radio_calibrate.grc

options:
  parameters:
    author: ''
    category: '[GRC Hier Blocks]'
    cmake_opt: ''
    comment: ''
    copyright: ''
    description: ''
    gen_cmake: 'On'
    gen_linking: dynamic
    generate_options: no_gui
    hier_block_src_path: '.:'
    id: radio_calibrate
    max_nouts: '0'
    output_language: python
    placement: (0,0)
    qt_qss_theme: ''
    realtime_scheduling: ''
    run: 'True'
    run_command: '{python} -u {filename}'
    run_options: run
    sizing_mode: fixed
    thread_safe_setters: ''
    title: radio_calibrate
    window_size: ''
  states:
    bus_sink: false
    bus_source: false
    bus_structure: null
    coordinate: [8, 8]
    rotation: 0
    state: enabled

blocks:
- name: directory_name
  id: parameter
  parameters:
    alias: ''
    comment: ''
    hide: none
    label: directory_name
    short_id: ''
    type: str
    value: '"."'
  states:
    bus_sink: false
    bus_source: false
    bus_structure: null
    coordinate: [8, 205]
    rotation: 0
    state: true
- name: num_bins
  id: parameter
  parameters:
    alias: ''
    comment: ''
    hide: none
    label: num_bins
    short_id: ''
    type: intx
    value: '4096'
  states:
    bus_sink: false
    bus_source: false
    bus_structure: null
    coordinate: [9, 106]
    rotation: 0
    state: true
- name: save_calibration
  id: epy_block
  parameters:
    _source_code: "\"\"\"\nEmbedded Python Blocks:\n\nEach time this file is saved,\
      \ GRC will instantiate the first class it finds\nto get ports and parameters\
      \ of your block. The arguments to __init__  will\nbe the parameters. All of\
      \ them are required to have default values!\n\"\"\"\n\nimport numpy as np\n\
      import numpy.polynomial.polynomial as poly\nimport json\n\nfrom gnuradio import\
      \ gr\nimport pmt\n\nimport pathlib\n\n\nclass blk(gr.sync_block):\n    \"\"\"\
      Embedded Python Block - Calculate Calibration Values\"\"\"\n\n    def __init__(\n\
      \        self,\n        directory=\".\",\n        filename=\"calibration.json\"\
      ,\n        vec_length=4096,\n        poly_smoothing_order=25,\n    ):  # only\
      \ default arguments here\n        \"\"\"arguments to this function show up as\
      \ parameters in GRC\"\"\"\n        gr.sync_block.__init__(\n            self,\n\
      \            name=\"Embedded Python Block\",  # will show up in GRC\n      \
      \      in_sig=[(np.float32, vec_length)],\n            out_sig=None,\n     \
      \   )\n        # if an attribute with the same name as a parameter is found,\n\
      \        # a callback is registered (properties work, too).\n        self.directory\
      \ = directory\n        self.filename = filename\n        self.vec_length = vec_length\n\
      \        self.poly_smoothing_order = poly_smoothing_order\n        self.past_input\
      \ = np.zeros(vec_length)\n        self.num_past_input = 0\n\n    def work(self,\
      \ input_items, output_items):\n        \"\"\"Divide Input by Average, Determine\
      \ Calibration Power, and Save\"\"\"\n        for input_array in input_items[0]:\n\
      \            self.past_input += input_array\n            self.num_past_input\
      \ += 1\n            averaged_input = self.past_input / self.num_past_input\n\
      \            relative_freq_values = np.linspace(-1, 1, self.vec_length)\n  \
      \          poly_fit = poly.Polynomial.fit(\n                relative_freq_values,\
      \ averaged_input, self.poly_smoothing_order,\n            )\n            smoothed_input\
      \ = poly_fit(relative_freq_values)\n            average_value = np.average(smoothed_input)\n\
      \            rescaled_input = smoothed_input / average_value\n            file_output\
      \ = {\n                \"cal_pwr\": average_value,\n                \"cal_values\"\
      : rescaled_input.tolist(),\n            }\n            with open(pathlib.Path(self.directory,\
      \ self.filename), \"w\") as outfile:\n                json.dump(file_output,\
      \ outfile)\n        return len(input_items[0])\n"
    affinity: ''
    alias: ''
    comment: ''
    directory: directory_name
    filename: '''calibration.json'''
    maxoutbuf: '0'
    minoutbuf: '0'
    poly_smoothing_order: '25'
    vec_length: num_bins
  states:
    _io_cache: ('Embedded Python Block', 'blk', [('directory', "'.'"), ('filename',
      "'calibration.json'"), ('vec_length', '4096'), ('poly_smoothing_order', '25')],
      [('0', 'float', 4096)], [], 'Embedded Python Block - Calculate Calibration Values',
      ['directory', 'filename', 'poly_smoothing_order', 'vec_length'])
    bus_sink: false
    bus_source: false
    bus_structure: null
    coordinate: [492, 134]
    rotation: 0
    state: true
- name: zeromq_sub_source_0
  id: zeromq_sub_source
  parameters:
    address: tcp://127.0.0.1:5560
    affinity: ''
    alias: ''
    comment: ''
    hwm: '-1'
    maxoutbuf: '0'
    minoutbuf: '0'
    pass_tags: 'True'
    timeout: '100'
    type: float
    vlen: num_bins
  states:
    bus_sink: false
    bus_source: false
    bus_structure: null
    coordinate: [238, 134]
    rotation: 0
    state: true

connections:
- [zeromq_sub_source_0, '0', save_calibration, '0']

metadata:
  file_format: 1