diff --git a/workflows/ci.yml b/.github/workflows/ci.yml
similarity index 100%
rename from workflows/ci.yml
rename to .github/workflows/ci.yml
diff --git a/workflows/codebase-diagram.yml b/.github/workflows/codebase-diagram.yml
similarity index 100%
rename from workflows/codebase-diagram.yml
rename to .github/workflows/codebase-diagram.yml
diff --git a/workflows/docs.yml b/.github/workflows/docs.yml
similarity index 100%
rename from workflows/docs.yml
rename to .github/workflows/docs.yml
diff --git a/workflows/test.yml b/.github/workflows/test.yml
similarity index 100%
rename from workflows/test.yml
rename to .github/workflows/test.yml
diff --git a/README.md b/README.md
index a71cdd0..6083e4d 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,3 @@
-# Path Planner
-
-![Visualization of the codebase](./codebase-diagram.svg)
+# Speed Profiler
 
 ## Features
-plans the path :)
\ No newline at end of file
diff --git a/scripts/conegenerator.py b/scripts/conegenerator.py
deleted file mode 100644
index 89253c1..0000000
--- a/scripts/conegenerator.py
+++ /dev/null
@@ -1,66 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-# The arc is a semi-circle, from pi (180 degrees) to 0
-theta = np.linspace(np.pi, 0, int(2 * np.pi * 3))  # Assuming there's a point every 1.5m in the outer arc with radius 6m
-# Define the radius of outer and inner semi-circles
-
-curve_radius = 6
-track_width = 5
-
-r_outer = curve_radius + track_width/2  # radius of outer semi-circle
-r_inner = curve_radius - track_width/2  # radius of inner semi-circle
-# Compute x, y coordinates for points along the outer and inner semi-circles
-
-
-y_outer_arc = r_outer * np.cos(theta) + r_outer - (r_outer-r_inner)/2
-x_outer_arc = r_outer * np.sin(theta) + 20
-y_inner_arc = r_inner * np.cos(theta) + r_outer - (r_outer-r_inner)/2 # Offset by r_outer to align with outer arc
-x_inner_arc = r_inner * np.sin(theta) + 20
-
-# Compute the straight line sections (assuming they are 10m long)
-x_straight = np.linspace(2, 19, int(15/1))  # Points every 2m for the straight line
-x_straight_exit = np.linspace(2, 19, int(15/1))  # Exit straight line
-y_outer_straight = np.full_like(x_straight, - (r_outer-r_inner)/2)  # Outer straight line is at x = 0
-y_inner_straight = np.full_like(x_straight, + (r_outer-r_inner)/2)  # Inner straight line is at x = 3
-y_outer_straight_exit = np.full_like(x_straight_exit, 2*r_outer - (r_outer-r_inner)/2)  # Outer exit straight line is at x = 2*r_outer
-y_inner_straight_exit = np.full_like(x_straight_exit, 2*r_outer - (r_outer-r_inner)/2 - (r_outer-r_inner))  # Inner exit straight line is at x = 2*r_outer - 3
-
-x_orange = [1,1,1,1]
-y_orange = [track_width/2, - track_width/2, 2*curve_radius + track_width/2, 2*curve_radius - track_width/2]
-
-# Concatenate straight line, arc sections and exit straight line
-x_outer = np.concatenate((x_straight, x_outer_arc, x_straight_exit))
-y_outer = np.concatenate((y_outer_straight, y_outer_arc, y_outer_straight_exit))
-x_inner = np.concatenate((x_straight, x_inner_arc, x_straight_exit))
-y_inner = np.concatenate((y_inner_straight, y_inner_arc, y_inner_straight_exit))
-
-# Create the plot
-plt.figure(figsize=(10, 10))
