def callback(self, day, day_fraction, status, positions, home, work, plt,
**ignore_other_kwargs):
""" This gets called after each computation cycle (see pandemic/simulation.py) """
from pandemic.metrics import collision_count
cc = collision_count(positions=positions,
status=status,
precision=self.params['geometry']['p'])
self.collision_history.append(cc)
if day_fraction == 0:
# Daily collision TS
self.collision_daily_history.append(
sum(self.collision_history[-self.params['motion']['t']:]))
# Standard plot of infections
metrics = status_counts(status=status)
self.metric_history.append(metrics)
self.time_history.append(day + day_fraction)
self.axs[0][0].clear
plot_points(plt=self.axs[0][0],
positions=positions,
status=status,
title='Ornstein-Uhlenbeck')
self.axs[0][0].figure
# Standard plot of vulnerable only
metrics = status_counts(status=status)
vulnerable_positions = [
pos for pos, s in zip(positions, status) if s == 0
]
vulnerable_status = [s for s in status if s == 0]
# Counts plot
self.metric_history.append(metrics)
self.time_history.append(day + day_fraction)
self.axs[1][0].clear()
plot_points(plt=self.axs[1][0],
positions=vulnerable_positions,
status=vulnerable_status,
title='Vulnerable')
self.axs[1][0].figure
# Growth curve
infect = [m[1] for m in self.metric_history]
self.axs[0][1].plot(self.time_history, infect, color=self.color)
#self.axs[0][1].set_yscale('log')
self.axs[0][1].set_title('Infected')
self.axs[0][1].figure
if day > 1:
# Collisions curve
self.axs[1][1].plot(self.collision_daily_history,
color=self.color)
self.axs[1][1].set_title('Collisions per day')
self.axs[1][1].set_xlabel('Days since ' +
str(self.params['geometry']['i']) +
' cases.')
self.plt.show(block=False)
self.plt.pause(0.1)
def plot_data_points(self):
"""Plot the location of the data points in (H, Hr) or (Hc, Hb) space.
"""
self.send_latest_data.emit()
plotting.plot_points(ax=self.p_map.axes,
forc=self.data_queue.get(),
coordinates=self.coordinates())
self.tabWidget.setCurrentIndex(1)
return
def one_height_slice(mesh,
begin_height,
box_size,
box_height,
vectors=None,
fraction=3,
debug=False):
if vectors is None:
vectors = mesh.vectors.copy()
x_min, x_max, y_min, y_max, z_min, z_max = find_mins_maxs(mesh)
step = box_height // fraction
height = begin_height
slice_plane, vectors = one_slice(vectors,
height,
x_min,
x_max,
y_min,
y_max,
box_size,
debug=debug)
for iter in range(fraction - 2):
height += step
t_slice_plane, vectors = one_slice(vectors,
height,
x_min,
x_max,
y_min,
y_max,
box_size,
debug=debug)
slice_plane += t_slice_plane
t_slice_plane, vectors = one_slice(vectors,
begin_height + box_height,
x_min,
x_max,
y_min,
y_max,
box_size,
debug=debug)
slice_plane += t_slice_plane
slice_plane[slice_plane != 0] = 1
plot_points(slice_plane, debug=debug)
return slice_plane, vectors
#plot_points(points_0_30 + points_50_30 + points_100_30, "30 degrees")
#plot_points(points_0_45 + points_50_45 + points_100_45, "45 degrees")
#plot_points(points_0_60 + points_50_60 + points_100_60, "60 degrees")
#plot_points(points_0_75 + points_50_75 + points_100_75, "75 degrees")
#plot_with_TSTR_fit(points_0_30 + points_50_30 + points_100_30, "30 degrees, Fitted")
