95 lines
2.5 KiB
Python
95 lines
2.5 KiB
Python
import torch
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import matplotlib
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def get_random_messages(count, order):
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"""
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Generate a list of messages.
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:param count: Number of messages to generate.
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:param order: Number of possible messages.
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:return: One-dimensional vector with each entry being the index of the
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generated message which is between 0, inclusive, and `order`, exclusive.
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>>> get_random_messages(5)
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torch.tensor([0, 2, 0, 3, 4])
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"""
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return torch.randint(0, order, (count,))
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def messages_to_onehot(messages, order):
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"""
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Convert messages represented as indexes to one-hot encoding.
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:param messages: List of messages to convert.
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:param order: Number of possible messages.
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:return: One-hot encoded messages.
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>>> messages_to_onehot(torch.tensor([0, 2, 0, 3, 4]))
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torch.tensor([
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[1., 0., 0., 0., 0.],
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[0., 0., 1., 0., 0.],
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[1., 0., 0., 0., 0.],
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[0., 0., 0., 1., 0.],
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[0., 0., 0., 0., 1.],
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])
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"""
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return torch.nn.functional.one_hot(messages, num_classes=order).float()
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def plot_constellation(ax, constellation):
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ax.grid()
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order = len(constellation)
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color_map = matplotlib.cm.Dark2
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color_norm = matplotlib.colors.BoundaryNorm(range(order + 1), order)
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# Extend axes symmetrically around zero so that they fit data
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axis_extent = max(
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abs(constellation.min()),
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abs(constellation.max())
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) * 1.05
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ax.set_xlim(-axis_extent, axis_extent)
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ax.set_ylim(-axis_extent, axis_extent)
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# Hide borders but keep ticks
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for direction in ['left', 'bottom', 'right', 'top']:
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ax.axis[direction].line.set_color('#00000000')
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# Show zero-centered axes without ticks
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for direction in ['xzero', 'yzero']:
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axis = ax.axis[direction]
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axis.set_visible(True)
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axis.set_axisline_style('-|>')
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axis.major_ticklabels.set_visible(False)
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# Add axis names
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ax.annotate(
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'I', (1, 0.5), xycoords='axes fraction',
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xytext=(25, 0), textcoords='offset points',
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va='center', ha='right'
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)
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ax.annotate(
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'Q', (0.5, 1), xycoords='axes fraction',
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xytext=(0, 25), textcoords='offset points',
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va='center', ha='center'
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)
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ax.scatter(
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*zip(*constellation.tolist()),
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zorder=10,
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s=60,
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c=range(len(constellation)),
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edgecolor='black',
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cmap=color_map,
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norm=color_norm,
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)
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# Plot center
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center = constellation.sum(dim=0) / order
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ax.scatter(
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center[0], center[1],
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marker='X',
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)
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