'3,0',
])
#=================================================================================================#
# Prepare reference data. #
#=================================================================================================#
#ref_folder = 'RobotArena/{0}/'.format(sys.argv[1].strip())
ref_data = np.zeros((len(ref_folders), len(ROUTE), 3))
# stack the route from each folder up along the 3rd axis
for repeat, ref_folder in enumerate(ref_folders):
for filename in os.listdir(ref_folder):
file_path = os.path.join(ref_folder, filename)
if os.path.isfile(file_path): # no folders (just in case)
summary = mflog_utils.summarise_file(file_path)
# put the data in this file at the right position along the route
index = np.where(ROUTE == summary['location'])
ref_data[repeat, index, :] = [
summary['x']['median'],
summary['y']['median'],
summary['z']['median'],
]
# take the diff of each repeat at once and take their mean
# ref_diff = np.insert(np.diff(ref_data, axis=1), 0, 0, axis=1)
ref_diff = np.diff(ref_data, axis=1)
ref_diff = np.mean(ref_diff, axis=0)
from mpl_toolkits.mplot3d import Axes3D
import mflog_utils
summaries = {}
# run numbers to use
run_numbers = [int(num) for num in sys.argv[1:-1]]
for run_number in run_numbers:
for dirpath, _, filenames in os.walk('RobotArena/' + str(run_number)):
# Yay, order!
print('Doing run #' + str(run_number))
summaries[run_number] = {}
for file in filenames:
summary = mflog_utils.summarise_file(os.path.join(dirpath, file))
summaries[run_number][summary['location']] = summary
# just the once - no subdirs
break
print('Got {} runs'.format(len(summaries)))
# matplotlib setup
mpl.rc('font', family='Arial')
#plt.style.use('ggplot')
fig, ax = plt.subplots(len(summaries), 3, figsize=(15, 2.5 * len(summaries) + 2), squeeze=False,
sharex='col', sharey='row')
ax[-1, 1].set_xlabel('Position on path around robot arena', size='x-large')
ax[0, 0].set_title('x', fontsize=16)
import os
import numpy as np
import mflog_utils
import tabulate
files = []
for dirpath, _, filenames in os.walk('./TimeTesting'):
for filename in filenames:
if filename.endswith('.mflog'):
files.append(os.path.join(dirpath, filename))
break
tests = []
for filename in files:
summary, data = mflog_utils.summarise_file(filename, True)
tests.append([summary['duration'], summary['sample_count'], summary['x']['median'],
summary['x']['range'], summary['x']['std']**2])
tests.sort()
print(tabulate.tabulate(tests,
headers=('Duration', 'Samples', 'Median (x)', 'Range (x)', 'Var (x)')))
with open('./TimeTesting/summary.csv', 'w') as out:
for test in tests:
out.write(','.join([str(t) for t in test]) + '\n')
def draw_xyz_plot(files,
save=None,
location_as_label=False,
label_prefix='L',
dim_height=3,
colors=mflog_utils.tableau20[0::2]):
""" Draws a grid of plots, with a row for each file's x, y and z dimensions. `files` is a
string list of names of .mflog files. If `save` is given and is a string, the plot is
saved to `save`.