#plot_with_TSTR_fit(points_0_45 + points_50_45 + points_100_45, "45 degrees, Fitted")
#plot_with_TSTR_fit(points_0_60 + points_50_60 + points_100_60, "60 degrees, Fitted")
#plot_with_TSTR_fit(points_0_75 + points_50_75 + points_100_75, "75 degrees, Fitted")
fit_plot_100 = False
if fit_plot_100:
#plot_points(points_100, "TSTR Fit")
plot_with_TSTR_fit(points_100_60, "TSTR Fit")
fit_plot_0 = False
if fit_plot_0:
plot_points(points_0, "TSTR Fit")
#plot_with_TSTR_fit(points_100_60, "TSTR Fit")
"""
plot_points(points_mineral_oil_30 + points_100_30, "")
plot_points(points_mineral_oil_45 + points_100_45, "")
plot_points(points_mineral_oil_52_5 + points_100_52_5, "")
plot_points(points_mineral_oil_60 + points_100_60, "")
plot_points(points_mineral_oil_75 + points_100_75, "")
"""
#plot_points(points, "TSTR Fit")
#plot_with_TSTR_fit(points_100, "TSTR Fit")
405, photodiode_solid_angle,
photodiode_angular_width,
"60 degrees, relative to rotation stage")
points_75_rot = make_points(data_75_rot[0], 0, 75, 1, 0.5, data_75_rot[1],
405, photodiode_solid_angle,
photodiode_angular_width,
"75 degrees, relative to rotation stage")
all_points = points_30 + points_45 + points_60 + points_75
all_points_rot = points_30_rot + points_45_rot + points_60_rot + points_75_rot
plot_1 = False
if plot_1:
#plot_points(points_30_rot, "30 degrees")
plot_points(all_points_rot, "all points rotation stage angle")
plot_points(all_points, "all points")
plt.show()
fit = True
if fit:
fit_30 = TSTR_fit.fit_parameters(points_30)
fit_45 = TSTR_fit.fit_parameters(points_45)
fit_60 = TSTR_fit.fit_parameters(points_60)
fit_75 = TSTR_fit.fit_parameters(points_75)
plot_1b = False
if plot_1b:
plot_TSTR_fit_one_set_of_parameters(points_30, fit_30, "30 degrees")
plot_TSTR_fit_one_set_of_parameters(points_45, fit_45, "45 degrees")
plot_TSTR_fit_one_set_of_parameters(points_60, fit_60, "60 degrees")
from data import load_position from detect import find_candidate_lines from plotting import imshow, plot_points, plot_lines from chessboard import Chessboard import matplotlib.pyplot as plt import skimage position_name = 'roy_lopez_marshall_attack.png' orig = skimage.transform.rotate(load_position(position_name), 0) lines = find_candidate_lines(orig) chessboard = Chessboard(lines) fig, ax = plt.subplots() imshow(ax, orig) plot_lines(ax, lines, orig) plot_points(ax, chessboard.all_intersections()) plt.show()
for entry in file_data:
filename = entry[0]
flux_i = entry[1]
# product of this and measured voltage is (flux/str)/flux_i, flux in units of amps
# intensity_factor * V = (V * sensitivity / photodiode_solid_angle) / flux_i
intensity_factor = sensitivity / (photodiode_solid_angle * flux_i)
data_arr_i = make_data_by_run(filename, -35, 90, intensity_factor)
for data in data_arr_i:
if not get_entry_or_default(use_arr, ii, default=False):
ii += 1
continue
if sub_avg:
y_avg = TSTR_fit.average_by_angle(data[0], data[1], avg_angle)
y_sub = [data_i - avg_i for data_i, avg_i in zip(data[1], y_avg)]
data_add = [data[0], y_avg]
else:
data_add = data
leg_i = get_entry_or_default(leg_arr, ii, default="")
theta_i = get_entry_or_default(theta_i_arr, ii, default=0.)
n_i = get_entry_or_default(n_arr, ii, default=1.)
