{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2021-03-04T18:21:22.822563Z", "start_time": "2021-03-04T18:21:18.656643Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "source": [ "%pylab inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Notebook magic" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2021-03-05T06:53:22.506665Z", "start_time": "2021-03-05T06:53:22.499658Z" } }, "outputs": [], "source": [ "from IPython.core.magic import Magics, magics_class, line_cell_magic\n", "from IPython.core.magic import cell_magic, register_cell_magic, register_line_magic\n", "from IPython.core.magic_arguments import argument, magic_arguments, parse_argstring\n", "import subprocess\n", "import os" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2021-03-05T06:53:23.127314Z", "start_time": "2021-03-05T06:53:23.103181Z" } }, "outputs": [], "source": [ "@magics_class\n", "class PyboardMagic(Magics):\n", " @cell_magic\n", " @magic_arguments()\n", " @argument('-skip')\n", " @argument('-unix')\n", " @argument('-pyboard')\n", " @argument('-file')\n", " @argument('-data')\n", " @argument('-time')\n", " @argument('-memory')\n", " def micropython(self, line='', cell=None):\n", " args = parse_argstring(self.micropython, line)\n", " if args.skip: # doesn't care about the cell's content\n", " print('skipped execution')\n", " return None # do not parse the rest\n", " if args.unix: # tests the code on the unix port. Note that this works on unix only\n", " with open('/dev/shm/micropython.py', 'w') as fout:\n", " fout.write(cell)\n", " proc = subprocess.Popen([\"../../micropython/ports/unix/micropython\", \"/dev/shm/micropython.py\"], \n", " stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n", " print(proc.stdout.read().decode(\"utf-8\"))\n", " print(proc.stderr.read().decode(\"utf-8\"))\n", " return None\n", " if args.file: # can be used to copy the cell content onto the pyboard's flash\n", " spaces = \" \"\n", " try:\n", " with open(args.file, 'w') as fout:\n", " fout.write(cell.replace('\\t', spaces))\n", " printf('written cell to {}'.format(args.file))\n", " except:\n", " print('Failed to write to disc!')\n", " return None # do not parse the rest\n", " if args.data: # can be used to load data from the pyboard directly into kernel space\n", " message = pyb.exec(cell)\n", " if len(message) == 0:\n", " print('pyboard >>>')\n", " else:\n", " print(message.decode('utf-8'))\n", " # register new variable in user namespace\n", " self.shell.user_ns[args.data] = string_to_matrix(message.decode(\"utf-8\"))\n", " \n", " if args.time: # measures the time of executions\n", " pyb.exec('import utime')\n", " message = pyb.exec('t = utime.ticks_us()\\n' + cell + '\\ndelta = utime.ticks_diff(utime.ticks_us(), t)' + \n", " \"\\nprint('execution time: {:d} us'.format(delta))\")\n", " print(message.decode('utf-8'))\n", " \n", " if args.memory: # prints out memory information \n", " message = pyb.exec('from micropython import mem_info\\nprint(mem_info())\\n')\n", " print(\"memory before execution:\\n========================\\n\", message.decode('utf-8'))\n", " message = pyb.exec(cell)\n", " print(\">>> \", message.decode('utf-8'))\n", " message = pyb.exec('print(mem_info())')\n", " print(\"memory after execution:\\n========================\\n\", message.decode('utf-8'))\n", "\n", " if args.pyboard:\n", " message = pyb.exec(cell)\n", " print(message.decode('utf-8'))\n", "\n", "ip = get_ipython()\n", "ip.register_magics(PyboardMagic)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## pyboard" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "ExecuteTime": { "end_time": "2020-05-07T07:35:35.126401Z", "start_time": "2020-05-07T07:35:35.105824Z" } }, "outputs": [], "source": [ "import pyboard\n", "pyb = pyboard.Pyboard('/dev/ttyACM0')\n", "pyb.enter_raw_repl()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2020-05-19T19:11:18.145548Z", "start_time": "2020-05-19T19:11:18.137468Z" } }, "outputs": [], "source": [ "pyb.exit_raw_repl()\n", "pyb.close()" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "ExecuteTime": { "end_time": "2020-05-07T07:35:38.725924Z", "start_time": "2020-05-07T07:35:38.645488Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "%%micropython -pyboard 1\n", "\n", "import utime\n", "import ulab as np\n", "\n", "def timeit(n=1000):\n", " def wrapper(f, *args, **kwargs):\n", " func_name = str(f).split(' ')[1]\n", " def new_func(*args, **kwargs):\n", " run_times = np.zeros(n, dtype=np.uint16)\n", " for i in range(n):\n", " t = utime.ticks_us()\n", " result = f(*args, **kwargs)\n", " run_times[i] = utime.ticks_diff(utime.ticks_us(), t)\n", " print('{}() execution times based on {} cycles'.format(func_name, n, (delta2-delta1)/n))\n", " print('\\tbest: %d us'%np.min(run_times))\n", " print('\\tworst: %d us'%np.max(run_times))\n", " print('\\taverage: %d us'%np.mean(run_times))\n", " print('\\tdeviation: +/-%.3f us'%np.std(run_times)) \n", " return result\n", " return new_func\n", " return wrapper\n", "\n", "def timeit(f, *args, **kwargs):\n", " func_name = str(f).split(' ')[1]\n", " def new_func(*args, **kwargs):\n", " t = utime.ticks_us()\n", " result = f(*args, **kwargs)\n", " print('execution time: ', utime.ticks_diff(utime.ticks_us(), t), ' us')\n", " return result\n", " return