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-#
-# Copyright 2008, 2009 Free Software Foundation, Inc.
-#
-# This file is part of GNU Radio
-#
-# GNU Radio is free software; you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation; either version 3, or (at your option)
-# any later version.
-#
-# GNU Radio is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with GNU Radio; see the file COPYING. If not, write to
-# the Free Software Foundation, Inc., 51 Franklin Street,
-# Boston, MA 02110-1301, USA.
-#
-
-##################################################
-# conditional disconnections of wx flow graph
-##################################################
-import wx
-from gnuradio import gr
-from gnuradio import blocks
-
-RUN_ALWAYS = gr.prefs().get_bool('wxgui', 'run_always', False)
-
-
-class wxgui_hb(object):
- """
- The wxgui hier block helper/wrapper class:
- A hier block should inherit from this class to make use of the wxgui connect method.
- To use, call wxgui_connect in place of regular connect; self.win must be defined.
- The implementation will conditionally enable the copy block after the source (self).
- This condition depends on weather or not the window is visible with the parent notebooks.
- This condition will be re-checked on every ui update event.
- """
-
- def wxgui_connect(self, *points):
- """
- Use wxgui connect when the first point is the self source of the hb.
- The win property of this object should be set to the wx window.
- When this method tries to connect self to the next point,
- it will conditionally make this connection based on the visibility state.
- All other points will be connected normally.
- """
- try:
- assert points[0] == self or points[0][0] == self
- copy = blocks.copy(self.input_signature().sizeof_stream_item(0))
- handler = self._handler_factory(copy.set_enabled)
- if not RUN_ALWAYS:
- handler(False) # initially disable the copy block
- else:
- handler(True) # initially enable the copy block
- self._bind_to_visible_event(win=self.win, handler=handler)
- points = list(points)
- points.insert(1, copy) # insert the copy block into the chain
- except (AssertionError, IndexError): pass
- self.connect(*points) # actually connect the blocks
-
- @staticmethod
- def _handler_factory(handler):
- """
- Create a function that will cache the visibility flag,
- and only call the handler when that flag changes.
-
- Args:
- handler: the function to call on a change
-
- Returns:
- a function of 1 argument
- """
- cache = [None]
-
- def callback(visible):
- if cache[0] == visible: return
- cache[0] = visible
- # print visible, handler
- if not RUN_ALWAYS:
- handler(visible)
- else:
- handler(True)
- return callback
-
- @staticmethod
- def _bind_to_visible_event(win, handler):
- """
- Bind a handler to a window when its visibility changes.
- Specifically, call the handler when the window visibility changes.
- This condition is checked on every update ui event.
-
- Args:
- win: the wx window
- handler: a function of 1 param
- """
- # is the window visible in the hierarchy
- def is_wx_window_visible(my_win):
- while True:
- parent = my_win.GetParent()
- if not parent: return True # reached the top of the hierarchy
- # if we are hidden, then finish, otherwise keep traversing up
- if isinstance(parent, wx.Notebook) and parent.GetCurrentPage() != my_win: return False
- my_win = parent
- # call the handler, the arg is shown or not
- def handler_factory(my_win, my_handler):
- def callback(evt):
- my_handler(is_wx_window_visible(my_win))
- evt.Skip() # skip so all bound handlers are called
- return callback
- handler = handler_factory(win, handler)
- # bind the handler to all the parent notebooks
- win.Bind(wx.EVT_UPDATE_UI, handler)
-
-##################################################
-# Helpful Functions
-##################################################
-
-# A macro to apply an index to a key
-index_key = lambda key, i: "%s_%d" % (key, i+1)
-
-
-def _register_access_method(destination, controller, key):
- """
- Helper function for register access methods.
- This helper creates distinct set and get methods for each key
- and adds them to the destination object.
- """
- def set(value): controller[key] = value
- setattr(destination, 'set_'+key, set)
- def get(): return controller[key]
- setattr(destination, 'get_'+key, get)
-
-
-def register_access_methods(destination, controller):
- """
- Register setter and getter functions in the destination object for all keys in the controller.