pol_i = get_entry_or_default(pol_arr, ii, default=0.5)
points_arr += make_points(data_add[0], 0, theta_i, n_i, pol_i,
data_add[1], wavelength,
photodiode_solid_angle,
photodiode_angular_width, leg_i)
ii += 1
plot_points(points_arr, title, log=False, show=False, draw_lines=True)
#plot_points(points_arr, "120 Grit Diffuse Reflector", log=False, show=False)
plt.show()
points_coarse_30 = make_points(data_coarse_30[0], 0, 30, 1.47399, 0.5,
data_coarse_30[1], 405,
photodiode_solid_angle,
photodiode_angular_width,
"30 degrees, 120 grit sample")
points_coarse_45 = make_points(data_coarse_45[0], 0, 45, 1.47399, 0.5,
data_coarse_45[1], 405,
photodiode_solid_angle,
photodiode_angular_width,
"45 degrees, 120 grit sample")
points_coarse_60 = make_points(data_coarse_60[0], 0, 60, 1.47399, 0.5,
data_coarse_60[1], 405,
photodiode_solid_angle,
photodiode_angular_width,
"60 degrees, 120 grit sample")
all_points_fine = points_fine_30 + points_fine_45 + points_fine_60 + points_fine_75
all_points_coarse = points_coarse_30 + points_coarse_45 + points_coarse_60
plot_points(all_points_fine,
"1500 Grit Diffuse Reflector",
log=False,
show=False)
plot_points(all_points_coarse,
"120 Grit Diffuse Reflector",
log=False,
show=False)
plt.show()
data_2_75[0], 0, 75, 1.47399, 0.5, data_2_75[1], 405,
photodiode_solid_angle, photodiode_angular_width,
"75 degrees, 120 grit sample, rotated 45 degrees")
all_points_coarse = points_coarse_30 + points_coarse_45 + points_coarse_60
all_points_1 = points_1_30 + points_1_45 + points_1_60 + points_1_75
all_points_2 = points_2_30 + points_2_45 + points_2_60 + points_2_75
all_points = all_points_coarse + all_points_1 + all_points_2
make_plots = False
if make_plots:
plot_points(points_coarse_30 + points_1_30 + points_2_30,
"120 Grit Diffuse Reflector 30 Degrees",
log=False,
show=False)
plot_points(points_coarse_45 + points_1_45 + points_2_45,
"120 Grit Diffuse Reflector 45 Degrees",
log=False,
show=False)
plot_points(points_coarse_60 + points_1_60 + points_2_60,
"120 Grit Diffuse Reflector 60 Degrees",
log=False,
show=False)
plot_points(points_1_75 + points_2_75,
"120 Grit Diffuse Reflector 75 Degrees",
log=False,
show=False)
plt.show()
"""
data_old_walls = make_data_by_run("background in mineral oil no sample old walls new walls lens tubes.txt", -90, 90, intensity_factor_no_tube)[2]
data_new_walls = make_data_by_run("background in mineral oil no sample old walls new walls lens tubes.txt", -90, 90, intensity_factor_no_tube)[1]
data_with_tube = make_data_by_run("background in mineral oil no sample old walls new walls lens tubes.txt", -90, 90, intensity_factor_with_tube)[0]
data_older_without_cone = make_data_by_run("mineral oil background with and without cone.txt", -90, 90, intensity_factor_older)[0]
data_older_with_cone = make_data_by_run("mineral oil background with and without cone.txt", -90, 90, intensity_factor_older)[1]
points_old_walls = make_points(data_old_walls[0], 0, 90, 1.47399, 0.5, data_old_walls[1], 405,
photodiode_solid_angle, photodiode_angular_width, "cardboard walls")
points_new_walls = make_points(data_new_walls[0], 0, 90, 1.47399, 0.5, data_new_walls[1], 405,
photodiode_solid_angle, photodiode_angular_width, "new walls")
points_with_tube = make_points(data_with_tube[0], 0, 90, 1.47399, 0.5, data_with_tube[1], 405,
photodiode_solid_angle, photodiode_angular_width, "new walls with cone of darkness")
points_older_without_cone = make_points(data_older_without_cone[0], 0, 90, 1.47399, 0.5, data_older_without_cone[1],
405, photodiode_solid_angle, photodiode_angular_width, "older without cone")
points_older_with_cone = make_points(data_older_with_cone[0], 0, 90, 1.47399, 0.5, data_older_with_cone[1],
405, photodiode_solid_angle, photodiode_angular_width, "older with cone")
all_points = points_old_walls + points_new_walls + points_with_tube
#plot_points(points_old_walls + points_new_walls + points_with_tube, "Newer Background Tests", log=False, show=False)
#plot_points(points_older_with_cone + points_older_without_cone, "Older Background Tests", log=False, show=False)
#plot_points(points_older_with_cone + points_older_without_cone + points_new_walls + points_with_tube, "Old Cone vs New Cone", log=False, show=False)
plot_points(points_older_without_cone + points_new_walls, "Old vs New Without Cone", log=False, show=False)
plot_points(points_older_with_cone + points_with_tube, "Old vs New With Cone", log=False, show=False)
plt.show()
# Parameters.
data_folder = '../data/'
dataset_name = 'cluster_harder' # Select either 'cluster_easy', 'cluster_harder', 'camel'.
