{
"cells": [
{
"cell_type": "code",
"execution_count": 64,
"id": "499860ca-54b4-43b7-b82a-8fafe158afe0",
"metadata": {},
"outputs": [],
"source": [
"from dataclasses import dataclass\n",
"from dataclasses import field\n",
"from struct import Struct\n",
"from math import sqrt\n",
"from collections import namedtuple\n",
"import sys"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "41b2b84f-7935-4620-857f-cf0c217fd256",
"metadata": {},
"outputs": [],
"source": [
"@dataclass\n",
"class vecf:\n",
" x: float\n",
" y: float\n",
" z: float\n",
" packer: Struct = field(init=False, repr=False, default=Struct( \"fff\" ))\n",
" def normalize(self):\n",
" return sqrt(self.x*self.x + self.y*self.y + self.z*self.z)\n",
"\n",
" def pack(self):\n",
" return self.packer.pack(*self.to_list())\n",
"\n",
" def unpack(self, pkt):\n",
" return self.packer.unpack(pkt)\n",
"\n",
" def to_list(self):\n",
" ret = []\n",
" for a in self.__dict__.values():\n",
" if isinstance(a,float) or isinstance(a,int):\n",
" ret.append(a)\n",
" else:\n",
" for i in a.to_list():\n",
" ret.append(i)\n",
" return ret"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "5542ffee-6568-4be6-b6a5-1ed06d9fea17",
"metadata": {},
"outputs": [],
"source": [
"@dataclass\n",
"class imu:\n",
" id: int # something\n",
" accel: vecf\n",
" gyro: vecf\n",
" mag: vecf\n",
" pressure: float\n",
" temperature: float\n",
" timestamp: int\n",
" packer: Struct = field(init=False, repr=False, default=Struct( \"BfffffffffffI\" ))\n",
"\n",
" def pack(self):\n",
" data = self.to_list()\n",
" print(data)\n",
" return self.packer.pack(*data)\n",
"\n",
" def unpack(self, pkt):\n",
" return self.packer.unpack(pkt)\n",
"\n",
" def to_list(self):\n",
" ret = []\n",
" for a in self.__dict__.values():\n",
" if isinstance(a,float) or isinstance(a,int):\n",
" ret.append(a)\n",
" else:\n",
" for i in a.to_list():\n",
" ret.append(i)\n",
" return ret"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "6e860ce2-f698-43d6-ad30-c6686f291509",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"vecf(x=1, y=2, z=3)\n"
]
},
{
"data": {
"text/plain": [
"[1, 2, 3]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"v = vecf(1,2,3)\n",
"print(v)\n",
"\n",
"import dataclasses\n",
"f = dataclasses.fields(v)[0]\n",
"l = []\n",
"for a in v.__dict__.values():\n",
" if isinstance(a,float) or isinstance(a,int):\n",
" l.append(a)\n",
" else:\n",
" for i in a.to_list():\n",
" l.append(i)\n",
"\n",
"l\n",
"# f.values()\n",
"# for ff in f:\n",
" # print(ff)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c28d1237-cc1b-47af-8e08-dcccce811652",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1, 2, 3]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"v.to_list()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "1ff55c3e-c700-4d2d-a18b-0dd22c1dcaef",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"b'\\x00\\x00\\x80?\\x00\\x00\\x00@\\x00\\x00@@'\n"
]
}
],
"source": [
"pkt = v.pack()\n",
"print(pkt)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "2e221ecc-1801-44f3-a13b-99dead25f3a2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"vecf(x=1, y=2, z=3)\n"
]
}
],
"source": [
"m = v.unpack(pkt)\n",
"print(v)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "9ad4dc05-d684-4900-a428-ee8311ab37e7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"imu(id=1, accel=vecf(x=1, y=2, z=3), gyro=vecf(x=4, y=5, z=6), mag=vecf(x=7, y=8, z=9), pressure=1, temperature=2, timestamp=3)\n"
]
}
],
"source": [
"i = imu(1,vecf(1,2,3),vecf(4,5,6),vecf(7,8,9),1,2,3)\n",
"print(i)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "e0e6be3c-0041-473e-8cf6-8283389e2f52",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3]\n",
"b'\\x01\\x00\\x00\\x00\\x00\\x00\\x80?\\x00\\x00\\x00@\\x00\\x00@@\\x00\\x00\\x80@\\x00\\x00\\xa0@\\x00\\x00\\xc0@\\x00\\x00\\xe0@\\x00\\x00\\x00A\\x00\\x00\\x10A\\x00\\x00\\x80?\\x00\\x00\\x00@\\x03\\x00\\x00\\x00'\n"
]
}
],
"source": [
"pkt = i.pack()\n",
"print(pkt)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "dcfffe69-d082-45a1-9f4e-54c69e0acd1d",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "5f49efe6-e12c-4f2e-a28c-534391f41144",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 101,
"id": "ba4c5e16-0e10-44c7-bf87-2de5f507381e",
"metadata": {},
"outputs": [],
"source": [
"class Base:\n",
" def flatten(self, data):\n",
" \"\"\"\n",
" (0, (1, 2, 3), (4, 5, 6)) -> (0, 1, 2, 3, 4, 5, 6)\n",
" \"\"\"\n",
" if isinstance(data, tuple):\n",
" for x in data:\n",
" yield from self.flatten(x)\n",
" else:\n",
" yield data\n",
" \n",
" def serialize(self):\n",
" return tuple(self.flatten(dataclasses.astuple(self)))\n",
" \n",
"@dataclass(frozen=True)\n",
"class vec_t(Base):\n",
" x: float\n",
" y: float\n",
" z: float\n",
" \n",
" def __yivo__(self):\n",
