Python Report.subsection方法代码示例

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def report_servo1(processed, area_graphs):
    r = Report('servo1')
    
    nmap = processed['nmap']
    servo = processed['servo']
    centroid = processed['centroid']
    robot = processed['robot']
    
    with r.subsection('u', robust=False) as s:
        commands = [x['u'] for x in servo]
        vels = map(robot.debug_get_vel_from_commands, commands)
        vels = map(se2_project_from_se3, vels)
        repsec_servo1_generic_vel_field(s, 'u', centroid, nmap, vels,
                                        normalize=True, area_graphs=area_graphs)
        
    if 'u_raw' in servo[0]:
        with r.subsection('u_raw', robust=True) as s:
            commands = [x['u_raw'] for x in servo]
            vels = map(robot.debug_get_vel_from_commands, commands)
            vels = map(se2_project_from_se3, vels)
            repsec_servo1_generic_vel_field(s, 'u_raw', centroid, nmap, vels,
                                            normalize=True, area_graphs=area_graphs)

    if 'descent' in servo[0]:
        with r.subsection('descent', robust=True) as s:
            commands = [x['descent'] for x in servo]
            vels = map(robot.debug_get_vel_from_commands, commands)
            vels = map(se2_project_from_se3, vels)
            repsec_servo1_generic_vel_field(s, 'descent', centroid, nmap, vels,
                                            normalize=False, area_graphs=area_graphs)
         
    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def aer_stats_freq_meat(log, pipeline):
    events = aer_pipeline_transitions1_all(log, pipeline)
    
    r = Report('index')
        
    with r.subsection('all') as sub:
        report_band(sub, events, min_f=20.0, max_f=3000.0)

    with r.subsection('high') as sub:
        report_band(sub, events, min_f=500.0, max_f=3000.0)
            
    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def report_dds_geometry(id_discdds, tolerance):
    dds = get_conftools_discdds().instance(id_discdds)
    r = Report('dds_geometry-%s-%s' % (id_discdds, tolerance))
    ds = DiffeoStructure(dds, tolerance=tolerance)
    with r.subsection('display') as r:
        ds.display(r)
    
    with r.subsection('show_reduction_steps') as r:
        ds.show_reduction_steps(r, max_nsteps=5)
        
    with r.subsection('show_reduction') as r:
        ds.show_reduction(r)
        
    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def go():
    ieee_fonts_zoom3(pylab)

    r = Report()
    algos = [InvMult2.ALGO_UNIFORM, InvMult2.ALGO_VAN_DER_CORPUT]
    for algo in algos:
        InvMult2.ALGO = algo
        InvPlus2.ALGO = algo
        print("Using algorithm %s " % algo)
        with r.subsection(algo) as r2:
            # first
            F = parse_poset("dimensionless")
            R = F
            dp = InvMult2(F, (R, R))
            ns = [3, 4, 5, 6, 10, 15]

            axis = (0.0, 6.0, 0.0, 6.0)

            with r2.subsection("invmult2") as rr:
                go1(rr, ns, dp, plot_nominal_invmult, axis)

            # second
            axis = (0.0, 1.2, 0.0, 1.2)
            dp = InvPlus2(F, (R, R))
            with r2.subsection("invplus2") as rr:
                go1(rr, ns, dp, plot_nominal_invplus, axis)

    fn = "out-plot_approximations/report.html"
    print("writing to %s" % fn)
    r.to_html(fn)

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def test_consistency_uncertainty():
    print 'here'
    pass
    contracts.disable_all()
    symdds = 'sym-dpchain1-120'
    print('instancing dds %s' % symdds)
    dds = get_conftools_discdds().instance(symdds)
    shape = dds.get_shape()
    d1f = dds.actions[0].get_diffeo2d_forward()
    d1b = dds.actions[0].get_diffeo2d_backward()
    
    fb = Diffeomorphism2D.compose(d1f, d1b)
    bf = Diffeomorphism2D.compose(d1b, d1f)
    identity = Diffeomorphism2D.identity(shape)
    print Diffeomorphism2D.distance_L2_infow(d1f, identity)
    print Diffeomorphism2D.distance_L2_infow(d1b, identity)
    print Diffeomorphism2D.distance_L2_infow(fb, identity)
    print Diffeomorphism2D.distance_L2_infow(bf, identity)

    action = dds.actions[0]
    action2 = consistency_based_uncertainty(action, None)

    r = Report(symdds)
    r.text('symdds', symdds)
    with r.subsection('action') as sub:
        action.display(sub)
    with r.subsection('action2') as sub:
        action2.display(sub)
#         
#     with r.subsection('misc') as sub:
#         d = d1f.get_discretized_diffeo()
#         f = sub.figure()
#         f.array_as_image('d0', d[:, :, 0])
#         f.array_as_image('d1', d[:, :, 1])
#         
        
#     with r.subsection('d1f') as sub:
#         d1f.display(sub)
#     with r.subsection('d1b') as sub:
#         d1b.display(sub)
# 
#     with r.subsection('fb') as sub:
#         fb.display(sub)
#     with r.subsection('bf') as sub:
#         bf.display(sub)
    
    r.to_html('test_consistency_uncertainty.html')

