import csv, sys
from lib2to3.pgen2.pgen import DFAState
import plotly.express as px
import plotly.io as pio
import plotly.graph_objects as go
import numpy
import pandas
from scipy import signal

filename = 'example_data/TachymeterTable_103.csv'

# einfaches Beispiel: CSV direkt ausgeben:
#with open(filename, newline='') as f:
#    reader = csv.reader(f)
#    try:
#        for row in reader:
#            print(row)
#    except csv.Error as e:
#        sys.exit('file {}, line {}: {}'.format(filename, reader.line_num, e))

class Tachies(object):
    """This class contains lists of values created from csv rows"""
    def __init__(self):
        self.index = []
        self.Time = []
        self.x = []
        self.y = []
        self.z = []
        self.d = []
        self.deltaT = []
        self.SOG = []
        self.RelTime = []
        self.Beschleunigung = []
        self.BeschleunigungDeltaTFix = []
        self.ABSBeschleunigung = []

    def appendRow(self, i, row, header):
        aDict = dict(zip(header, row))
        self.index.append(i)
        self.Time.append(aDict["Time"])
        self.x.append(aDict["x"])
        self.y.append(aDict["y"])
        self.z.append(aDict["z"])
        self.d.append(aDict["d"])
        self.deltaT.append(aDict["deltaT"])
        self.SOG.append(float(aDict["SOG"]))
        self.RelTime.append(aDict["RelTime"])
        self.Beschleunigung.append(aDict["Beschleunigung"])
        self.BeschleunigungDeltaTFix.append(aDict["BeschleunigungDeltaTFix"])
        self.ABSBeschleunigung.append(aDict["ABSBeschleunigung"])


# Time,x,y,z,d,deltaT,SOG,RelTime,Beschleunigung,BeschleunigungDeltaTFix,ABSBeschleunigung
class Tachymeter(object):

    def __init__(self, i, Time, x, y, z, d, deltaT, SOG, RelTime, Beschleunigung, BeschleunigungDeltaTFix, ABSBeschleunigung):
        self.index = i
        self.Time = Time
        self.x = x
        self.y = y
        self.z = z
        self.d = d
        self.deltaT = deltaT
        self.SOG = SOG
        self.RelTime = RelTime
        self.Beschleunigung = Beschleunigung
        self.BeschleunigungDeltaTFix = BeschleunigungDeltaTFix
        self.ABSBeschleunigung = ABSBeschleunigung

    def __init__(self, row, header):
        self.__dict__ = dict(zip(header, row))
        self.index = row


data = list(csv.reader(open(filename, newline='')))

# Erzeugung einer Klasse Tachies und Hinzufügen aller Werte

t = Tachies()
i = 0
for d in data[1:]:
    t.appendRow(i, d, data[0])
    i+=1

# Erzeugung einer Liste von Klassen vom Typ Tachymeter
tachies = [Tachymeter(i, data[0]) for i in data[1:]]

# for tachy in tachies:
#     print(tachy.x)

#fig = dict({
#    "data": [{"type": "bar",
#              "x": [1, 2, 3],
#              "y": [1, 3, 2]}],
#    "layout": {"title": {"text": "A Figure Specified By Python Dictionary"}}
#})

# pio.show(fig)

# fig = px.line(x=t.index, y=t.SOG, title="SOG")

fig = go.Figure()
fig.add_trace(go.Scatter(x=t.index, y=t.SOG, mode='lines', name='SOG'))
fig.add_trace(go.Scatter(x=t.index, y=signal.savgol_filter(t.SOG, 53, 3), mode='lines', name='Smooth SOG'))
fig.write_html("smooth.html")
fig.show()

#df = dict( {
#    "x" : [ 1, 2, 3, 4, 5],
#    "y" : [0.4, 2.3, 2.4, 2.7, 1.3]
#})


#fig = go.Figure(go.Line(x = t.index, y = t.SOG, name='SOG'))
#fig.update_layout(title='Apple Share Prices over time (2014)',
#                   plot_bgcolor='rgb(230, 230,230)',
#                   showlegend=True)

#fig.show()