-plt.plot(x_outer, y_outer, 'o', label='Outer Path')
-plt.plot(x_inner, y_inner, 'o', label='Inner Path')
-plt.plot(x_orange, y_orange, 'o', label='Orange Cone')
-
-s = ""
-for i in range(len(x_inner)):
-    s += "yellow,%f,%f,0,0,0,0\n" % (x_inner[i],y_inner[i])
-
-for i in range(len(x_outer)):
-    s += "blue,%f,%f,0,0,0,0\n" % (x_outer[i],y_outer[i])
-
-for i in range(len(x_orange)):
-    s += "big_orange,%f,%f,0,0,0,0\n" % (x_orange[i],y_orange[i])
-
-
-f = open("map.csv", 'w')
-f.write(s)
-f.close()
-
-print(s)
-
-plt.legend()
-plt.title('U-turn Track with Entry and Exit Straight Sections')
-plt.xlabel('x (m)')
-plt.ylabel('y (m)')
-plt.grid(True)
-plt.axis('equal')  # Ensure the x and y axis scales are equal
-plt.show()
\ No newline at end of file
diff --git a/scripts/map.csv b/scripts/map.csv
deleted file mode 100644
index 7182099..0000000
--- a/scripts/map.csv
+++ /dev/null
@@ -1,100 +0,0 @@
-yellow,2.000000,2.500000,0,0,0,0
-yellow,3.214286,2.500000,0,0,0,0
-yellow,4.428571,2.500000,0,0,0,0
-yellow,5.642857,2.500000,0,0,0,0
-yellow,6.857143,2.500000,0,0,0,0
-yellow,8.071429,2.500000,0,0,0,0
-yellow,9.285714,2.500000,0,0,0,0
-yellow,10.500000,2.500000,0,0,0,0
-yellow,11.714286,2.500000,0,0,0,0
-yellow,12.928571,2.500000,0,0,0,0
-yellow,14.142857,2.500000,0,0,0,0
-yellow,15.357143,2.500000,0,0,0,0
-yellow,16.571429,2.500000,0,0,0,0
-yellow,17.785714,2.500000,0,0,0,0
-yellow,19.000000,2.500000,0,0,0,0
-yellow,20.000000,2.500000,0,0,0,0
-yellow,20.643123,2.559594,0,0,0,0
-yellow,21.264346,2.736347,0,0,0,0
-yellow,21.842513,3.024240,0,0,0,0
-yellow,22.357935,3.413469,0,0,0,0
-yellow,22.793060,3.890779,0,0,0,0
-yellow,23.133072,4.439916,0,0,0,0
-yellow,23.366390,5.042180,0,0,0,0
-yellow,23.485070,5.677061,0,0,0,0
-yellow,23.485070,6.322939,0,0,0,0
-yellow,23.366390,6.957820,0,0,0,0
-yellow,23.133072,7.560084,0,0,0,0
-yellow,22.793060,8.109221,0,0,0,0
-yellow,22.357935,8.586531,0,0,0,0
-yellow,21.842513,8.975760,0,0,0,0
-yellow,21.264346,9.263653,0,0,0,0
-yellow,20.643123,9.440406,0,0,0,0
-yellow,20.000000,9.500000,0,0,0,0
-yellow,2.000000,9.500000,0,0,0,0
-yellow,3.214286,9.500000,0,0,0,0
-yellow,4.428571,9.500000,0,0,0,0
-yellow,5.642857,9.500000,0,0,0,0
-yellow,6.857143,9.500000,0,0,0,0
-yellow,8.071429,9.500000,0,0,0,0
-yellow,9.285714,9.500000,0,0,0,0
-yellow,10.500000,9.500000,0,0,0,0
-yellow,11.714286,9.500000,0,0,0,0
-yellow,12.928571,9.500000,0,0,0,0
-yellow,14.142857,9.500000,0,0,0,0
-yellow,15.357143,9.500000,0,0,0,0
-yellow,16.571429,9.500000,0,0,0,0
-yellow,17.785714,9.500000,0,0,0,0
-yellow,19.000000,9.500000,0,0,0,0
-blue,2.000000,-2.500000,0,0,0,0
-blue,3.214286,-2.500000,0,0,0,0
-blue,4.428571,-2.500000,0,0,0,0
-blue,5.642857,-2.500000,0,0,0,0
-blue,6.857143,-2.500000,0,0,0,0
-blue,8.071429,-2.500000,0,0,0,0
-blue,9.285714,-2.500000,0,0,0,0
-blue,10.500000,-2.500000,0,0,0,0
-blue,11.714286,-2.500000,0,0,0,0
-blue,12.928571,-2.500000,0,0,0,0
-blue,14.142857,-2.500000,0,0,0,0
-blue,15.357143,-2.500000,0,0,0,0
-blue,16.571429,-2.500000,0,0,0,0
-blue,17.785714,-2.500000,0,0,0,0
-blue,19.000000,-2.500000,0,0,0,0
-blue,20.000000,-2.500000,0,0,0,0
-blue,21.561871,-2.355271,0,0,0,0