C = 1
#kernel_func = functools.partial(rbf, gamma=1e3) # Use this for camel data.
kernel_func = linear # Use this for clusters data.
output_path = '../outputs/' # Where to save the plots.
class_colors = {-1: 'b', 1: 'r'} # Colors for plotting.
# Load data.
x_train, y_train = load_data_csv(os.path.join(data_folder, dataset_name+'_train.csv'))
x_test, y_test = load_data_csv(os.path.join(data_folder, dataset_name+'_test.csv'))
plot_points(x_train, y_train, class_colors=class_colors, title='Train - correct labels')
plot_points(x_test, y_test, class_colors=class_colors, title='Test - correct labels')
# Train the SVM classifier on the training data.
C_group = [1e-4, 1e-3, 1e-2, 1e-1, 1, 1e1, 1e2, 1e3, 1e4]
for i in range(len(C_group)):
C = C_group[i]
svm = SVM(kernel_func=kernel_func, C=C)
print('Training...')
svm.train(x_train, y_train)
print('Plotting...')
plot_svm_decision_boundary(svm, x_train, y_train,
title='SVM decision boundary on training data', output_path=output_path,
file_name=str(dataset_name) + '_support_vectors_train.png',
class_colors=class_colors)
def generate(npoints=50):
'''
generate a set of 50 points with
parameters r and R as small as possible
'''
X = fibonacci_sphere(npoints)
R, r, obs = minimize(X)
return X, R, r, obs
if __name__ == '__main__':
print('Experiment 1')
X = [[0.0740328,-0.0669765,-0.995004],[-0.0424728,-0.0903481,-0.995004],[0.49942,-0.26344,-0.825336],[0.520044,0.219943,-0.825336],[0.158841,0.54184,-0.825336],[-0.318986,0.465907,-0.825336],[-0.562607,0.0478954,-0.825336],[-0.393151,-0.405282,-0.825336],[0.0649644,-0.560893,-0.825336],[0.475382,-0.304685,-0.825336],[0.866629,-0.207856,-0.453596],[0.844371,0.28511,-0.453596],[0.563236,0.690663,-0.453596],[0.109417,0.884465,-0.453596],[-0.377948,0.807097,-0.453596],[-0.749438,0.482279,-0.453596],[-0.891156,0.00959889,-0.453596],[-0.759652,-0.466025,-0.453596],[-0.395246,-0.798769,-0.453596],[0.0903402,-0.886617,-0.453596],[0.548228,-0.702635,-0.453596],[0.838034,-0.303231,-0.453596],[0.999467,0.0145951,0.0291995],[0.870013,0.492164,0.0291995],[0.527371,0.849133,0.0291995],[0.0555024,0.998031,0.0291995],[-0.429966,0.902373,0.0291995],[-0.810076,0.585597,0.0291995],[-0.991686,0.125327,0.0291995],[-0.930293,-0.365653,0.0291995],[-0.640942,-0.767034,0.0291995],[-0.194535,-0.980461,0.0291995],[0.299541,-0.953636,0.0291995],[0.720218,-0.693133,0.0291995],[0.964412,-0.262785,0.0291995],[0.833167,0.225751,0.504846],[0.57369,0.644988,0.504846],[0.127056,0.853807,0.504846],[-0.361029,0.784085,0.504846],[-0.731333,0.458566,0.504846],[-0.863051,-0.0165536,0.504846],[-0.713211,-0.486272,0.504846],[-0.330696,-0.797352,0.504846],[0.159703,-0.848307,0.504846],[0.598002,-0.622515,0.504846],[0.841211,-0.193636,0.504846],[0.448738,0.253724,0.856889],[0.0444146,0.513584,0.856889],[-0.398518,0.326994,0.856889],[-0.495025,-0.143847,0.856889],[-0.161214,-0.489644,0.856889],[0.312737,-0.409801,0.856889],[0.514831,0.0262759,0.856889],[0.030007,0.0287842,0.999135]]
plot_points(X)