"""
matplotlib.rc('font', family='Arial', weight='bold')
#plt.style.use('ggplot')
figure, axes = plt.subplots(len(files),
3,
sharex='col',
figsize=(12, dim_height * len(files)),
squeeze=False)
axes[0, 0].set_title('x', size=24, position=[0.5, 1.05])
axes[0, 1].set_title('y', size=24, position=[0.5, 1.05])
axes[0, 2].set_title('z', size=24, position=[0.5, 1.05])
axes[-1, 0].set_xlabel(u'μT', fontweight='bold', fontsize=16)
axes[-1, 1].set_xlabel(u'μT', fontweight='bold', fontsize=16)
axes[-1, 2].set_xlabel(u'μT', fontweight='bold', fontsize=16)
location_keys = {}
for (file_index, file_name) in enumerate(files):
summary, data = mflog_utils.summarise_file(file_name,
include_data=True)
if location_as_label:
location_key = summary['location']
else:
location_key = label_prefix + str(file_index)
location_keys[location_key] = summary
axes[file_index, 0].set_ylabel(location_key,
rotation=0,
size=20,
labelpad=40)
for dimension in range(3):
these_axes = axes[file_index, dimension]
these_axes.tick_params(axis='y',
which='both',
left='off',
right='off',
labelleft='off')
these_axes.tick_params(axis='x',
which='both',
top='off',
labelsize=16)
these_axes.xaxis.grid(True)
#these_axes.get_xaxis().tick_bottom()
#these_axes.get_yaxis().tick_left()
# Good to disable spines in default style
# these_axes.spines["top"].set_visible(False)
# #these_axes.spines["bottom"].set_visible(False)
# these_axes.spines["right"].set_visible(False)
# these_axes.spines["left"].set_visible(False)
# these_axes.hist(data.T[dimension], 25, normed=1,
# color=mflog_utils.tableau20[0::2][file_index % 10], linewidth=0)
these_axes.hist(data.T[dimension],
25,
normed=1,
color=colors[file_index % len(colors)],
linewidth=0)
figure.tight_layout()
if isinstance(save, str):
plt.savefig(save + '.png') # woo, duck typing
save_meta_file(save + '.txt', location_keys)
plt.show()
mean_6090 = np.mean(data[3048:, :], axis=0)
with open(save_name + '.txt', 'w') as f:
f.write(title + '\n\n')
f.write('dim,all,-,0-30,-,30-60,-,60-90,-\n')
for i in range(3):
f.write('{},{},{},{},{},{},{},{},{}\n'.format(
dims[i],
mean_full[i],
stds_full[i],
mean_0030[i],
stds_0030[i],
mean_3060[i],
stds_3060[i],
mean_6090[i],
stds_6090[i],
))
plt.savefig(save_name + 'png')
plt.show()
if __name__ == '__main__':
_, data = mflog_utils.summarise_file('./PeopleTesting/Experiment1.mflog',
include_data=True)
plot_xyz(data, 'People Experiment 1', 'Plots/final/people1')
_, data = mflog_utils.summarise_file('./PeopleTesting/Experiment2.mflog',
include_data=True)
plot_xyz(data, 'People Experiment 2', 'Plots/final/people2')
color=spot_detail[1],
zorder=0)
ax.add_patch(spot)
art3d.patch_2d_to_3d(spot, z=0)
# Read files
arrow_magnitudes = np.zeros((16, 3))
arrow_positions = np.zeros((16, 3))
arrows = None # for now
first_file_activity = ''
first_file_datetime = ''
first_file_filename = ''
for file in files:
# pylint: disable=invalid-sequence-index
summary = mflog_utils.summarise_file(file)
# The location of arena files is set to "x,y" where x and y are integers between 0 and 3
locx, locy = summary['location'].split(',', 1)
locx = int(locx)
locy = int(locy)
if locx == 0 and locy == 0:
# The first file!
first_file_activity = summary['activity']
first_file_datetime = summary['time_string']
first_file_filename = file.split('/')[-1].split('.')[0]
# Get the position of this arrow in the same order as the spots
ordinal = locy * 4 + locx
for dirpath, _, filenames in os.walk('RobotArena'):
# Assuming we never revisit the same directory
dirpath_parts = list(filter(None, dirpath.split('\\')))
# First item yielded by walk is just the "RobotArena" directory. No want.
if len(dirpath_parts) < 2:
continue
else:
run_number = int(dirpath_parts[1])
# Yay, order!
print('Doing run #' + str(run_number))
if run_number == TEST_RUN_NUMBER:
for file in filenames:
summary, data = mflog_utils.summarise_file(os.path.join(dirpath, file), True)
# guaranteed only once
post_data[summary['location']] = data
if summary['location'] == '0,0': # first point
post_file_meta = {
'activity': summary['room'],
'time_string': summary['time_string']
}
else:
for file in filenames:
summary, data = mflog_utils.summarise_file(os.path.join(dirpath, file), True)
coords = summary['location']
if coords not in prior_data:
