def create_frames(self):
self.p_frame = tk.Frame(self.master)
self.p_frame.pack(side='left')
self.w_frame = tk.Frame(self.master)
self.w_frame.pack(side='right')
self.plots = plots.Plots(figsize=(11, 9), dpi=75)
self.canvas = FigureCanvasTkAgg(self.plots, master=self.p_frame)
self.canvas.draw()
self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
def create_plots(data, results, modulus, output_dir):
print("Creating Plots...")
save_loc = Path(output_dir, "plots")
modulus = int(modulus) * 10**6
#Create Models...
N = 2000000
Nf = np.linspace(1, N, N) #Cycles to Failure Variable
Rf = 2 * Nf #Reversals to Failure Variable
plastic_SL = (results[3] * (Rf**results[4])) #Plastic Strain-Life
elastic_SL = (
(results[0] / modulus) * (Rf**results[1])) #Elastic Strain-Life
total_SL = plastic_SL + elastic_SL #Total Strain-Life
stresslife = (results[6] * (Nf**results[7])) #Stress-Life
#Plot Plastic Strain-Life...
plots.Plots(None,
save_loc).fatigue_loglog(data['MaxCycles'], data['PlasticAmp'],
Rf, plastic_SL, "P")
#Plot Elastic Strain-Life...
plots.Plots(None,
save_loc).fatigue_loglog(data['MaxCycles'], data['ElasticAmp'],
Rf, elastic_SL, "E")
#Plot Stress-Life...
c = 10**-6
plots.Plots(None, save_loc).fatigue_loglog(data['MaxCycles'],
data['StressRange'] * c, Nf,
stresslife * c, "S")
#Plot Strain Amp vs Cycles...
StrainLife = total_SL * 100
plots.Plots(None, save_loc).fatigue_semilogX(data['MaxCycles'],
data['StrainAmp'] * 100, Nf,
StrainLife)
#Plot total strain-life
plots.Plots(None, save_loc).total_strain_life(Nf, plastic_SL, elastic_SL,
total_SL)
def __init__(self, num_samples=None):
if num_samples is not None:
self.plotting = plots.Plots(N, num_samples, L)
### simulation variables
self.an = numpy.zeros(N) # modal displacements
self.adn = numpy.zeros(N) # modal velocities; "d" is for "dot"
# positions
self.x0 = 0 # bow or pluck
self.x1 = 0 # finger
self.x2 = 0
self.x3 = 0
self.phix0 = phi(self.x0)
self.phix1 = phi(self.x1)
self.phix2 = phi(self.x2)
self.phix3 = phi(self.x3)
self.K0 = 0
self.K1 = 0
self.K2 = 0
self.K3 = 0
self.R0 = 0
self.R1 = 0
self.R3 = 0
self.ypluck = 0
self.plucks_left = False
self.release = False
self.x_finger = 0
self.x_pluck = 0
self.K_pluck = 0
self.K_finger = 0
self.R_pluck = 0
self.R_finger = 0
# bowing stuff
self.Fb = False
self.vb = 0
self.bowstate = 0 # 0=stick, 1=slip
self.debug_max_dv0h = 0
self.debug_prev_dv = 0
self.debug_prev_v0h = 0
self.debug_dv = 0
self.debug_print_state = False
self.debug_tick = 0
self.debug_plucks = 0
self.debug_slips = 0
def plot0():
"""
Plots the intensity/interference pattern.
"""
fig = plt.figure(figsize=(9, 6))
ax00 = plt.subplot2grid((10, 1), (0, 0), rowspan=8)
pattern00 = ax00.errorbar(x,
intensity_values[0][0],
yerr=intensity_values[0][1],
fmt='g-',
linewidth=1,
label='measurements')
fitted_pattern00 = ax00.errorbar(x,
intensity_values_fit[0][0],
yerr=intensity_values_fit[0][1],
fmt='b-',
linewidth=1,
label='fitted')
title00 = ax00.set_title(
"$i$ = %i, $\lambda$ = %i, $stroke$ = %0.4f$\mu m$, $voltage$ = %0.2fV"
% (0, fitted_cos_period[0][0], stroke_values[0][0], voltages[0]),
fontsize=16)
ax00.set_xlim(x[0], x[-1])
ax00.set_ylim(smallest_intensity(intensity_values_fit),
largest_intensity(intensity_values_fit))
ax00.legend()
ax00.tick_params(labelsize=16)
ax00.set_ylabel('$Intensity$', fontsize=18)
ax00.set_xlabel('$Distance$ $(Pixel)$', fontsize=18)
ax00.legend(fontsize=18)
axcolor = 'lightgoldenrodyellow'
ax_slider = plt.axes([0.15, 0.1, 0.65, 0.03], facecolor=axcolor)
slide = Slider(ax_slider, 'i', 0, no_of_images - 1, valinit=0, valfmt='%i')
plot_list = plots.Plots()
plot_list.adderrorbar(pattern00)
plot_list.adderrorbar(fitted_pattern00)
def update(val):
"""
Allows the change of interference pattern with the slider.