R, r, obs = minimize(X)
print('R = {0:.4f}\nr = {1:.4f}'.format(R, r))
plot_circles(X, R)
print('Experiment 2')
X = sample_spherical(50, ndim=3)
R, r, obs = minimize(X)
print('R = {0:.4f}\nr = {1:.4f}'.format(R, r))
plot_circles(X, R)
print('Experiment 3')
X, R, r, obs = generate(50)
print('R = {0:.4f}\nr = {1:.4f}'.format(R, r))
plot_circles(X, R)
def one_slice(vectors,
height,
x_min,
x_max,
y_min,
y_max,
box_size,
decimals=6,
frac=0.001,
debug=False):
"""
make boxed slice for given height
:param vectors: array of 3d object
:param height: heeigth for slice
:param x_min: min x coordinate of the object
:param x_max: max x coordinate of the object
:param y_min: min y coordinate of the object
:param y_max: max y coordinate of the object
:param decimals: number of the decimals after point for rounding operations after math calculation
:param box_size: size of the cube box
:param frac: error in comparison
:return: 2d binary array where 1 means that there`s a cube
"""
lines_of_slice = []
triangles_of_slice = []
plot_vectors(vectors, debug=debug)
# left only triangles which crosses horizontal plane
new_vectors = []
for triangle in vectors:
upper = 0
lower = 0
for i in triangle:
if i[2] > height:
upper += 1
else:
lower += 1
if upper != 0 and lower != 0:
triangles_of_slice.append([triangle.copy(), upper])
if upper != 0:
new_vectors.append(triangle.copy())
plot_vectors([i[0] for i in triangles_of_slice])
# save only line of triangles in horizontal plane
for triangle, upper in triangles_of_slice:
# find points for neadble lines
point_m = None
point_a = None
point_b = None
if upper == 2:
# two points upper than height
min_ind = 0
for i in range(2):
if triangle[min_ind][2] > triangle[i + 1][2]:
min_ind = i + 1
point_m = triangle[min_ind]
point_a = triangle[(min_ind + 1) % 3]
point_b = triangle[(min_ind + 2) % 3]
else:
# two points lower than height
max_ind = 0
for i in range(2):
if triangle[max_ind][2] < triangle[i + 1][2]:
max_ind = i + 1
point_m = triangle[max_ind]
point_a = triangle[(max_ind + 1) % 3]
point_b = triangle[(max_ind + 2) % 3]
# find intersections between lines and plane
# with a line
z = height
x_a = point_m[0] + (point_a[0] - point_m[0]) * (z - point_m[2]) / (
point_a[2] - point_m[2])
y_a = point_m[1] + (point_a[1] - point_m[1]) * (z - point_m[2]) / (
point_a[2] - point_m[2])
x_b = point_m[0] + (point_b[0] - point_m[0]) * (z - point_m[2]) / (
point_b[2] - point_m[2])
y_b = point_m[1] + (point_b[1] - point_m[1]) * (z - point_m[2]) / (
point_b[2] - point_m[2])
lines_of_slice.append([[x_a, y_a], [x_b, y_b]])
lines_of_slice = np.array(lines_of_slice)
lines_of_slice = np.around(lines_of_slice - 10**(-(decimals + 5)),
decimals=decimals)
plot_lines(lines_of_slice, debug=debug)
# create dotted plane from given group of borders
length = math.ceil(abs(x_max - x_min) / box_size)
width = math.ceil(abs(y_max - y_min) / box_size)
slice_plane_cubes = np.zeros((length, width))
for i in range(length):
for j in range(width):
for k in range(box_size**2):
