human
I am working on the file "Notebooks/Make_Transects_interactive.ipynb".
The first task is:
Define class to allow interactive plotting
The class DrawLine allows the reader to select a transect and will then interpolate the solution from the specified event to this transect.
We first define a function topo_func that allows us to evaluate the topography at any point (x,y).
The function plot_transect is then defined to take two points (x1,y1) and (x2,y2) and interpolate the topography onto a set of 1000 equally spaced points along the transect (straight line connecting the points).  The function also takes another argument, a z_func function that can also be evaluated at any point and is assumed to return a value of $\zeta$ at this point.  This might be defined to be the zeta for a particular single event, or it might be the zeta coming from a probabilistic analysis at some particular probability p.
Can you write Python code for it?
 ... Write me a the Python code you requested?
assistant
#Here is the Python code you requested.

from scipy.interpolate import RegularGridInterpolator
topo_func = RegularGridInterpolator((X[:,0], Y[0,:]), topo)

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec

class DrawLine:
    def __init__(self, line,zeta,topo):
        self.line = line
        self.figure = line[0].figure
        self.xprev = 0
        self.yprev = 0
        self.xnew = 0
        self.ynew = 0
        self.press = None
        self.zeta = zeta
        self.topo = topo

    def connect(self):
        'connect to all the events we need'
        self.cidpress = self.figure.canvas.mpl_connect(
            'button_press_event', self.on_press)
        self.cidrelease = self.figure.canvas.mpl_connect(
            'button_release_event', self.on_release)

    def on_press(self, event):
        self.xprev = event.xdata
        self.yprev = event.ydata
        self.press = 1
        ax1.plot(self.xprev,self.yprev,'ro')
        self.figure.canvas.draw()
        #self.line[0].set_data([[event.xdata],[event.ydata]])
        #self.line[0].set_xdata = np.array([event.xdata, self.line[0].get_xdata()[1]])
        #self.line[0].set_ydata = np.array([event.ydata, self.line[0].get_ydata()[1]])

    def on_release(self, event):
        self.press = None
        self.xnew = event.xdata
        self.ynew = event.ydata
        #print('+++ xnew, ynew: ', xnew,ynew)
        #self.line[0].set_xdata = np.array([self.line[0].get_xdata()[0]], event.xdata)
        #self.line[0].set_ydata = np.array([self.line[0].get_ydata()[0]], event.ydata)
        ax1.cla()
        
        topo_clines = arange(0,20,2)
        ax1.contour(X,Y,topo,topo_clines,colors='k')
        CClatitude = 41.75  # to rescale longitude
        ax1.set_aspect(1. / cos(pi*CClatitude/180.)) 
        ax1.ticklabel_format(format='plain',useOffset=False)
    
        ax1.plot(self.xprev,self.yprev,'ro')
        ax1.plot([self.xprev,self.xnew],[self.yprev,self.ynew],'-r',lw=3)
        #ax1.set_xlim(-5,5)
        #ax1.set_ylim(-5,5)
        
       ...