Engineering-Internship-Goniometer/data_store.py at main · CairnCoder/Engineering-Internship-Goniometer · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
from os import makedirs, path
import json
import pandas as pd
from database_connection import DataBase
import pickle

def write_to_pickle(experiment_df: pd.DataFrame, background_df: pd.DataFrame, experiment_parameters: dict):
    # Make file folder
    name = experiment_parameters["Start_date"].replace(":","-").replace(" ","T")
    folderpath = path.join(path.dirname(path.abspath(__file__)), name)
    makedirs(folderpath, exist_ok=True)

    with open(path.join(folderpath, f'{name}.pkl'), 'wb') as file:
        pickle.dump((experiment_df, background_df, experiment_parameters), file)

    print('Saved to pickle')
    print()

def get_from_pickle(name):
    folderpath = path.join(path.dirname(path.abspath(__file__)), name)

    with open(path.join(folderpath, f'{name}.pkl'), 'wb') as file:
        experiment_df, background_df, experiment_parameters = pickle.load(file)
        print("Unpickled")
        print()
        return experiment_df, background_df, experiment_parameters

def write_to_folder(experiment_df: pd.DataFrame, background_df: pd.DataFrame, experiment_parameters: dict):
    # Make file folder
    foldername = experiment_parameters["Start_date"].replace(":","-").replace(" ","T")
    folderpath = path.join(path.dirname(path.abspath(__file__)), foldername)
    makedirs(folderpath, exist_ok=True)

    # Save experiment_parameters to file
    with open(path.join(folderpath, 'experiment_parameters.json'), 'w') as f:
        json.dump(experiment_parameters, f)
    print("Written experiment_parameters to json")

    # Save experiment_df to file
    experiment_df.to_csv(path.join(folderpath, 'angle_voltage.csv'), header=True, index=False)
    print("Written data to file")

    # Save background_df to file
    background_df.to_csv(path.join(folderpath, 'background.csv'), header=True, index=False)
    print("Written background to file")
    print()

def get_from_folder(foldername:str):
    folderpath = path.join(path.dirname(path.abspath(__file__)), foldername)
    try:
        experiment_df = pd.read_csv(path.join(folderpath, 'angle_voltage.csv'))
    except:
        experiment_df = None
    try:
        background_df = pd.read_csv(path.join(folderpath, 'background.csv'))
    except:
        background_df = None
    try:
        with open(path.join(folderpath, 'experiment_parameters.json'), 'r') as json_file:
            experiment_parameters = json.load(json_file)
    except:
        experiment_parameters = None

    print("Got data from database")
    print()
    return experiment_df, background_df, experiment_parameters


def write_to_database(experiment_df: pd.DataFrame, background_df: pd.DataFrame, experiment_parameters: dict, user:str):
    """experiment_df must have this format: Angle PD_Voltage LED_Current LED_Voltage"""

    metadata = {
        'MetaData': [experiment_parameters,],
        'Background': background_df
    }

    ## Save to database
    obj=DataBase()
    responce = obj.save(3,1001,metadata,experiment_df,user,'Goniometer')

    ## Show database responce
    if responce == False:
        print("Something went wrong saving to database.")
        raise Exception("Something went wrong saving to database.")
    print()


def get_from_database(metadata_filter:dict, is_and:bool = True, remove_database_info=True):
    # Get from database
    obj = DataBase()
    experiment_parameters_df, experiment_df, background_df = obj.get_goniometer(metadata_filter, is_and)

    # Remove database fields if desired
    if remove_database_info:
        experiment_parameters_df = experiment_parameters_df.drop(columns=['Tracker_Id',])
        columns_to_remove = ['DUT_Name', 'Pin', 'Tracker_Id']
        experiment_df = experiment_df.drop(columns=columns_to_remove)
        background_df = background_df.drop(columns=columns_to_remove)

    # Convert experiment_parameters from pd.dataframe to dict
    experiment_parameters = experiment_parameters_df.to_dict(orient='index')
    experiment_parameters = list(experiment_parameters.values())[0]

    print("Got data from database")
    print()

    return experiment_df, background_df, experiment_parameters