if slice_plane_cubes[i, j] != 0:
break
else:
if (i * box_size + k % box_size < abs(x_max - x_min)) and (
j * box_size + k // box_size < abs(y_max - y_min)):
slice_plane_cubes[i, j] += is_inside([
int(round(x_min)) + i * box_size + k % box_size,
int(round(y_min)) + j * box_size + k // box_size
], lines_of_slice)
slice_plane_cubes[i, j] = slice_plane_cubes[i, j] % 2
plot_points(slice_plane_cubes, debug=debug)
return slice_plane_cubes, new_vectors
def callback(self, day, day_fraction, status, positions, home, work, plt, **ignore_other_kwargs):
""" This gets called after each computation cycle (see pandemic/simulation.py) """
from pandemic.metrics import collision_count
# Unique collisions with Joe
from geohash import encode
approx_precision = self.params['geometry']['p'] - 2
for joe in range(self.num_joes):
joes_hash = encode( positions[joe][0],positions[joe][1], precision = approx_precision )
rough_positions = [ ( encode(pos[0], pos[1], precision=self.params['geometry']['p']-2),j) for j,pos in enumerate(positions) ]
joes_collisions = [ j for (h,j) in rough_positions if h==joes_hash and not j==joe ]
joes_new_collisions = [j for j in joes_collisions if not j in self.friends[joe] ]
self.friends[joe].update( joes_new_collisions )
self.collision_history.append(len(joes_collisions))
self.unique_collions_history.append(len(joes_new_collisions))
num_rolling = 48
if len(self.collision_history)>num_rolling*self.num_joes:
rolling_collisions = sum(self.collision_history[-num_rolling*self.num_joes:])
rolling_unique_collisions = sum(self.unique_collions_history[-num_rolling*self.num_joes:])
if day_fraction==0:
self.attenuation_history.append((0.1 + rolling_unique_collisions) / (0.1 + rolling_collisions))
self.herd_history.append(sum([s in [VULNERABLE] for s in status]) / len(status))
if day_fraction==0:
# Daily collision TS
self.collision_daily_history.append(sum(self.collision_history[-self.params['motion']['t']:]))
# Standard plot of infections
metrics = status_counts(status=status)
self.metric_history.append(metrics)
self.time_history.append(day + day_fraction)
self.axs[0][0].clear
plot_points(plt=self.axs[0][0],positions=positions,status=status,title='Ornstein-Uhlenbeck')
self.axs[0][0].figure
if day > 1:
# Collisions curve
self.axs[1][0].plot(self.attenuation_history,marker='*')
self.axs[1][0].plot(self.herd_history, marker='o')
self.axs[1][0].set_title('Novelty versus Herd effect')
self.axs[1][0].set_xlabel('Days since ' + str(self.params['geometry']['i']) + ' cases.')
self.axs[1][0].set_ylabel('Attenuation')
# Growth curve
infect = [m[1] for m in self.metric_history]
self.axs[0][1].plot(self.time_history, infect,color=self.color)
#self.axs[0][1].set_yscale('log')
self.axs[0][1].set_title('Infected')
self.axs[0][1].figure
if day>1:
# Collisions curve
self.axs[1][1].plot(self.collision_daily_history, color=self.color, marker='*')
self.axs[1][1].set_title('Daily collisions')
self.axs[1][1].set_xlabel('Days since '+str(self.params['geometry']['i'])+' cases.')
