Python - module 'Cdt' has no attribute 'CDT'

Question

Hello, I am working with a code that uses two classes in two files: Radoncdt and CDT. The first one needs the second one. However, when trying to use one of the functions of the CDT class, I get the error:

module 'cdt' has no attribute 'CDT'

Follows the code of the classes:

import numpy as np
import cdt as CDT
from scipy import interp
from skimage.transform import radon, iradon

class RadonCDT:
    def __init__(self,theta=np.arange(180)):
        self.theta=theta

    def transform(self,I):
        """
        transform calculates calculates the Radon transform of the input image
        and calculate its CDT with respect to the Radon transform of the template
        input:
            I: A two-dimensional distribution
        output:
            The Radon-CDT transformation of I
        """
        assert not((1.0*I<0).sum())
        # Force I to be a positive probability distribution
        eps=1e-5#This small dc level is needed for a numerically unique solution of the transport map
        I=I+eps
        I=I/I.sum()
        radonI=radon(I,theta=self.theta,circle=False)
        self.dim=radonI.shape[0]
        Ihat=np.zeros_like(radonI)
        self.cdt=CDT.CDT(dim=self.dim)
        for i in range(len(self.theta)):
            Ihat[:,i]=self.cdt.transform(radonI[:,i])
        return Ihat

    def itransform(self,Ihat):
        """
        itransform calculates the inverse of the Radon-CDT. It receives the Radon-CDT
        and finds the corresponding two-dimensional distribution I from it.
        input:
            Ihat: Radon-CDT of I
        output:
            I: The original distribution
        """
        radonI=np.zeros_like(Ihat)
        for i in range(len(self.theta)):
            radonI[:,i]=self.cdt.itransform(Ihat[:,i])
        I=iradon(radonI,theta=self.theta,circle=False)
        return I

And the other class:

import numpy as np
from scipy import interp
    
class CDT:
    def __init__(self,dim):
        template=np.ones((dim,))
        template=template/template.sum()
        self.template=template
        self.dim=dim
        self.template_CDF=np.cumsum(template)
        self.x=np.arange(self.dim) #Discretization of the domain of template
        self.xtilde=np.linspace(0,1,self.dim)
        self.template_CDF_inverse=interp(self.xtilde,self.template_CDF,self.x)
    
    def transform(self,I):
        """
        transform calculates the transport map, f, that morphs the one-dimensional distribution
        I into the template.
        input:
            I: A one dimensional distributions of size self.dim
        output:
            The CDT transformation of I
        """
        assert self.dim==len(I)
        assert not((1.0*I<0).sum())
        # Force I to be a positive probability distribution
        eps=1e-5#This small dc level is needed for a numerically unique solution of the transport map
        I=I+eps
        I=I/I.sum()
        #Calculate its CDF
        I_CDF=np.cumsum(I)
        I_CDF_inverse = interp(self.xtilde,I_CDF, self.x)
        u = interp(self.x,self.template_CDF_inverse,self.template_CDF_inverse-I_CDF_inverse)
        Ihat= u*np.sqrt(self.template)
        return Ihat
    
    def itransform(self,Ihat):
        """
        itransform calculates the inverse of the CDT. It receives a signal in the CDT space
        and finds the corresponding one dimensional distribution I from it.
        input:
            u: Transport displacement map
            I0: The template used for calculating the CDT
        output:
            I: The original distribution
        """
        u=Ihat/np.sqrt(self.template)
        f=self.x-u
        fprime=np.gradient(f)
        I = interp(self.x,f, self.template/fprime)
        I = I/I.sum()
        return I

In the main code, my mistake happens here:

import transportBasedTransforms.radonCDT as RCDT

theta=np.arange(180)
rcdt=RCDT.RadonCDT(theta)
# Load images and calculate their Radon-CDT
I=[]
rI=[]
Ihat=[]
for i in range(2):
    I.append(rgb2gray(imread('./Data/I%d.bmp'%(i))))
    rI.append(radon(I[i],theta,circle=False))
    Ihat.append(rcdt.transform(I[i]))

I’ve tried to change the way I import, I’ve put them all in the same file, but I think it’s something else.