Nptyping shapefix

labs/lab2/lab2.ipynb

@@ -60,7 +60,7 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "import ipywidgets as widgets\n",
-    "from nptyping import NDArray\n",
+    "from nptyping import NDArray, Shape\n",
     "from typing import Any, Tuple, List, Optional\n",
     "\n",
     "# Import Racecar library\n",
@@ -107,7 +107,7 @@
     "\n",
     "    \n",
     "def draw_circle(\n",
-    "    color_image: NDArray[(Any, Any, 3), np.uint8],\n",
+    "    color_image: NDArray[Shape[\"*, *, 3\"], np.uint8],\n",
     "    center: Tuple[int, int],\n",
     "    color: Tuple[int, int, int] = (0, 255, 255),\n",
     "    radius: int = 6,\n",
@@ -324,7 +324,7 @@
    "outputs": [],
    "source": [
     "def get_mask(\n",
-    "    image: NDArray[(Any, Any, 3), np.uint8],\n",
+    "    image: NDArray[Shape[\"*, *, 3\"], np.uint8],\n",
     "    hsv_lower: Tuple[int, int, int],\n",
     "    hsv_upper: Tuple[int, int, int]\n",
     ") -> NDArray[Any, Any]:\n",
@@ -931,7 +931,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -945,7 +945,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.10.2"
   }
  },
  "nbformat": 4,

labs/lab3/lab3.ipynb

@@ -57,7 +57,7 @@
     "import matplotlib.pyplot as plt\n",
     "import ipywidgets as widgets\n",
     "import statistics\n",
-    "from nptyping import NDArray\n",
+    "from nptyping import NDArray, Shape\n",
     "from typing import Any, Tuple, List, Optional\n",
     "\n",
     "# Import Racecar library\n",
@@ -80,7 +80,7 @@
    "outputs": [],
    "source": [
     "def show_depth_image(\n",
-    "    depth_image: NDArray[(Any, Any), np.float32],\n",
+    "    depth_image: NDArray[Shape[\"*, *\"], np.float32],\n",
     "    max_depth: int = 400,\n",
     "    points: List[Tuple[int, int]] = []\n",
     ") -> None:\n",
@@ -111,10 +111,10 @@
     "\n",
     "\n",
     "def add_noise(\n",
-    "    depth_image: NDArray[(Any, Any), np.float32],\n",
+    "    depth_image: NDArray[Shape[\"*, *\"], np.float32],\n",
     "    error_percent = 0.1,\n",
     "    null_percent: float = 0.005\n",
-    ") -> NDArray[(Any, Any), np.float32]:\n",
+    ") -> NDArray[Shape[\"*, *\"], np.float32]:\n",
     "    \"\"\"\n",
     "    Adds noise to a depth image.\n",
     "    \n",
@@ -359,7 +359,7 @@
    "outputs": [],
    "source": [
     "def get_depth_image_center_distance(\n",
-    "    depth_image: NDArray[(Any, Any), np.float32], \n",
+    "    depth_image: NDArray[Shape[\"*, *\"], np.float32], \n",
     "    kernel_size: int\n",
     ") -> float:\n",
     "    \"\"\"\n",
@@ -445,7 +445,7 @@
    "outputs": [],
    "source": [
     "def get_closest_pixel(\n",
-    "    depth_image: NDArray[(Any, Any), np.float32],\n",
+    "    depth_image: NDArray[Shape[\"*, *\"], np.float32],\n",
     "    kernel_size: int = 5\n",
     ") -> Tuple[int, int]:\n",
     "    \"\"\"\n",
@@ -530,7 +530,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -544,7 +544,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.10.2"
   }
  },
  "nbformat": 4,

library/camera.py

@@ -10,6 +10,7 @@
 import copy
 import numpy as np
 from nptyping import NDArray
+from nptyping import Shape
 
 
 class Camera(abc.ABC):
@@ -24,7 +25,7 @@ class Camera(abc.ABC):
     # Maximum range of the depth camera (in cm)
     _MAX_RANGE = 1200
 
-    def get_color_image(self) -> NDArray[(480, 640, 3), np.uint8]:
+    def get_color_image(self) -> NDArray[Shape["480, 640, 3"], np.uint8]:
         """
         Returns a deep copy of the current color image captured by the camera.
 
@@ -53,7 +54,7 @@ def get_color_image(self) -> NDArray[(480, 640, 3), np.uint8]:
         return copy.deepcopy(self.get_color_image_no_copy())
 
     @abc.abstractmethod
-    def get_color_image_no_copy(self) -> NDArray[(480, 640, 3), np.uint8]:
+    def get_color_image_no_copy(self) -> NDArray[Shape["480, 640, 3"], np.uint8]:
         """
         Returns a direct reference to the color image captured by the camera.
 
@@ -94,7 +95,7 @@ def get_color_image_no_copy(self) -> NDArray[(480, 640, 3), np.uint8]:
         pass
 
     @abc.abstractmethod
-    def get_color_image_async(self) -> NDArray[(480, 640, 3), np.uint8]:
+    def get_color_image_async(self) -> NDArray[Shape["480, 640, 3"], np.uint8]:
         """
         Returns the current color image without the car in "go" mode.
 
