"""Tests for the Streamline module.

This module uses the compare_image function to perform image based
testing.  This is so just to illustrate how you could use image based
tests.  However, we recommend that one does not use image based tests
since they are not always reliable and a pain.
"""
# Author: Prabhu Ramachandran <prabhu_r@users.sf.net>
# Copyright (c) 2005-2008,  Enthought, Inc.
# License: BSD Style.

# Standard library imports.
from os.path import abspath
from StringIO import StringIO
import copy
import numpy
import sys


# Local imports.
from common import TestCase, is_running_with_nose


class TestStreamline(TestCase):
    def make_data(self):
        """Trivial data -- creates an elementatry scalar field and a
        constant vector field along the 'x' axis."""
        s = numpy.arange(0.0, 10.0, 0.01)
        s = numpy.reshape(s, (10,10,10))
        s = numpy.transpose(s)

        v = numpy.zeros(3000, 'd')
        v[::3] = 1.0
        v = numpy.reshape(v, (10,10,10,3))
        return s, v


    def test(self):
        if is_running_with_nose():
            import unittest
            raise unittest.SkipTest('This test Segfaults after passing or fails.')
        self.main()

    def do(self):
        ############################################################
        # Imports.
        script = self.script
        from mayavi.sources.array_source import ArraySource
        from mayavi.modules.outline import Outline
        from mayavi.modules.streamline import Streamline

        ############################################################
        # Create a new scene and set up the visualization.
        s = self.new_scene()

        d = ArraySource()
        sc, vec = self.make_data()
        d.origin = (-5, -5, -5)
        d.scalar_data = sc
        d.vector_data = vec

        script.add_source(d)

        # Create an outline for the data.
        o = Outline()
        script.add_module(o)
        # View the data.
        st = Streamline()
        script.add_module(st)
        widget = st.seed.widget
        widget.set(radius=1.0, center=(-4.0, -4.0, -4.0),
                   theta_resolution=4, phi_resolution=4)

        st = Streamline(streamline_type='ribbon')
        seed = st.seed
        seed.widget = seed.widget_list[1]
        script.add_module(st)
        seed.widget.set(point1=(-5.0, -4.5, -4.0), point2=(-5.0, -4.5, 4.0))
        st.ribbon_filter.width = 0.25

        st = Streamline(streamline_type='tube')
        seed = st.seed
        seed.widget = seed.widget_list[2]
        script.add_module(st)
        seed.widget.set(center=(-5.0, 1.5, -2.5))
        st.tube_filter.radius = 0.15

        st = Streamline(streamline_type='tube')
        seed = st.seed
        seed.widget = seed.widget_list[3]
        script.add_module(st)
        seed.widget.position=(-5.0, 3.75, 3.75)
        st.tube_filter.radius = 0.2

        # Set the scene to a suitable view.
        s.scene.z_plus_view()
        c = s.scene.camera
        c.azimuth(-30)
        c.elevation(30)
        s.render()

        # Update the streamlines.
        mm = o.module_manager
        for child in mm.children[1:]:
            child.update_streamlines = True

        # Now compare the image.
        self.compare_image(s, 'images/test_streamline.png')

        ############################################################
        # Test if the modules respond correctly when the components
        # are changed.

        tf = st.tube_filter
        st.tube_filter = tf.__class__()
        st.tube_filter = tf
        st.ribbon_filter = st.ribbon_filter.__class__()
        seed = st.seed
        st.seed = seed.__class__()
        st.seed = seed
        st.actor = st.actor.__class__()
        tracer = st.stream_tracer
        st.stream_tracer = tracer.__class__()
        st.stream_tracer = tracer

        s.render()
        # Now compare the image.
        self.compare_image(s, 'images/test_streamline.png')
        s.render()

        ############################################################
        # Test if saving a visualization and restoring it works.

        bg = s.scene.background
        # Save visualization.
        f = StringIO()
        f.name = abspath('test.mv2') # We simulate a file.
        script.save_visualization(f)
        f.seek(0) # So we can read this saved data.

        # Remove existing scene.
        engine = script.engine
        engine.close_scene(s)

        # Load visualization
        script.load_visualization(f)
        s = engine.current_scene

        # Set the scene to a suitable view.
        s.scene.z_plus_view()
        c = s.scene.camera
        c.azimuth(-30)
        c.elevation(30)
        s.render()
        s.scene.background = bg

        # Now compare the image.
        self.compare_image(s, 'images/test_streamline.png')

        ############################################################
        # Test if the MayaVi2 visualization can be deepcopied.

        # Pop the source object.
        sources = s.children
        s.children = []
        # Add it back to see if that works without error.
        s.children.extend(sources)

        s.scene.reset_zoom()
        # Now compare the image.
        self.compare_image(s, 'images/test_streamline.png')

        # Now deepcopy the source and replace the existing one with
        # the copy.  This basically simulates cutting/copying the
        # object from the UI via the right-click menu on the tree
        # view, and pasting the copy back.
        sources1 = copy.deepcopy(sources)
        s.children[:] = sources
        s.scene.reset_zoom()
        self.compare_image(s, 'images/test_streamline.png')

        # If we have come this far, we are golden!


if __name__ == "__main__":
    t = TestStreamline()
    t.test()