-
- Args:
- destination: the object to get new setter and getter methods
- controller: the pubsub controller
- """
- for key in controller.keys(): _register_access_method(destination, controller, key)
-
-##################################################
-# Input Watcher Thread
-##################################################
-from gnuradio import gru
-
-
-class input_watcher(gru.msgq_runner):
- """
- Input watcher thread runs forever.
- Read messages from the message queue.
- Forward messages to the message handler.
- """
- def __init__ (self, msgq, controller, msg_key, arg1_key='', arg2_key=''):
- self._controller = controller
- self._msg_key = msg_key
- self._arg1_key = arg1_key
- self._arg2_key = arg2_key
- gru.msgq_runner.__init__(self, msgq, self.handle_msg)
-
- def handle_msg(self, msg):
- if self._arg1_key: self._controller[self._arg1_key] = msg.arg1()
- if self._arg2_key: self._controller[self._arg2_key] = msg.arg2()
- self._controller[self._msg_key] = msg.to_string()
-
-
-##################################################
-# Shared Functions
-##################################################
-import numpy
-import math
-
-
-def get_exp(num):
- """
- Get the exponent of the number in base 10.
-
- Args:
- num: the floating point number
-
- Returns:
- the exponent as an integer
- """
- if num == 0: return 0
- return int(math.floor(math.log10(abs(num))))
-
-
-def get_clean_num(num):
- """
- Get the closest clean number match to num with bases 1, 2, 5.
-
- Args:
- num: the number
-
- Returns:
- the closest number
- """
- if num == 0: return 0
- sign = num > 0 and 1 or -1
- exp = get_exp(num)
- nums = numpy.array((1, 2, 5, 10))*(10**exp)
- return sign*nums[numpy.argmin(numpy.abs(nums - abs(num)))]
-
-
-def get_clean_incr(num):
- """
- Get the next higher clean number with bases 1, 2, 5.
-
- Args:
- num: the number
-
- Returns:
- the next higher number
- """
- num = get_clean_num(num)
- exp = get_exp(num)
- coeff = int(round(num/10**exp))
- return {
- -5: -2,
- -2: -1,
- -1: -.5,
- 1: 2,
- 2: 5,
- 5: 10,
- }[coeff]*(10**exp)
-
-
-def get_clean_decr(num):
- """
- Get the next lower clean number with bases 1, 2, 5.
-
- Args:
- num: the number
-
- Returns:
- the next lower number
- """
- num = get_clean_num(num)
- exp = get_exp(num)
- coeff = int(round(num/10**exp))
- return {
- -5: -10,
- -2: -5,
- -1: -2,
- 1: .5,
- 2: 1,
- 5: 2,
- }[coeff]*(10**exp)
-
-
-def get_min_max(samples):
- """
- Get the minimum and maximum bounds for an array of samples.
-
- Args:
- samples: the array of real values
-
- Returns:
- a tuple of min, max
- """
- factor = 2.0
- mean = numpy.average(samples)
- std = numpy.std(samples)
- fft = numpy.abs(numpy.fft.fft(samples - mean))
- envelope = 2*numpy.max(fft)/len(samples)
- ampl = max(std, envelope) or 0.1
- return mean - factor*ampl, mean + factor*ampl
-
-
-def get_min_max_fft(fft_samps):
- """
- Get the minimum and maximum bounds for an array of fft samples.
-
- Args:
- samples: the array of real values
-
- Returns:
- a tuple of min, max
- """
- # get the peak level (max of the samples)
- peak_level = numpy.max(fft_samps)
- # separate noise samples
- noise_samps = numpy.sort(fft_samps)[:len(fft_samps)/2]
- # get the noise floor
- noise_floor = numpy.average(noise_samps)
- # get the noise deviation
- noise_dev = numpy.std(noise_samps)
- # determine the maximum and minimum levels
- max_level = peak_level
- min_level = noise_floor - abs(2*noise_dev)
- return min_level, max_level