self.plt.show(block=False)
figManager = plt.get_current_fig_manager()
figManager.full_screen_toggle()
self.plt.pause(2)
points_60_horizontal = make_points(data_60_horizontal[0], 0, 60, 1.47399,
0.5, data_60_horizontal[1], 405,
photodiode_solid_angle,
photodiode_angular_width,
"60 degrees horizontal polarization")
points_75_vertical = make_points(data_75_vertical[0], 0, 75, 1.47399, 0.5,
data_75_vertical[1], 405,
photodiode_solid_angle,
photodiode_angular_width,
"75 degrees vertical polarization")
points_75_horizontal = make_points(data_75_horizontal[0], 0, 75, 1.47399,
0.5, data_75_horizontal[1], 405,
photodiode_solid_angle,
photodiode_angular_width,
"75 degrees horizontal polarization")
all_points = points_45_vertical + points_45_horizontal + points_60_vertical + points_60_horizontal + points_75_vertical + points_75_horizontal
plot_points(points_45_horizontal + points_45_vertical,
"45 degrees",
log=False,
show=False)
plot_points(points_60_horizontal + points_60_vertical,
"60 degrees",
log=False,
show=False)
plot_points(points_75_horizontal + points_75_vertical,
"75 degrees",
log=False,
show=False)
plt.show()
points_air_without_75_slit = points_30_horizontal_air_slit + points_45_horizontal_air_slit + points_60_horizontal_air_slit
points_water_slit = points_30_horizontal_water_slit + points_45_horizontal_water_slit + points_60_horizontal_water_slit + points_75_horizontal_water_slit
points_water_without_75_slit = points_30_horizontal_water_slit + points_45_horizontal_water_slit + points_60_horizontal_water_slit
points_mineral_oil_slit = points_30_horizontal_mineral_oil_slit + points_45_horizontal_mineral_oil_slit + points_60_horizontal_mineral_oil_slit + points_75_horizontal_mineral_oil_slit
points_mineral_oil_without_75_slit = points_30_horizontal_mineral_oil_slit + points_45_horizontal_mineral_oil_slit + points_60_horizontal_mineral_oil_slit
all_points_slit = points_air_slit + points_water_slit + points_mineral_oil_slit
plot_air = False
if plot_air:
#plot_points(points_air_without_75 + points_air_without_75_slit, "Horizontal Polarization In Air With And Without Slit")
plot_points(points_30_horizontal_air + points_30_horizontal_air_slit,
"Horizontal Polarization In Air With And Without Slit")
plot_points(points_45_horizontal_air + points_45_horizontal_air_slit,
"Horizontal Polarization In Air With And Without Slit")
plot_points(points_60_horizontal_air + points_60_horizontal_air_slit,
"Horizontal Polarization In Air With And Without Slit")
plot_points(points_75_horizontal_air + points_75_horizontal_air_slit,
"Horizontal Polarization In Air With And Without Slit")
plot_water = False
if plot_water:
#plot_with_TSTR_fit(points_water, "Horizontal Polarization in Water Without Slit")
plot_points(points_30_horizontal_water + points_30_horizontal_water_slit,
"Horizontal Polarization In Water With And Without Slit")
plot_points(points_45_horizontal_water + points_45_horizontal_water_slit,
"Horizontal Polarization In Water With And Without Slit")
plot_points(points_60_horizontal_water + points_60_horizontal_water_slit,
theta_rot = 90 - p.theta_r_in_degrees
theta_r = 180 - p.theta_i_in_degrees - theta_rot
p.theta_r_in_degrees = theta_r
#plot_points(points_tape, "Tape in Mineral Oil", log=False)
"""
points_mineral_oil_30_subtracted = subtract_background(points_mineral_oil_30, points_background)
points_mineral_oil_45_subtracted = subtract_background(points_mineral_oil_45, points_background)
points_mineral_oil_52_5_subtracted = subtract_background(points_mineral_oil_52_5, points_background)
points_mineral_oil_60_subtracted = subtract_background(points_mineral_oil_60, points_background)
points_mineral_oil_75_subtracted = subtract_background(points_mineral_oil_75, points_background)
"""
#plot_points(points_background, "", log=False, show=True)
"""
plot_points(points_mineral_oil_30 + points_mineral_oil_30_subtracted,
"Mineral Oil 30 degrees and Background", log=False, show=False)
plot_points(points_mineral_oil_45 + points_mineral_oil_45_subtracted,
"Mineral Oil 45 degrees and Background", log=False, show=False)
plot_points(points_mineral_oil_52_5 + points_mineral_oil_52_5_subtracted,
"Mineral Oil 52.5 degrees and Background", log=False, show=False)
plot_points(points_mineral_oil_60 + points_mineral_oil_60_subtracted,
"Mineral Oil 60 degrees and Background", log=False, show=False)
plot_points(points_mineral_oil_75 + points_mineral_oil_75_subtracted,
"Mineral Oil 75 degrees and Background", log=False, show=False)
plt.show()
"""