Update app.py

app.py

@@ -1,10 +1,57 @@
 
+import numpy as np
+import matplotlib.pylab as plt
+import ruptures as rpt
 import streamlit as st
+from ruptures.metrics import precision_recall
+from ruptures.metrics import hausdorff
+from ruptures.metrics import randindex
 
 
 st.title("Change Point Detection")
 # Generating Signal
 
+def pw_constant_input(n,dim,n_bkps,sigma):
+    """Piecewise constant (pw_constant)"""
+    # n, dim  # number of samples, dimension
+    # n_bkps, sigma # number of change points, noise standard deviation
+    signal, bkps = rpt.pw_constant(n, dim, n_bkps, noise_std=sigma)
+    rpt.display(signal, bkps)
+    return signal,bkps
+
+def pw_linear_input(n,dim,n_bkps,sigma):
+    """Piecewise Linear"""
+    # creation of data
+    # n, dim = 500, 3  # number of samples, dimension of the covariates
+    # n_bkps, sigma = 3, 5  # number of change points, noise standart deviation
+    signal, bkps = rpt.pw_linear(n, dim, n_bkps, noise_std=sigma)
+    rpt.display(signal, bkps)
+    return signal,bkps
+
+def pw_normal_input(n,dim,n_bkps,sigma):
+    """Piecewise 2D Gaussian process (pw_normal)#"""
+    # creation of data
+    #n = 500  # number of samples
+    #n_bkps = 3  # number of change points
+    signal, bkps = rpt.pw_normal(n, n_bkps)
+    rpt.display(signal, bkps)
+    return signal,bkps
+
+def pw_wavy_input(n,dim,n_bkps,sigma):
+    # creation of data
+    #n, dim = 500, 3  # number of samples, dimension
+    #n_bkps, sigma = 3, 5  # number of change points, noise standart deviation
+    signal, bkps = rpt.pw_wavy(n, n_bkps, noise_std=sigma)
+    rpt.display(signal, bkps)
+    return signal,bkps
+
+input_list = ['piecewiseConstant','piecewiseLinear','piecewiseNormal','piecewiseSinusoidal']
+generate_signal = st.selectbox(label = "Choose an input signal", options = input_list)
+
+
+
+
+