Get 4 points.
Your score is MATH_SCORE + GUI_SCORE - ABS(MATH_SCORE-GUI_SCORE)/2

MATH
- Add a sin wave curve to the app, complete with item in menu bar to 
  activate it.
- Show the pierson's coeffecient betweeen the X and Y data.
- Have a menu item so the user can log scale the data and then fit.
- Fix my bug.  Use a data file who's X's dont start at zero to see.
- (3x) When you load the data, have it programatically figure out the best fit, 
  and start with that as the default fit.
- (2x) Highlight the biggest outlier point (the point that is farthest from the 
  fit curve.

GUI
- (2x) Add a save menu item, that saves the current name of the loaded file and the
  current fit type.  Be able to load you save file type.
- Set the title of the graph from user input.
- Turn on grid lines
- Set the X and Y axis labels from user input.
- Have a toggle so it can show all the fits at once.
- Change the app name (main window name) to reflect the current fata file.
- Have a menu of colors .. change the color of the graph.





import sys
from PyQt5.QtWidgets import *
from PyQt5.QtGui import *
import numpy as np
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
import matplotlib.pyplot as plt
from lmfit import  Model

class App(QMainWindow):
    def __init__(self):
        super().__init__()
        self.left = 100
        self.top = 100
        self.title = 'PyQt5 matplotlib example - pythonspot.com'
        self.width = 640
        self.height = 400

        menubar = self.menuBar()

        loadAct = QAction(QIcon('exit24.png'), 'Load', self)
        loadAct.setShortcut('Ctrl+L')
        loadAct.triggered.connect(self.load)
        menubar.addAction(loadAct)

        fitAct = QAction(QIcon('exit24.png'), 'Line', self)
        fitAct.triggered.connect(lambda : self.fit(2))
        menubar.addAction(fitAct)

        fitAct = QAction(QIcon('exit24.png'), ' Gauss', self)
        fitAct.triggered.connect(lambda: self.fit(1))
        menubar.addAction(fitAct)

        fitAct = QAction(QIcon('exit24.png'), ' Poly3', self)
        fitAct.triggered.connect(lambda: self.fit(3))
        menubar.addAction(fitAct)

        self.setWindowTitle(self.title)
        self.setGeometry(self.left, self.top, self.width, self.height)
        self.show()

    def load(self):
        print("start")
        options = QFileDialog.Options()
        options |= QFileDialog.DontUseNativeDialog
        self.fileName, _ = QFileDialog.getOpenFileName(self, "QFileDialog.getOpenFileName()", "",
                                                  "All Files (*);;Text Files (*.txt)", options=options)
        if self.fileName:
            self.data = np.genfromtxt(self.fileName, delimiter=",")
            print(self.data)
            self.fit()

    def fit(self, type=1):
            self.plot = PlotCanvas(parent=self, data=self.data, type=type)
            self.setCentralWidget(self.plot)
            self.show()

class PlotCanvas(FigureCanvas):
    def __init__(self, data=None, type=1, parent=None,width=5, height=4, dpi=100):
        fig = Figure(figsize=(width, height), dpi=dpi)

        FigureCanvas.__init__(self, fig)
        self.setParent(parent)
        FigureCanvas.setSizePolicy(self,QSizePolicy.Expanding,QSizePolicy.Expanding)
        FigureCanvas.updateGeometry(self)
        print("About to make funcs")
        if type==1:
            def func(x, p1,p2,p3):
                "1-d gaussian: gaussian(x, amp, cen, wid)"
                return (p1 / (np.sqrt(2 * np.pi) * p2)) * np.exp(-(x - p3) ** 2 / (2 * p2 ** 2))
        elif type==2:
            def func(x,p1,p2,p3):
                "Straight line"
                return p1*x+p2
        else:
            def func(x,p1,p2,p3):
                "poly"
                return p1*x*x + p2*x + p3

        print("after making gauss")
        print(data)
        x = data[:, 0]
        y = data[:, 1]
        print(x)
        gmodel = Model(func)
        result = gmodel.fit(y, x=x, p1=1, p2=1, p3=1)
        print(result.best_fit)
        ax = self.figure.add_subplot(111)
        ax.plot(data[:,0],data[:,1],'o')
        ax.plot(result.best_fit,"r")
        self.draw()

if __name__ == '__main__':
    app = QApplication(sys.argv)
    ex = App()
    sys.exit(app.exec_())