import numpy as np
from dataserver import get_file
from demo_helpers import generate_rank1_data
# TODO, make scatter
f = get_file('parametric_test.h5').get_numbered_child()
f.create_dataset('random walk', rank=2)
#f.create_dataset('3d random walk', rank=2)
f['random walk'].set_attrs(parametric=True)
#f['3d random walk'].set_attrs(parametric=True)
pos_2d = np.zeros(2)
#pos_3d = np.zeros(3)
xs, ys, zs = (generate_rank1_data() for _ in range(3))
for x, y, z in zip(xs, ys, zs):
raw_input("Enter to Step")
pos_2d += (x, y)
# pos_3d += (x, y, z)
f['random walk'].append(pos_2d)
# f['3d random walk'].append(pos_3d)
print 'Done'
from dataserver import get_file
from demo_helpers import generate_rank1_data, generate_rank2_data
f = get_file('simple_test.h5')
f = f.get_group('simple group')
f = f.get_numbered_child()
f['lines'] = generate_rank1_data()
f['image'] = generate_rank2_data()
print 'Done'
from H5Plot import plotwindow_client
from demo_helpers import generate_rank1_data
win = plotwindow_client(serverport=55563)
plot = win.add_plot('some test plot')
plot.set_data(generate_rank1_data())
from dataserver import get_file
from demo_helpers import generate_rank1_data
f = get_file('attr_test.h5').get_numbered_child()
f['lines'] = generate_rank1_data()
f['lines'].set_attrs(x0=1, xscale=.01, xlabel='Time', ylabel='Noise')
import numpy as np
from dataserver import get_file
from demo_helpers import generate_rank1_data, generate_rank2_data
f = get_file('accumulating_test.h5').get_numbered_child()
f.create_dataset('line', rank=1)
f.create_dataset('img', rank=2)
for x, trace in zip(generate_rank1_data(), generate_rank2_data()):
#time.sleep(.1)
print "Enter to step",
raw_input()
f['line'].append(np.random.normal())
f['img'].append(np.random.normal(size=100))
print 'Done'