-blue,23.070554,-1.926014,0,0,0,0
-blue,24.474673,-1.226846,0,0,0,0
-blue,25.726413,-0.281576,0,0,0,0
-blue,26.783146,0.877606,0,0,0,0
-blue,27.608888,2.211224,0,0,0,0
-blue,28.175518,3.673865,0,0,0,0
-blue,28.463740,5.215719,0,0,0,0
-blue,28.463740,6.784281,0,0,0,0
-blue,28.175518,8.326135,0,0,0,0
-blue,27.608888,9.788776,0,0,0,0
-blue,26.783146,11.122394,0,0,0,0
-blue,25.726413,12.281576,0,0,0,0
-blue,24.474673,13.226846,0,0,0,0
-blue,23.070554,13.926014,0,0,0,0
-blue,21.561871,14.355271,0,0,0,0
-blue,20.000000,14.500000,0,0,0,0
-blue,2.000000,14.500000,0,0,0,0
-blue,3.214286,14.500000,0,0,0,0
-blue,4.428571,14.500000,0,0,0,0
-blue,5.642857,14.500000,0,0,0,0
-blue,6.857143,14.500000,0,0,0,0
-blue,8.071429,14.500000,0,0,0,0
-blue,9.285714,14.500000,0,0,0,0
-blue,10.500000,14.500000,0,0,0,0
-blue,11.714286,14.500000,0,0,0,0
-blue,12.928571,14.500000,0,0,0,0
-blue,14.142857,14.500000,0,0,0,0
-blue,15.357143,14.500000,0,0,0,0
-blue,16.571429,14.500000,0,0,0,0
-blue,17.785714,14.500000,0,0,0,0
-blue,19.000000,14.500000,0,0,0,0
-big_orange,1.000000,2.500000,0,0,0,0
-big_orange,1.000000,-2.500000,0,0,0,0
-big_orange,1.000000,14.500000,0,0,0,0
-big_orange,1.000000,9.500000,0,0,0,0
diff --git a/tests/test_interpolate.py b/tests/test_interpolate.py
deleted file mode 100644
index 9af81c4..0000000
--- a/tests/test_interpolate.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import numpy as np
-
-from speed_profiler.interpolate import interpolate_with_least_squares
-
-
-def test_interpolate_with_least_squares(planner_parameters):
-    points_per_waypoint = planner_parameters['points_per_waypoint']
-    path_gen_margin = planner_parameters['path_gen_margin']
-    total_waypoints = 10
-
-    total_points_in_path = total_waypoints * points_per_waypoint
-    expected_positive = np.linspace(
-        1 - path_gen_margin,
-        (total_waypoints - 1) + path_gen_margin,
-        total_points_in_path
-    )
-    expected_negative = np.negative(expected_positive)
-    expected_zero = [0] * total_points_in_path
-
-    test_cases = [
-        {
-            'initial_vehicle_position': np.array([0, 0]),
-            'waypoints': np.array([[x, 0] for x in range(total_waypoints)]),
-            'expected_path': np.column_stack((expected_positive, expected_zero))
-        },
-        {
-            'initial_vehicle_position': np.array([0, 0]),
-            'waypoints': np.array([[x, 0] for x in range(0, -total_waypoints, -1)]),
-            'expected_path': np.column_stack((expected_negative, expected_zero))
-        },
-        {
-            'initial_vehicle_position': np.array([0, 0]),
-            'waypoints': np.array([[0, y] for y in range(total_waypoints)]),
-            'expected_path': np.column_stack((expected_zero, expected_positive))
-        },
-        {
-            'initial_vehicle_position': np.array([0, 0]),
-            'waypoints': np.array([[0, y] for y in range(0, -total_waypoints, -1)]),
-            'expected_path': np.column_stack((expected_zero, expected_negative))
-        },
-    ]
-
-    for test_case in test_cases:
-        initial_vehicle_position = test_case['initial_vehicle_position']
-        waypoints = test_case['waypoints']