@@ -122,7 +123,7 @@ def get_color_image_async(self) -> NDArray[(480, 640, 3), np.uint8]:
         pass
 
     @abc.abstractmethod
-    def get_depth_image(self) -> NDArray[(480, 640), np.float32]:
+    def get_depth_image(self) -> NDArray[Shape["480, 640"], np.float32]:
         """
         Returns the current depth image captured by the camera.
 
@@ -141,7 +142,7 @@ def get_depth_image(self) -> NDArray[(480, 640), np.float32]:
         pass
 
     @abc.abstractmethod
-    def get_depth_image_async(self) -> NDArray[(480, 640), np.float32]:
+    def get_depth_image_async(self) -> NDArray[Shape["480, 640"], np.float32]:
         """
         Returns the current depth image without the car in "go" mode.
 

library/display.py

@@ -11,6 +11,7 @@
 import math
 from typing import List, Tuple, Any
 from nptyping import NDArray
+from nptyping import Shape
 
 import racecar_utils as rc_utils
 
@@ -68,7 +69,7 @@ def show_color_image(self, image: NDArray) -> None:
 
     def show_depth_image(
         self,
-        image: NDArray[(Any, Any), np.float32],
+        image: NDArray[Shape["*,*"], np.float32],
         max_depth: int = 1000,
         points: List[Tuple[int, int]] = [],
     ) -> None:

library/lidar.py

@@ -9,6 +9,7 @@
 import abc
 import numpy as np
 from nptyping import NDArray
+from nptyping import Shape
 
 
 class Lidar(abc.ABC):
@@ -20,7 +21,7 @@ class Lidar(abc.ABC):
     _NUM_SAMPLES: int = 720
 
     @abc.abstractmethod
-    def get_samples(self) -> NDArray[720, np.float32]:
+    def get_samples(self) -> NDArray[Shape["720"], np.float32]:
         """
         Returns the current LIDAR scan as an array of distance measurements.
 
@@ -42,7 +43,7 @@ def get_samples(self) -> NDArray[720, np.float32]:
         pass
 
     @abc.abstractmethod
-    def get_samples_async(self) -> NDArray[720, np.float32]:
+    def get_samples_async(self) -> NDArray[Shape["720"], np.float32]:
         """
         Returns the current LIDAR scan without the car in "go" mode.
 

library/physics.py

@@ -9,6 +9,7 @@
 import abc
 import numpy as np
 from nptyping import NDArray
+from nptyping import Shape
 
 
 class Physics(abc.ABC):
@@ -17,7 +18,7 @@ class Physics(abc.ABC):
     """
 
     @abc.abstractmethod
-    def get_linear_acceleration(self) -> NDArray[3, np.float32]:
+    def get_linear_acceleration(self) -> NDArray[Shape["3"], np.float32]:
         """
         Returns a 3D vector containing the car's linear acceleration.
 
@@ -42,7 +43,7 @@ def get_linear_acceleration(self) -> NDArray[3, np.float32]:
         pass
 
     @abc.abstractmethod
-    def get_angular_velocity(self) -> NDArray[3, np.float32]:
+    def get_angular_velocity(self) -> NDArray[Shape["3"], np.float32]:
         """
         Returns a 3D vector containing the car's angular velocity.
 

library/racecar_utils.py

@@ -10,6 +10,7 @@
 import numpy as np
 from typing import *
 from nptyping import NDArray
+from nptyping import Shape
 from enum import Enum, IntEnum
 
 
@@ -187,10 +188,10 @@ def remap_range(
 
 
 def crop(
-    image: NDArray[(Any, ...), Any],
+    image: NDArray[Shape["*, ..."], Any],
     top_left_inclusive: Tuple[float, float],
     bottom_right_exclusive: Tuple[float, float],
-) -> NDArray[(Any, ...), Any]:
+) -> NDArray[Shape["*, ..."], Any]:
     """
     Crops an image to a rectangle based on the specified pixel points.
 
@@ -241,8 +242,8 @@ def crop(
 
 
 def stack_images_horizontal(
-    image_0: NDArray[(Any, ...), Any], image_1: NDArray[(Any, ...), Any]
-) -> NDArray[(Any, ...), Any]:
+    image_0: NDArray[Shape["*, ..."], Any], image_1: NDArray[Shape["*, ..."], Any]
+) -> NDArray[Shape["*, ..."], Any]:
     """
     Stack two images horizontally.
 
@@ -274,8 +275,8 @@ def stack_images_horizontal(
 
 
 def stack_images_vertical(
-    image_0: NDArray[(Any, ...), Any], image_1: NDArray[(Any, ...), Any]
-) -> NDArray[(Any, ...), Any]:
+    image_0: NDArray[Shape["*, ..."], Any], image_1: NDArray[Shape["*, ..."], Any]
+) -> NDArray[Shape["*, ..."], Any]:
     """
     Stack two images vertically.
 