new_func" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "__END_OF_DEFS__" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# ulab utilities\n", "\n", "\n", "There might be cases, when the format of your data does not conform to `ulab`, i.e., there is no obvious way to map the data to any of the five supported `dtype`s. A trivial example is an ADC or microphone signal with 32-bit resolution. For such cases, `ulab` defines the `utils` module, which, at the moment, has four functions that are not `numpy` compatible, but which should ease interfacing `ndarray`s to peripheral devices. \n", "\n", "The `utils` module can be enabled by setting the `ULAB_HAS_UTILS_MODULE` constant to 1 in [ulab.h](https://github.com/v923z/micropython-ulab/blob/master/code/ulab.h):\n", "\n", "```c\n", "#ifndef ULAB_HAS_UTILS_MODULE\n", "#define ULAB_HAS_UTILS_MODULE (1)\n", "#endif\n", "```\n", "\n", "This still does not compile any functions into the firmware. You can add a function by setting the corresponding pre-processor constant to 1. E.g., \n", "\n", "```c\n", "#ifndef ULAB_UTILS_HAS_FROM_INT16_BUFFER\n", "#define ULAB_UTILS_HAS_FROM_INT16_BUFFER (1)\n", "#endif\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## from_int32_buffer, from_uint32_buffer\n", "\n", "With the help of `utils.from_int32_buffer`, and `utils.from_uint32_buffer`, it is possible to convert 32-bit integer buffers to `ndarrays` of float type. These functions have a syntax similar to `numpy.frombuffer`; they support the `count=-1`, and `offset=0` keyword arguments. However, in addition, they also accept `out=None`, and `byteswap=False`. \n", "\n", "Here is an example without keyword arguments" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2021-03-05T06:53:26.256516Z", "start_time": "2021-03-05T06:53:26.007070Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a: bytearray(b'\\x01\\x01\\x00\\x00\\x00\\x00\\x00\\xff')\n", "\n", "unsigned integers: array([257.0, 4278190080.000001], dtype=float64)\n", "\n", "b: bytearray(b'\\x01\\x01\\x00\\x00\\x00\\x00\\x00\\xff')\n", "\n", "signed integers: array([257.0, -16777216.0], dtype=float64)\n", "\n", "\n" ] } ], "source": [ "%%micropython -unix 1\n", "\n", "from ulab import numpy as np\n", "from ulab import utils\n", "\n", "a = bytearray([1, 1, 0, 0, 0, 0, 0, 255])\n", "print('a: ', a)\n", "print()\n", "print('unsigned integers: ', utils.from_uint32_buffer(a))\n", "\n", "b = bytearray([1, 1, 0, 0, 0, 0, 0, 255])\n", "print('\\nb: ', b)\n", "print()\n", "print('signed integers: ', utils.from_int32_buffer(b))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The meaning of `count`, and `offset` is similar to that in `numpy.frombuffer`. `count` is the number of floats that will be converted, while `offset` would discard the first `offset` number of bytes from the buffer before the conversion.\n", "\n", "In the example above, repeated calls to either of the functions returns a new `ndarray`. You can save RAM by supplying the `out` keyword argument with a pre-defined `ndarray` of sufficient size, in which case the results will be inserted into the `ndarray`. If the `dtype` of `out` is not `float`, a `TypeError` exception will be raised." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2021-03-05T06:53:41.551440Z", "start_time": "2021-03-05T06:53:41.534163Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "b: bytearray(b'\\x01\\x00\\x01\\x00\\x00\\x01\\x00\\x01')\n", "a: array([65537.0, 16777472.0], dtype=float64)\n", "\n", "\n" ] } ], "source": [ "%%micropython -unix 1\n", "\n", "from ulab import numpy as np\n", "from ulab import utils\n", "\n", "a = np.array([1, 2], dtype=np.float)\n", "b = bytearray([1, 0, 1, 0, 0, 1, 0, 1])\n", "print('b: ', b)\n", "utils.from_uint32_buffer(b, out=a)\n", "print('a: ', a)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, since there is no guarantee that the endianness of a particular peripheral device supplying the buffer is the same as that of the microcontroller, `from_(u)intbuffer` allows a conversion via the `byteswap` keyword argument." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2021-03-05T06:53:52.242950Z", "start_time": "2021-03-05T06:53:52.229160Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a: bytearray(b'\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x01')\n", "buffer without byteswapping: array([1.0, 16777216.0], dtype=float64)\n", "buffer with byteswapping: array([16777216.0, 1.0], dtype=float64)\n", "\n", "\n" ] } ], "source": [ "%%micropython -unix 1\n", "\n", "from ulab import numpy as np\n", "from ulab import utils\n", "\n", "a = bytearray([1, 0, 0, 0, 0, 0, 0, 1])\n", "print('a: ', a)\n", "print('buffer without byteswapping: ', utils.from_uint32_buffer(a))\n", "print('buffer with byteswapping: ', utils.from_uint32_buffer(a, byteswap=True))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## from_int16_buffer, from_uint16_buffer\n", "\n", "These two functions are identical to `utils.from_int32_buffer`, and `utils.from_uint32_buffer`, with the exception that they convert 16-bit integers to floating point `ndarray`s. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.5" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": { "height": "calc(100% - 180px)", "left": "10px", "top": "150px", "width": "382.797px" }, "toc_section_display": true, "toc_window_display": true }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }