def generate_mayavi_point_plot(self, srcid_sciclasses_list):
""" Generate a Mayavi mlab 3D plot which summarizes iterative
classification of a TUTOR source over the number of epochs
used/added.
"""
# # # # # # # # #
# TODO: I should label which science class by color, as Y axis labels
from enthought.mayavi.scripts import mayavi2
mayavi2.standalone(globals())
from enthought.mayavi import mlab
epoch_ids = [0] # x
class_groups = [0] # y
probs = [0] # z
styles = [0] # numbers used for coloring & glyph sizes
for src_id,sci_classes in srcid_sciclasses_list:
#print 'src_id:', src_id
i = 0
for class_name, class_dict in sci_classes.class_dict.iteritems():
epoch_ids.extend(class_dict['epoch_ids'])
class_groups.extend([1]*len(class_dict['epoch_ids']))
probs.extend(class_dict['probs'])
styles.extend([i + 1]*len(class_dict['epoch_ids']))
i += 1
mlab.points3d(numpy.array(epoch_ids),
numpy.array(class_groups),
numpy.array(probs)*100.0,
numpy.array(styles),
colormap="Paired",
scale_mode="none",
scale_factor=2.0)
mlab.axes(xlabel='N of epochs',
ylabel='science class',
zlabel='% Prob.')
# Example of option baskets
# Distributed under BSD License
from enthought.mayavi.scripts import mayavi2
from enthought.tvtk.tools import mlab
from plotspace import PlotSpace
mayavi2.standalone(globals())
import eurooption
import basketoption
import scipy
import numpy
import threading
spot = scipy.arange(10.0, 100.0, 5.0)
vol = scipy.arange(0.1, 1.0, 0.1)
riskfree = scipy.arange(0.0, 5.0, 1.0)
u1 = scipy.arange(0.5, 15.0, 0.5)
u2 = scipy.arange(0.5, 15.0, 0.5)
if __name__ == "__main__":
mayavi.new_scene()
p = PlotSpace(mayavi.engine.current_scene, [1, 100, 1])
p.add_points([[1, 2, 1], [1, 3, 1], [2, 4, 2]])
p.add_lines([[2, 2, 1], [3, 3, 1], [3, 3, 1], [3, 4, 1], [4, 4, 2]])
mayavi.new_scene()
p = PlotSpace(mayavi.engine.current_scene, [1, 100, 1])
# Example of option baskets
# Distributed under BSD License
from enthought.mayavi.scripts import mayavi2
mayavi2.standalone(globals())
import scipy
import QuantLib as ql
from enthought.tvtk.tools import mlab
from enthought.mayavi.sources.vtk_data_source import VTKDataSource
from enthought.mayavi.filters.warp_scalar import WarpScalar
from enthought.mayavi.modules.surface import Surface
spot = scipy.arange(10.0, 100.0, 5.0)
vol = scipy.arange(0.1, 1.0, 0.1)
riskfree = scipy.arange(0.0, 5.0, 1.0)
todaysDate = ql.Date(15, ql.May, 1998)
ql.Settings.instance().evaluationDate = todaysDate
settlementDate = ql.Date(17, ql.May, 1998)
riskFreeQuote = ql.SimpleQuote(0.05)
riskFreeRate = ql.FlatForward(settlementDate, ql.QuoteHandle(riskFreeQuote),
ql.Actual365Fixed())
# option parameters
exercise1 = ql.AmericanExercise(settlementDate, ql.Date(17, ql.May, 1999))
exercise2 = ql.EuropeanExercise(settlementDate)
payoff = ql.PlainVanillaPayoff(ql.Option.Call, 40.0)
# market data
def generate_mayavi_line_plot(self, srcid_sciclasses_list,
use_linfit_segments=False,
enable_mayavi2_interactive_gui=False):
""" Generate a Mayavi mlab 3D plot which summarizes iterative
classification of a TUTOR source over the number of epochs
used/added.
"""
# TODO: I would like to plot each sci class a different color
# - I should have each science class re-use a single number/color
# - I should label which science class by color, as Y axis labels
# TODO: I will need to insert a 0 point onto arrays (for s[0]?)
if enable_mayavi2_interactive_gui:
from enthought.mayavi.scripts import mayavi2
mayavi2.standalone(globals())
from enthought.mayavi import mlab
# scalar cut plane plotting module stuff:
import enthought.mayavi
from enthought.mayavi.modules.scalar_cut_plane import ScalarCutPlane
epoch_ids = [0] # x
class_groups = [0] # y
probs = [0] # z
styles = [0] # numbers used for coloring & glyph sizes
used_final_classes = []
i_srcid = 0
for final_class in self.pars['interested_sci_classes']:
if not finalclass_ordered_dict.has_key(final_class):
continue # skip this science class since nothing to plot
else:
used_final_classes.append(final_class)
srcid_sciclasses_list = finalclass_ordered_dict[final_class]
for src_id,sci_classes in srcid_sciclasses_list:
print 'src_id:', src_id, '\t', final_class
sci_classes.generate_linearfit_endpoints_segments()
i = 0
for class_name,class_dict in sci_classes.class_dict.iteritems():
class_style = self.sciclass_style_dict[class_name]
if use_linfit_segments:
for segment_dict in class_dict['linfit_segments']:
epoch_ids.extend([segment_dict['epoch_ids'][0]])
class_groups.extend([i_srcid])
probs.extend([0])
styles.extend([0])
epoch_ids.extend(segment_dict['epoch_ids'])
class_groups.extend([i_srcid]*len(segment_dict['epoch_ids']))
probs.extend(segment_dict['probs'])
styles.extend([class_style]*len(segment_dict['epoch_ids']))
epoch_ids.extend([segment_dict['epoch_ids'][-1]])
class_groups.extend([i_srcid])
probs.extend([0])
styles.extend([0])
else:
epoch_ids.extend([class_dict['epoch_ids'][0]])
class_groups.extend([i_srcid])
probs.extend([0])
styles.extend([0])
epoch_ids.extend(class_dict['epoch_ids'])
class_groups.extend([i_srcid]*len(class_dict['epoch_ids']))
probs.extend(class_dict['probs'])
styles.extend([class_style]*len(class_dict['epoch_ids']))
epoch_ids.extend([class_dict['epoch_ids'][-1]])
class_groups.extend([i_srcid])
probs.extend([0])
styles.extend([0])
i += 1
i_srcid += 3 # Y spacing between srcids within a science-class
i_srcid += 20 # Y spacing between science-class groups
mlab.plot3d(numpy.array(epoch_ids),
numpy.array(class_groups),
numpy.array(probs)*100.0,
numpy.array(styles),
colormap="Paired",
tube_radius=1)
# extent=[0,600,
# 0,i_srcid,
# 15, 110])
mlab.axes(xlabel='N of epochs',
ylabel='science class',
zlabel='% Prob.')#,
# DEBUG/UPGRADE: These seem to trigger some bug about Actor methods:
# extent=[0,600,
# 0,i_srcid,
# -10, 110])
title_str = "num_srcids=%d probability_cut=%0.2lf factor_threshold=%0.2lf bin_size=%d poly_order=%d" % (\
self.pars['num_srcids_to_retrieve_plot'],
self.pars['sciclass_probability_cut'],
self.pars['polyfit_factor_threshold'],
self.pars['polyfit_bin_size'],
self.pars['polyfit_poly_order'])
##### TITLE:
# The 'z' is a flag in Mayavi2 v3.1.0 documentation:
#mlab.text(0.01, 0.97, title_str, width=1.0, name='title', z=0.0)
mlab.text(0.01, 0.97, title_str, width=1.0, name='title')
##### SCIENCE CLASS LABELS:
# TODO: Eventually I would like the class labels to be colored and
# placed on the y axis, but this requires:
# 1) later mayavi version to allow 3D text positioning
# 2) ability to match text color to the line color-map.
if 1:
used_final_classes.reverse()
y = 0.95
for class_name in used_final_classes:
class_str = "%2d %s" %(len(finalclass_ordered_dict[class_name]),
class_name)
mlab.text(0.85, y, class_str, width=0.095*(len(class_str)/20.0))
y -= 0.018
##### Add a x-axis plane (I can't figure out code to make it opaque)
if 0:
cp = ScalarCutPlane()
mayavi.add_module(cp)
cp.implicit_plane._hideshow() # this un-displays the plane
cp.implicit_plane.normal = 0,0,1
cp.implicit_plane.origin = 150,168,15
#cp.implicit_plane.position= 0.15 # feature not available yet
print '##### cp:'
cp.print_traits()
print '##### cp.implicit_plane:'
cp.implicit_plane.print_traits()
print '##### cp.implicit_plane._HideShowAction:'
cp.implicit_plane._HideShowAction.print_traits()
##### Camera position:
if enable_mayavi2_interactive_gui:
camera_distance = 600
else:
camera_distance = 1200
enthought.mayavi.tools.camera.view(azimuth=50,
elevation=70, # 0:looking down to -z
distance=camera_distance,
focalpoint=(100,(i_srcid*0.4),50))
#enthought.mayavi.mlab.show_pipeline() # this introspecive feature is not available in current mayavi version.
#####If no Mayavi2 GUI, we allow user to resize image before saving file
if not enable_mayavi2_interactive_gui:
print 'Please resize window & Press a Key.'
import curses
stdscr = curses.initscr()
while 1:
c = stdscr.getch()
break
curses.endwin()
##### Save figure:
img_fpath ="/tmp/%s%s.png" %(title_str.replace('=','').replace(' ','_'),
self.pars['save_plot_image_suffix'])
if os.path.exists(img_fpath):
os.system('rm ' + img_fpath)
mlab.savefig(img_fpath)#, size=(500,500))#, dpi=200) #size flag doesn't do anything
print "Saved:", img_fpath