-        expected_path = test_case['expected_path']
-        path = interpolate_with_least_squares(
-            waypoints, initial_vehicle_position, points_per_waypoint, path_gen_margin
-        )
-
-        assert len(path) == len(expected_path)
-        assert np.linalg.norm(path - expected_path) < 0.1
diff --git a/tests/test_planner.py b/tests/test_planner.py
deleted file mode 100644
index 5474295..0000000
--- a/tests/test_planner.py
+++ /dev/null
@@ -1,170 +0,0 @@
-import sys
-
-import numpy as np
-from numpy import random
-import pytest
-
-from speed_profiler.planner import Planner
-from speed_profiler.utils import calculate_min_distance_to_point
-
-
-@pytest.fixture
-def planner(planner_parameters):
-    return Planner(planner_parameters)
-
-
-@pytest.fixture
-def linear_track(planner_parameters):
-    initial_vehicle_pose = np.array([0, 0, 0])
-
-    distance_between_waypoints = 3
-    total_waypoints = 10
-    total_points_in_path = (total_waypoints + 1) * planner_parameters['points_per_waypoint']
-
-    x_coordinates = range(
-        distance_between_waypoints,
-        total_waypoints * distance_between_waypoints,
-        distance_between_waypoints
-    )
-
-    orange_cones = [np.array([0, 1]), np.array([0, -1])]
-    blue_cones = [np.array([x, -1]) for x in x_coordinates]
-    yellow_cones = [np.array([x, 1]) for x in x_coordinates]
-
-    waypoints = compute_waypoints_as_cone_averages(orange_cones, blue_cones, yellow_cones)
-
-    path_x = np.linspace(
-        initial_vehicle_pose[0] - planner_parameters['path_gen_margin'],
-        waypoints[-1][0] + planner_parameters['path_gen_margin'],
-        total_points_in_path
-    )
-    path_y = [0] * total_points_in_path
-
-    path = np.column_stack((path_x, path_y))
-
-    return {
-        'orange_cones': orange_cones,
-        'blue_cones': blue_cones,
-        'yellow_cones': yellow_cones,
-        'waypoints': waypoints,
-        'path': path,
-        'initial_vehicle_pose': initial_vehicle_pose,
-        'track_name': 'acceleration'
-    }
-
-
-@pytest.fixture
-def circular_track_open(planner_parameters):
-    return create_circular_track(planner_parameters, open_track=True, max_angle_degrees=300)
-
-
-@pytest.fixture
-def circular_track_closed(planner_parameters):
-    return create_circular_track(planner_parameters)
-
-
-@pytest.mark.parametrize('track', ['linear_track', 'circular_track_open', 'circular_track_closed'])
-def test_generate_waypoints(planner, track, request):
-    track = request.getfixturevalue(track)
-    expected_waypoints = track['waypoints']
-
-    waypoints = planner._generate_waypoints(
-        track['orange_cones'], track['blue_cones'], track['yellow_cones']
-    )
-
-    assert len(waypoints) == 2 * len(expected_waypoints)
-
-    for waypoint in waypoints:
-        assert calculate_min_distance_to_point(waypoint, expected_waypoints) < sys.float_info.epsilon
-
-
-@pytest.mark.parametrize('track', ['linear_track', 'circular_track_open', 'circular_track_closed'])
-def test_filter_waypoints(planner, track, request):
-    track = request.getfixturevalue(track)
-    expected_waypoints = track['waypoints']
-