" return (\"fff\", 12, vec_t) # (struct format, number bytes)\n",
"\n",
"@dataclass(frozen=True)\n",
"class twist_t(Base):\n",
" linear: vec_t\n",
" angular: vec_t\n",
" \n",
" def __yivo__(self):\n",
" return (\"3f3f\", 120, twist_t) # (struct format, number bytes)\n",
"\n",
" # def __init__(self,lx,ly,lz,ax,ay,az):\n",
" # object.__setattr__(self, \"linear\", vec_t(lx,ly,lz))\n",
" # object.__setattr__(self, \"angular\", vec_t(ax,ay,az))\n",
"\n",
"def fmt(a):\n",
" return a.__yivo__()[0]\n",
"\n",
"def sizeof(a):\n",
" return a.__yivo__()[1]\n",
"\n",
"def cls(a):\n",
" return a.__yivo__()[2]"
]
},
{
"cell_type": "code",
"execution_count": 102,
"id": "5762769b-8278-4d2e-847c-44b0097263fb",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"twist_t(linear=vec_t(x=0, y=1, z=2), angular=vec_t(x=3, y=4, z=5))"
]
},
"execution_count": 102,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t=twist_t(vec_t(0,1,2),vec_t(3,4,5))\n",
"t"
]
},
{
"cell_type": "code",
"execution_count": 103,
"id": "cbb9f312-1afd-4a4b-9ffe-8b049aca4ff5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0, 1, 2, 3, 4, 5)"
]
},
"execution_count": 103,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t.serialize()"
]
},
{
"cell_type": "code",
"execution_count": 104,
"id": "81e0836c-ccf9-4734-b7de-3299db80fe22",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((0, 1, 2), (3, 4, 5))"
]
},
"execution_count": 104,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataclasses.astuple(t)"
]
},
{
"cell_type": "code",
"execution_count": 105,
"id": "3d6e25f6-6ba8-4d34-8852-8ba948fa5d1a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 105,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t2=twist_t(vec_t(0,1,2),vec_t(3,4,5))\n",
"\n",
"t == t2"
]
},
{
"cell_type": "code",
"execution_count": 106,
"id": "b8741f3b-0b08-4d5d-9336-f7d5dd63256b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'3f3f'"
]
},
"execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fmt(t)"
]
},
{
"cell_type": "code",
"execution_count": 107,
"id": "4aff82d9-54d0-4023-b5f7-109a1ccd56ee",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"120"
]
},
"execution_count": 107,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sizeof(t)"
]
},
{
"cell_type": "code",
"execution_count": 108,
"id": "70074502-0615-4ba2-b0c6-dd16fbd90f97",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"twist_t(linear=1, angular=2)"
]
},
"execution_count": 108,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x=cls(t)\n",
"x(1,2)"
]
},
{
"cell_type": "code",
"execution_count": 109,
"id": "473e7ff8-8662-41aa-a4ee-fcd0c853b32b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"__main__.vec_t"
]
},
"execution_count": 109,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"v = vec_t(1,2,3)\n",
"cls(v)"
]
},
{
"cell_type": "code",
"execution_count": 110,
"id": "ae749406-de0c-49a0-acbb-6512e3c62c7d",
"metadata": {},
"outputs": [
{
"ename": "FrozenInstanceError",
"evalue": "cannot assign to field 'linear'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFrozenInstanceError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[110], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlinear\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m4\u001b[39m\n",
"File \u001b[0;32m<string>:4\u001b[0m, in \u001b[0;36m__setattr__\u001b[0;34m(self, name, value)\u001b[0m\n",
"\u001b[0;31mFrozenInstanceError\u001b[0m: cannot assign to field 'linear'"
]
}
],
"source": [
"t.linear = 4"
]
},
{
"cell_type": "code",
"execution_count": 111,
"id": "4911f017-2f19-4a62-9669-6a75b5ed36e6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['__annotations__',\n",
" '__class__',\n",
" '__dataclass_fields__',\n",
" '__dataclass_params__',\n",
" '__delattr__',\n",
" '__dict__',\n",
" '__dir__',\n",
" '__doc__',\n",
" '__eq__',\n",
" '__format__',\n",
" '__ge__',\n",
" '__getattribute__',\n",
" '__getstate__',\n",
" '__gt__',\n",
" '__hash__',\n",
" '__init__',\n",
" '__init_subclass__',\n",
" '__le__',\n",
" '__lt__',\n",
" '__match_args__',\n",
" '__module__',\n",
" '__ne__',\n",
" '__new__',\n",
" '__reduce__',\n",
" '__reduce_ex__',\n",
" '__repr__',\n",
" '__setattr__',\n",
" '__sizeof__',\n",
" '__str__',\n",
" '__subclasshook__',\n",
" '__weakref__',\n",
" '__yivo__',\n",
" 'angular',\n",
" 'flatten',\n",
" 'linear',\n",
" 'serialize']"
]
},
"execution_count": 111,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dir(t)"
]
},
{
"cell_type": "code",
"execution_count": 114,
"id": "f74439ca-76cb-4910-86dc-0a8f6e1778b2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('3f3f', 120, __main__.twist_t)"
]
},
"execution_count": 114,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t.__yivo__()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7f10c9b9-dac3-4685-acad-7b16123186d9",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}