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Moving phasefield figure
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#!/usr/bin/env python3
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__doc__ = \
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"""
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Generate a figure showing a value combining
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the delays between a transmitter and a set of antennas
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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from itertools import chain, combinations, product
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c_light = 3e8
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f_beacon = 50e6
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class Antenna:
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"""
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Simple Antenna class
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"""
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def __init__(self,x=0,y=0,z=0,t0=0,name=""):
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self.x = x
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self.y = y
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self.z = z
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self.t = t0
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self.name = name
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def __repr__(self):
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cls = self.__class__.__name__
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return f'{cls}(x={self.x!r},y={self.y!r},z={self.z!r},t0={self.t!r},name={self.name!r})'
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def phase_mod(phase, low=np.pi):
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"""
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Modulo phase such that it falls within the
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interval $[-low, 2\pi - low)$.
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"""
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return (phase + low) % (2*np.pi) - low
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def dist(a,b):
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return ((a.x-b.x)**2+(a.y-b.y)**2+(a.z-b.z)**2)**0.5
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def phase(a,b,f=f_beacon,wrap=False):
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t = dist(a,b)/c_light
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phase = t*f*2*np.pi
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if wrap:
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phase = phase_mod(phase)
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return phase
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def grid_plot(grid, ax=None, **plot_kwargs):
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if ax is None:
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ax = plt.gca()
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x = [a.x for a in grid]
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y = [a.y for a in grid]
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l = [a.name for a in grid]
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ax.plot(x,y,'kx', **plot_kwargs)
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for x_,y_,l_ in zip(x,y,l):
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ax.annotate(l_,(x_,y_))
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def antenna_combinations(ants, ref_ant=None):
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if ref_ant is not None: # use only one reference antenna for the baselines
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ref = ref_ant
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ant_combi = [ (ref, j) for j in ants if j is not ref ]
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else: # use all baselines
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ant_combi = combinations(ants, 2)
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return list(ant_combi)
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def calculate_field(field, tx, ant_combi, ref_ant=None, calculate_phase=True):
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if plot_phase:
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p_ij = [ (phase(tx,i) - phase(tx,j)) for i,j in ant_combi ]
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else:
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t_ij = [ (dist(tx,i) - dist(tx, j))/c_light for i,j in ant_combi ]
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val = []
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xx = []
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yy = []
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xs = field[0]
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ys = field[1]
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for x in xs:
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for y in ys:
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tx_t = Antenna(x=x,y=y)
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if plot_phase: # phase
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dp_ij = np.array([ (phase(tx_t,i) - phase(tx_t,j)) - p_ij[k] for k,(i,j) in enumerate(ant_combi) ])
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if True: # phase wrap
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dp_ij = phase_mod(dp_ij)
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val.append(np.sum(dp_ij**2)**0.5)
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else: # time
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dt_ij = np.array([ (dist(tx_t,i) - dist(tx_t, j))/c_light - t_ij[k] for k,(i,j) in enumerate(ant_combi) ])
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val.append(np.sum(dt_ij**2)**0.5)
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xx.append(x)
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yy.append(y)
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return np.array(xx), np.array(yy), np.array(val)
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def plot_field(tx, ants, xx, yy, val, ax=None, ref_ant=None, color_label='$\\left( t - \\tau \\right)^2$', plot_phase=None, mask=None,**scatter_kwargs):
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if ax is None:
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ax = plt.gca()
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default_scatter_kwargs = {}
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default_scatter_kwargs['cmap'] = 'Spectral_r'
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if mask is not None:
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val[mask] = np.nan
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if plot_phase is None:
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pass
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elif plot_phase:
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default_scatter_kwargs['vmax'] = len(ants)*np.pi
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#default_scatter_kwargs['cmap'] = 'gray'
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pass
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scatter_kwargs = {**default_scatter_kwargs, **scatter_kwargs}
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grid_plot([tx] + ants, ax=ax)
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if ref_ant is not None:
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ax.set_title("Single reference antenna: {}, f: {}MHz".format(ref_ant.name, f_beacon/1e6))
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else:
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ax.set_title("All baselines f: {} MHz".format(f_beacon/1e6))
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sc = ax.scatter(xx,yy,c=val, **scatter_kwargs)
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fig = ax.get_figure()
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fig.colorbar(sc, ax=ax, label=color_label)
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return ax
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def square_grid(dx=1, N_x=10, dy=None, N_y=None, x_start=0, y_start=0):
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N_y = N_x if N_y is None else N_y
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dy = dx if dy is None else dy
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print([(N_x,N_y), (dx,dy), (x_start,y_start)])
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return product(
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(x_start + n*dx for n in range(N_x)),
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(y_start + n*dy for n in range(N_y)),
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)
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def triangular_grid(dx=1, N_x=10, dy=None, N_y=None, x_start=0, y_start=0):
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return chain(
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square_grid(dx=dx,dy=dy,N_x=N_x,N_y=N_y,x_start=x_start,y_start=y_start),
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square_grid(dx=dx,dy=dy,N_x=N_x,N_y=N_y,x_start=x_start + dx/2,y_start=y_start + dy/2),
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)
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if __name__ == "__main__":
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from argparse import ArgumentParser
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import os.path as path
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parser = ArgumentParser(description=__doc__)
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parser.add_argument("fname", metavar="path/to/figure[/]", nargs="?", help="Location for generated figure, will append __file__ if a directory. If not supplied, figure is shown.")