-    # Random deviation [..., [xk, yk], ...] , where xk and yk are between -0.5 and 0.5
-    random_deviation = random.random_sample((len(expected_waypoints), 2)) - 0.5
-
-    unfiltered_waypoints = np.vstack((expected_waypoints, expected_waypoints + random_deviation))
-    filtered_waypoints = planner._filter_waypoints(unfiltered_waypoints)
-
-    assert len(filtered_waypoints) == len(expected_waypoints)
-    assert np.linalg.norm(np.array(filtered_waypoints) - np.array(expected_waypoints)) < sys.float_info.epsilon
-
-
-@pytest.mark.parametrize('track', ['linear_track', 'circular_track_open', 'circular_track_closed'])
-def test_construct_path(planner, track, request):
-    track = request.getfixturevalue(track)
-    expected_path = track['path']
-
-    planner.initial_vehicle_pose = track['initial_vehicle_pose']
-    planner.track_name = track['track_name']
-    path, _ = planner.construct_path(
-        track['orange_cones'], track['blue_cones'], track['yellow_cones']
-    )
-
-    path_xy = path[:, 0:2]
-    assert len(path_xy) == len(expected_path)
-    assert np.linalg.norm(path_xy - expected_path) < 0.1
-
-
-def create_circular_track(planner_parameters, open_track=False, max_angle_degrees=None):
-    inner_radius = 14.0
-    outer_radius = 18.0
-    center_radius = (inner_radius + outer_radius) / 2
-
-    step = 10
-    if open_track:
-        max_interpolated_angle_degrees = max_angle_degrees - step
-    else:
-        max_angle_degrees = 360
-        max_interpolated_angle_degrees = 360
-
-    angles = [np.deg2rad(theta) for theta in range(10, max_angle_degrees, step)]
-
-    orange_cones = [np.array([inner_radius, 0]), np.array([outer_radius, 0])]
-    blue_cones = [
-        np.array([outer_radius * np.cos(theta), outer_radius * np.sin(theta)])
-        for theta in angles
-    ]
-    yellow_cones = [
-        np.array([inner_radius * np.cos(theta), inner_radius * np.sin(theta)])
-        for theta in angles
-    ]
-
-    waypoints = compute_waypoints_as_cone_averages(orange_cones, blue_cones, yellow_cones)
-
-    total_interpolated_angles = (
-        len(waypoints) * planner_parameters['points_per_waypoint']
-        if open_track
-        else (len(waypoints) + 1) * planner_parameters['points_per_waypoint']
-    )
-
-    interpolated_angles = np.deg2rad(
-        np.linspace(0, max_interpolated_angle_degrees, total_interpolated_angles)
-    )
-    path = np.array([
-        [center_radius * np.cos(theta), center_radius * np.sin(theta)]
-        for theta in interpolated_angles
-    ])
-
-    return {
-        'orange_cones': orange_cones,
-        'blue_cones': blue_cones,
-        'yellow_cones': yellow_cones,
-        'waypoints': waypoints,
-        'path': path,
-        'initial_vehicle_pose': np.array([center_radius, 0, np.pi/2]),
-        'track_name': 'trackdrive'
-    }
-
-
-def compute_waypoints_as_cone_averages(orange_cones, blue_cones, yellow_cones):
-    yellow_blue_waypoints = [
-        (yellow_cone + blue_cone) / 2
-        for yellow_cone, blue_cone in zip(yellow_cones, blue_cones)
-    ]
-    orange_waypoint = (orange_cones[0] + orange_cones[1]) / 2
-
-    return [orange_waypoint] + yellow_blue_waypoints