import numpy as np
from matplotlib import pyplot as plt

def plotEntries(entries,keyX,keyY,sortingKey,graphName,colors = None,markers = None):
    #assert len(keysX) == len(colors) and len(keysX) == len(markers)

    technologies = list(set([el[sortingKey] for el in entries]))


    for i,tech in enumerate(technologies):
        x = [el[keyX] for el in entries if el[sortingKey] == tech]
        y = [el[keyY] for el in entries if el[sortingKey] == tech]
        plt.scatter(x,y)
        print(tech)
        if i == 5:
            break
    plt.title(keyX + " vs " + keyY)
    plt.xlabel(keyX)
    plt.ylabel("test")

    plt.savefig(graphName + ".png")
if __name__ == "__main__":
    fileName = "dataSheet.csv"

    # Opening file
    with open(fileName,"r") as f:
        data = f.readlines()
    delimiter = "|"
    entryLength = 30

    # Some constants
    header = data[0][:-1]
    headers = header.split(delimiter)

    entries = []
    # Dank parsing
    for dataIt in range(1,len(data)):
        line = data[dataIt][:-1]
        values = line.split(delimiter)
        if len(values) != entryLength:
            continue
        entry = dict()
        for val,key in zip(values,headers):
            entry[key] = val
        entries.append(entry)
    # Dank filtering
    frequence  = 1e9
    entries = [el for el in entries if float(el["fs [Hz]"]) >= frequence]

    plotEntries(entries,"fs [Hz]","P [W]","TECHNOLOGY","test",None,None)