.drop('preciptype', inplace = True, axis = 1)45    X.drop('severerisk', inplace = True, axis = 1)46    X.drop('stations', inplace = True, axis = 1)47    X.drop('sunrise', inplace = True, axis = 1)48    X.drop('sunset', inplace = True, axis = 1)49    X.drop('moonphase', inplace = True, axis = 1)50    X.drop('description', inplace = True, axis = 1)51    X.drop('icon', inplace = True, axis = 1)52    X = X.drop(columns=["sunriseEpoch", "sunsetEpoch", "source", "datetimeEpoch"]).fillna(0) 53    X = X.rename(columns={'pressure':'sealevelpressure'})54    55    # Merge X and query56    #Y = X.append(Q, ignore_index=True)57    58    # Data scaling59    X = X.drop(columns = ['conditions', "datetime", "temp", "tempmax", "tempmin"])60    category_cols = ['conditions']61    cat_std_cols = ['feelslikemax','feelslikemin','feelslike','dew','humidity','precip','precipprob','precipcover','snow','snowdepth','windgust','windspeed','winddir','sealevelpressure','cloudcover','visibility','solarradiation','solarenergy','uvindex']62    scaler_std = proc.StandardScaler()63    X.insert(19,"conditions",0)64    X.insert(0,"name",0)65    66    X[cat_std_cols] = scaler_std.fit_transform(X[cat_std_cols])67    X[category_cols] = scaler_std.fit_transform(X[category_cols])68    69    # Predict70    preds = model.predict(X[0:count])71    preds1= model1.predict(X[0:count])72    preds2= model2.predict(X[0:count])73    74    for x in range(count):75        if (x != 0):76            str1 += (datetime.now() + timedelta(days=x)).strftime('%Y-%m-%d') + " predicted temperature: " +str(float(preds[len(preds) - count + x]))+ "\npredicted max temperature: " +str(float(preds1[len(preds1) - count + x]))+ "\npredicted min temperature: " +str(float(preds2[len(preds2) - count + x]))+"\n"77    78    return str179 80#######################################################81# Preparations82project = hopsworks.login()83mr=project.get_model_registry()84 85# fs = project.get_feature_store()86# weather_fg = fs.get_or_create_feature_group(87#     name = 'weather_fg',88#     version = 189# )90# 91# query = weather_fg.select_all()92# Q = query.read()93 94model = mr.get_model("temp_model_new", version=1)95model_dir=model.download()96 97model1 = mr.get_model("tempmax_model_new", version=1) 98model_dir1=model1.download()99 100model2 = mr.get_model("tempmin_model_new", version=1)101model_dir2=model2.download()102 103model = joblib.load(model_dir + "/model_temp_new.pkl")104model1 = joblib.load(model_dir1 + "/model_tempmax_new.pkl")105model2 = joblib.load(model_dir2+ "/model_tempmin_new.pkl")106 107 108########################################################109# Gradio Interface110#demo = gr.Interface(fn=greet, inputs = "text", outputs="text")111 112with gr.Blocks() as demo:113    with gr.Row():114        with gr.Column():115            days = gr.Slider(116                label="How many days do you want to predict the temperature of? ", value=1, minimum=1, maximum=15, step=1117            )118        with gr.Column():119            output = gr.Textbox(120                label="Predicted results: "121            )122        days.change(greet, days, output)123        124    125if __name__ == "__main__":126    demo.launch()127