"""
val = int(val)
plot_list.removeerrorbar(n=-1)
plot_list.removeerrorbar(n=-1)
pattern00 = ax00.errorbar(x,
intensity_values[val][0],
yerr=intensity_values[val][1],
fmt='g-',
linewidth=1,
label='measurements')
fitted_pattern00 = ax00.errorbar(x,
intensity_values_fit[val][0],
yerr=intensity_values_fit[val][1],
fmt='b-',
linewidth=1,
label='fitted')
plot_list.adderrorbar(pattern00)
plot_list.adderrorbar(fitted_pattern00)
title00.set_text(
"$i$ = %i, $\lambda$ = %0.5f, $stroke$ = %0.4f$\mu m$, $voltage$ = %0.2fV"
% (val, fitted_cos_period[0][val], stroke_values[0][val],
voltages[val]))
plt.draw()
return
slide.on_changed(update)
return slide
if __name__ == '__main__':
print("\n\t\tДанные для входа находятся в файле 'account.txt'" + "\n")
print("\t\tДанные записываются в формате ->app_id login password" + "\n")
# Авторизация
a = sing_in.SignIn()
session_vk = a.authorization_vk()
print("Авторизация прошла успешно\n")
print("Начинаем парсинг группы...\n")
p = parsing.Parsing()
result_parsing = p.parsing(session_vk)
print("Парсинг выполнен успешно\n")
f = filter.Filter(result_parsing)
man, girl = f.filter_sex()
print("В группе мужчин =", man, " и девушек =", girl, "\n")
birth_data_age = []
birth_data_count = []
birth_data_age, birth_data_count = f.filter_bdate()
pl = plots.Plots()
pl.round_plot(birth_data_age, birth_data_count)
print("\nДиаграмма построена\n")
input("\nНажмите Enter, чтобы выйти\n")
def mono_analysis(
input_dir, output_dir, files, channels, stress_bool, geo_bool
):
with open((str(output_dir) + '/Monotonic_Output.csv'),'w', newline='') as f:
thewriter = csv.writer(f,delimiter=',')
thewriter.writerow([
'File Name','Start Position (mm)','End Position (mm)',
'Nominal Extension(mm)','Poissons Ratio','Tensile Modulus (GPa)',
'0.2% Offset Strength (MPa)','0.2% Offset Strain (m/m)',
'Max Load (kN)','Yield Stress (MPa)','Yield Strain(m/m)',
'Ult. True Strength (MPa)','Engineering Fracture Strength (MPa)',
'Ult. True Ductility (m/m)','Max Axial Strain (%)',
'Max Transverse Strain (%)'
])
print("Beginning Analysis Iteration...")
runs = []
names = []
for filename in files:
this_file = Path(input_dir,filename)
name = str(filename)
print(" Reading File ",name)
#Create Instance...
run = Monotonic(
channels, stress_bool, geo_bool, this_file
)
#Get positions...
p1, p2, ext = run.get_positions()
#Get true stress and strain...
true_stress, true_strain = run.get_true()
#Get elastic modulus and Poissons ratio...
poissons, emod = run.get_modulus_and_poissons()
#get 0.2% offset strain and stress...
offset_strain, offset_stress = run.get_offset(emod)
#Get yield point(max of stress-strain curve)...
yield_stress, yield_strain, max_load = run.get_yield()
#Get fracture stress and strain...
engr_frac_strength, max_ax_str, max_tr_str = run.get_engr_fracture()
#Get ultimate true stress/strain...
max_true_stress = max(true_stress)
max_true_strain = max(true_strain)
#Write values to file for each test...
thewriter.writerow([
name, p1, p2, ext, poissons, emod*10**-9, offset_stress*10**-6,
offset_strain,max_load/1000, yield_stress*10**-6, yield_strain,
max_true_stress*10**-6, engr_frac_strength*10**-6,
max_true_strain, max_ax_str*100, max_tr_str*100
])
#make Individual Test Plot...
plots.Plots(
name[:-4],Path(str(output_dir),'plots')
).mono_test_plot(
run.ax_str,run.stress,true_strain,true_stress
)
runs.append(run)
names.append(name[:-4])
print("Saving Results...")
#Plots...
print("Creating Plots...")
plots.Plots(
name[:-4],Path(str(output_dir),'plots')
).mono_all_plot(runs,names)
plotname = os.path.basename(args.flight)
elif args.aura_flight:
plotname = os.path.basename(args.aura_flight)
elif args.px4_sdlog2:
plotname = os.path.basename(args.px4_sdlog2)
elif args.sentera_flight:
plotname = os.path.basename(args.sentera_flight)
elif args.sentera2_flight:
plotname = os.path.basename(args.sentera2_flight)
elif args.umn_flight:
plotname = os.path.basename(args.umn_flight)
else:
plotname = "plotname not set correctly"
# plots
plt = plots.Plots(plotname)
# plot onboard filter
data_ob = data_store.data_store()
for filterpt in data['filter']:
data_ob.append_from_filter(filterpt)
plt.update(data_ob, 'On Board', c='g', alpha=0.5)
# plot gps
data_gps = data_store.data_store()
for gpspt in data['gps']:
data_gps.append_from_gps(gpspt)
plt.update(data_gps, 'GPS', marker='*', c='g', alpha=0.5)
# find the range of gps time stamps that represent some significant
# amount of velocity
import plots p = plots.Plots() #p.tweet_intensity() # Figura 2 #p.tweets_and_users_by_month() # Figura 3 #p.time_intervals() # Figura 5 #p.time_intervals_detail() # Figura 5 detalle #p.distance_between_tweets_and_pois() # Figura 6 #p.avg_stddev_distance_to_POI() # Figura 6 #p.time_gap_between_consecutive_tweets() # Figura 7 #p.time_distribution() # Figura 8 p.avg_distance_and_interval() # Scatter distancia vs intervalo #p.avg_distance_and_interval_detail() # Scatter distancia vs intervalo #p.users_by_month() #p.tweets_by_month()