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parser.add_argument("type", choices=['single-left', 'single-center', 'square', 'tri', 'preset'])
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command_group = parser.add_mutually_exclusive_group(required=True)
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command_group.add_argument('--time', help='Use the time difference for the field', action='store_false')
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command_group.add_argument('--phase', help='Use wrapped phase for the field', action='store_true')
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parser.add_argument('--ref', dest='ref_ant', metavar='ref_antenna', help='Number of antenna to use as reference')
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args = parser.parse_args()
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if args.fname is not None and path.isdir(args.fname):
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args.fname = path.join(args.fname, path.splitext(path.basename(__file__))[0] + ".pdf")
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args.plot_phase = args.phase or args.time
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del args.time, args.phase
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if 'single' in args.type: # single baseline
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### Field
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x_low, x_high, N_x = -300, 300, 81
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y_low, y_high, N_y = -300, 300, 81
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### Geometry
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ants = [
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Antenna(x=-50,y=0,z=0,name="a"),
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Antenna(x=50,y=0,z=0,name="b"),
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]
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if args.type == 'single-center':
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tx = Antenna(x=-000,y=200,z=0,name="tx")
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else:
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tx = Antenna(x=-200,y=200,z=0,name="tx")
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elif args.type == 'square' or args.type == 'tri': # from grid definition
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### Field
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x_low, x_high, N_x = -1800, 1800, 161
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y_low, y_high, N_y = -x_low, -x_high, N_x
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### Geometry
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tx = Antenna(x=-800,y=300,z=0,name="tx")
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x_start, dx, ant_N_x = 0, 50, 2
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y_start, dy, ant_N_y = 0, dx, ant_N_x
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if args.type == 'square': # square grid
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grid_func = square_grid
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elif args.type == 'tri': # triangular
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grid_func = triangular_grid
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grid = grid_func(dx=dx, dy=dy, N_x=ant_N_x, N_y=ant_N_y, x_start=x_start, y_start=y_start)
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ants = [ Antenna(x=x,y=y,z=0,name=i) for i, (x,y) in enumerate(grid) ]
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else:
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### Field
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x_low, x_high, N_x = -400, 400, 161
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y_low, y_high, N_y = -x_low, -x_high, N_x
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### Geometry
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tx = Antenna(x=-300,y=300,z=0,name="tx")
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ants = [
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Antenna(x=100,y=0,z=0,name="a"),
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Antenna(x=0,y=-50,z=0,name="b"),
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Antenna(x=+50,y=-180,z=0,name="c"),
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Antenna(x=125,y=180,z=0,name="d"),
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]
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###
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### Options
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###
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plot_phase = args.plot_phase
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ref_ant = args.ref_ant
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ant_combi = antenna_combinations(ants, ref_ant=ref_ant)
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xs = np.linspace(x_low, x_high, N_x)
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ys = np.linspace(y_low, y_high, N_y)
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xx, yy, val = calculate_field((xs, ys), tx, ant_combi, calculate_phase=plot_phase)
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mask = None
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if False and plot_phase:
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mask = abs(val) > np.pi
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kwargs = {}
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if plot_phase:
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color_label='$\\sqrt{ \\sum \\left(\\varphi(x) - \\Delta \\varphi\\right)^2}$'
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else:
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color_label='$\\sqrt{ \\sum \\left(t(x) - \\Delta t\\right)^2}$ [ns]'
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val *= 1e9
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kwargs['vmax'] = 100
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ax = plot_field(tx, ants, xx, yy, val, ax=None, ref_ant=ref_ant, mask=mask, color_label=color_label, **kwargs)
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# if plot_phase:
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# N_lowest = np.min(len(ant_combi)-1, 10)
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# lowest_idx = np.argpartition(val, N_lowest)[:N_lowest]
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#
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# print(lowest_idx)
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# print(val[lowest_idx])
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# print( list(zip(np.array(xx)[lowest_idx], np.array(yy)[lowest_idx])) )
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if args.fname is not None:
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plt.savefig(args.fname)
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else:
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plt.show()
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