@@ -335,7 +336,7 @@ class ColorBGR(Enum):
 
 
 def find_contours(
-    color_image: NDArray[(Any, Any, 3), np.uint8],
+    color_image: NDArray[Shape["*, *, 3"], np.uint8],
     hsv_lower: Tuple[int, int, int],
     hsv_upper: Tuple[int, int, int],
 ) -> List[NDArray]:
@@ -447,7 +448,7 @@ def get_largest_contour(
 
 
 def draw_contour(
-    color_image: NDArray[(Any, Any, 3), np.uint8],
+    color_image: NDArray[Shape["Any, Any, 3"], np.uint8],
     contour: NDArray,
     color: Tuple[int, int, int] = ColorBGR.green.value,
 ) -> None:
@@ -483,7 +484,7 @@ def draw_contour(
 
 
 def draw_circle(
-    color_image: NDArray[(Any, Any, 3), np.uint8],
+    color_image: NDArray[Shape["Any, Any, 3"], np.uint8],
     center: Tuple[int, int],
     color: Tuple[int, int, int] = ColorBGR.yellow.value,
     radius: int = 6,
@@ -600,7 +601,7 @@ def get_contour_area(contour: NDArray) -> float:
 
 
 def get_depth_image_center_distance(
-    depth_image: NDArray[(Any, Any), np.float32], kernel_size: int = 5
+    depth_image: NDArray[Shape["*, *"], np.float32], kernel_size: int = 5
 ) -> float:
     """
     Finds the distance of the center object in a depth image.
@@ -639,7 +640,7 @@ def get_depth_image_center_distance(
 
 
 def get_pixel_average_distance(
-    depth_image: NDArray[(Any, Any), np.float32],
+    depth_image: NDArray[Shape["*, *"], np.float32],
     pix_coord: Tuple[int, int],
     kernel_size: int = 5,
 ) -> float:
@@ -711,7 +712,7 @@ def get_pixel_average_distance(
 
 
 def get_closest_pixel(
-    depth_image: NDArray[(Any, Any), np.float32], kernel_size: int = 5
+    depth_image: NDArray[Shape["*, *"], np.float32], kernel_size: int = 5
 ) -> Tuple[int, int]:
     """
     Finds the closest pixel in a depth image.
@@ -764,8 +765,8 @@ def get_closest_pixel(
 
 
 def colormap_depth_image(
-    depth_image: NDArray[(Any, Any), np.float32], max_depth: int = 1000,
-) -> NDArray[(Any, Any, 3), np.uint8]:
+    depth_image: NDArray[Shape["*, *"], np.float32], max_depth: int = 1000,
+) -> NDArray[Shape["*, *, 3"], np.uint8]:
     """
     Converts a depth image to a colored image representing depth.
 
@@ -967,7 +968,7 @@ class ARMarker:
     """
 
     def __init__(
-        self, marker_id: int, marker_corners: NDArray[(4, 2), np.int32]
+        self, marker_id: int, marker_corners: NDArray[Shape["4, 2"], np.int32]
     ) -> None:
         """
         Creates an object representing an AR marker.
@@ -1007,7 +1008,7 @@ def __init__(
 
     def detect_colors(
         self,
-        color_image: NDArray[(Any, Any), np.float32],
+        color_image: NDArray[Shape["Any, Any"], np.float32],
         potential_colors: List[Tuple[Tuple[int, int, int], Tuple[int, int, int], str]],
     ) -> None:
         """
@@ -1068,7 +1069,7 @@ def get_id(self) -> int:
         """
         return self.__id
 
-    def get_corners(self) -> NDArray[(4, 2), np.int32]:
+    def get_corners(self) -> NDArray[Shape["4, 2"], np.int32]:
         """
         Returns the (row, col) coordinates of the four corners of the marker.
 
@@ -1078,7 +1079,7 @@ def get_corners(self) -> NDArray[(4, 2), np.int32]:
         """
         return self.__corners
 
-    def get_corners_aruco_format(self) -> NDArray[(1, 4, 2), np.float32]:
+    def get_corners_aruco_format(self) -> NDArray[Shape["1, 4, 2"], np.float32]:
         """
         Returns the corners of the AR marker formatted as needed by the ArUco library.
         """
@@ -1113,7 +1114,7 @@ def __str__(self) -> str:
 
 
 def get_ar_markers(
-    color_image: NDArray[(Any, Any, 3), np.uint8],
+    color_image: NDArray[Shape["*, *, 3"], np.uint8],
     potential_colors: List[
         Tuple[Tuple[int, int, int], Tuple[int, int, int], str]
     ] = None,
@@ -1167,10 +1168,10 @@ def get_ar_markers(
 
 
 def draw_ar_markers(
-    color_image: NDArray[(Any, Any, 3), np.uint8],
+    color_image: NDArray[Shape["*, *, 3"], np.uint8],
     markers: List[ARMarker],
     color: Tuple[int, int, int] = ColorBGR.green.value,
-) -> NDArray[(Any, Any, 3), np.uint8]:
+) -> NDArray[Shape["*, *, 3"], np.uint8]:
     """
     Draws annotations on the AR markers in a image.