def up_and_down(file1, file2):
data1 = dataframes.DataStore(file1)
data2 = dataframes.DataStore(file2)
duty1, order1 = duty_order(data1)
duty2, order2 = duty_order(data2)
plotter = plotting.Plotter()
plotter.add_plot(duty1, order1, label='up')
plotter.add_plot(duty2, order2, label='down')
plotter.configure_legend()
plotter.show_figure()
def order_histogram(file, frames):
data = dataframes.DataStore(file)
plotter = plotting.Plotter()
for f in frames:
order = data.get_info(f, ['real order'])
n, bins = np.histogram(order, np.linspace(0, 1, 100))
bins = bins[:-1] + (bins[1] - bins[0]) / 2
plotter.add_plot(bins, n, label=str(f))
plotter.configure_xaxis(0, 'Order parameter')
plotter.configure_yaxis(0, 'Frequency')
plotter.configure_legend(0, title='Frame')
plotter.show_figure()
def histogram(file, duty):
data = dataframes.DataStore(file)
print(data.frame_data.head())
df = data.frame_data.merge(data.df.drop('frame', 1).reset_index()).set_index('Duty')
p = plotting.Plotter()
for d in duty:
orders = df.loc[d, 'real order']
n, bins = np.histogram(orders, bins=100, density=True)
p.add_plot(bins[:-1]+(bins[1]-bins[0])/2, n*(bins[1]-bins[0]), label=d)
p.configure_legend()
p.configure_xaxis(xlabel='Order Parameter')
p.configure_yaxis(ylabel='Relative Frequency')
def frame_order(file):
data = dataframes.DataStore(file)
print(data.num_frames)
plotter = plotting.Plotter()
# duty_cycle = data.frame_data.Duty
# frames = data.frame_data.Duty
# order = data.frame_data['mean order']
# plotter.add_plot(frames, order, fmt='x')
# plotter.show_figure()
fdata = data.frame_data
fdata = fdata.groupby('Duty').mean()
plotter.add_plot(fdata.index.values, fdata['mean order'].values)
plotter.show_figure()
def run(files):
plotter = plotting.Plotter(subplot=(3, 2))
duties = list(range(400, 1050, 50))
for i, file in enumerate(files):
print(i)
with dataframes.DataStore(file) as data:
df1, df2 = split_df(data.df)
plotter = order_histograms(df1, duties, plotter, i)
plotter.configure_legend(i)
plotter.configure_xaxis(i, 'Order')
plotter.configure_yaxis(i, 'Density')
plotter.configure_subplot_title(i, file)
plotter.show_figure()
for i in range(np.shape(crack_width)[0]-1):
index = np.max(np.where(crack_width[i,:] > 1))
tip_pos[i]=index
rad_tip[i]=np.max(np.sum(crack_width[:,index-50:index]))
time = (1/fps)*np.arange(0,np.size(tip_pos))
tip_pos = scale*tip_pos
rad_tip = scale * rad_tip/2
np.savetxt(filename[:-4] + '_tiptraj.txt',np.c_[time,tip_pos])
p2 = p.Plotter(subplot=(3,1))
#1st subplot is tip trajectory
p2.add_plot(time, tip_pos, marker='r-',subplot=0)
p2.configure_xaxis(xlabel='time (s)',subplot=0)
p2.configure_yaxis(ylabel='xpos (microns)', subplot=0,fontsize=14)
#2nd subplot is the final width profile of crack indicating where width measurements are being taken
p2.add_plot(range(0,np.shape(crack_width)[1]),crack_width[np.shape(crack_width)[0]-10,:],marker='b-',subplot=1)
#Show position of width measurement on this profile
p2.configure_yaxis(ylabel='width',subplot=1,fontsize=14)
p2.configure_yaxis(ylabel='Crack width (microns)', subplot=2,fontsize=14)
p2.configure_xaxis(xlim=(tip_pos[0],None),subplot=1)
add_position(p2, filename, crack_width, time, 929, 'g')
add_position(p2, filename, crack_width, time, 1073, 'y')
add_position(p2, filename, crack_width, time, 1241, 'k')
add_position(p2, filename, crack_width, time, 1400, 'r')