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def plot_different_solutions(libname, ndpname, query, out, upper=None):
    if not os.path.exists(out):
        os.makedirs(out)
    library = get_test_library(libname)
    #library.use_cache_dir(os.path.join(out, 'cache'))
    context = Context()
    ndp = library.load_ndp(ndpname, context)

    context = library._generate_context_with_hooks()
    ndp_labelled = get_labelled_version(ndp)
    dp0 = ndp_labelled.get_dp()
    if upper is not None:
        _, dpU = get_dp_bounds(dp0, nl=1, nu=upper)
        dp = dpU
    else:
        dp = dp0

    M = dp.get_imp_space()

    with open(os.path.join(out, 'ndp.txt'), 'w') as f:
        f.write(ndp.repr_long())
    with open(os.path.join(out, 'M.txt'), 'w') as f:
        f.write(M.repr_long())
    with open(os.path.join(out, 'dp.txt'), 'w') as f:
        f.write(dp.repr_long())
    with open(os.path.join(out, 'dp0.txt'), 'w') as f:
        f.write(dp0.repr_long())

    f = convert_string_query(ndp=ndp, query=query, context=context)

    report = Report()

    res = dp.solve(f)
    print('num solutions: %s' % len(res.minimals))
    for ri, r in enumerate(res.minimals):
        ms = dp.get_implementations_f_r(f, r)

        for j, m in enumerate(ms):
            imp_dict = get_imp_as_recursive_dict(M, m)
            print imp_dict

            images_paths = library.get_images_paths()
            gv = GetValues(ndp=ndp, imp_dict=imp_dict, nu=upper, nl=1)

            gg = gvgen_from_ndp(ndp=ndp, style=STYLE_GREENREDSYM,
                                images_paths=images_paths,
                                plotting_info=gv)

            with report.subsection('%s-%s' % (ri, j)) as rr:
                gg_figure(rr, 'figure', gg, do_png=True, do_pdf=False,
                          do_svg=False, do_dot=False)


    fn = os.path.join(out, 'solutions.html')
    print('writing to %s' % fn)
    report.to_html(fn)

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def aer_stats_events_meat(log):
#    events = collect_all(aer_load_log_generic(log))
    events = aer_raw_events_from_file_all(log)
    hist = aer_histogram(events)
    _, coords = md_argmax(hist)

    r = Report('index')    
    with r.subsection('sub') as sub:
        report_for_one(sub, events, coords)
    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def make_stream_report(id_stream, nsamples):
    config = get_diffeo2ddslearn_config()
    stream = config.streams.instance(id_stream)
    r = Report(id_stream)
    data = itertools.islice(stream.read_all(), nsamples)
    
    for i, log_item in enumerate(data):
        with r.subsection('log_item%d' % i) as sub:
            log_item.display(sub)
         
    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def report_agent(res, pomdp):
    agent = res['agent']


    r = Report()

    f = r.figure()

    p_p0 = pomdp.get_start_dist_dist()
    for i, (p0, _) in enumerate(p_p0.items()):
        with f.plot('p0-%d' % i) as pylab:
            pomdp.display_state_dist(pylab, p0)
            turn_all_axes_off(pylab)

    with r.subsection('states') as sub:
        agent.report_states(sub)

    with r.subsection('transitions') as sub:
        agent.report_transitions(sub)


    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def report_ndp1(ndp):
    r = Report()

    gg = gvgen_from_ndp(ndp)
    gg_figure(r, 'graph', gg)

    styles = ['greenred', 'clean', 'greenredsym']
    for style in styles:
        with r.subsection(style) as r2:
            gg = gvgen_from_ndp(ndp, style=style)
            gg_figure(r2, 'graph', gg)

    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def report_raw_display(processed):
    r = Report('raw_display')
    f = r.figure()

    centroid = processed['centroid']
    nmap = processed['nmap']
    xy = processed['nmap'].get_R2_points() 

    caption = "Raw trajectory and selected points"
    with f.plot('sparse_xy', caption=caption) as pylab:
        xy = np.array(xy)
        pylab.plot(xy[:, 0], xy[:, 1], 'k+')
        pylab.plot(centroid[0], centroid[1], 'go')
        nmap.plot_points(pylab)
        pylab.axis('equal')

    with r.subsection('nmap') as n:
        processed['nmap'].display(n) 

    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def report_servo_details(servo_agent, processed, nsamples=6):
    r = Report('servo_details')

    nmap = processed['nmap']
    y_goal = processed['y_goal']
    robot = processed['robot']

    for i in range(nsamples):
        j = np.random.randint(len(nmap.data))
        y0 = nmap.get_observations_at(j)
        servo = processed['servo'][j]
        with r.subsection('sample%s' % i) as r_i:
            f = r.figure(cols=4)
              
            with f.plot('map') as pylab:
                nmap.plot_points(pylab)
                vel = robot.debug_get_vel_from_commands(servo['u'])
                nmap.plot_vel_at_index(pylab, j, se2_project_from_se3(vel), length=0.05)

            with r_i.subsection('query') as rq:
                servo_agent.display_query(rq, observations=y0, goal=y_goal)
    
    return r

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]

#.........这里部分代码省略.........

                    print("artifact: %s" % artifact)

            tracer.log(s)

        if expect_nimp is not None:
            if expect_nimp != nimplementations:
                msg = "Found wrong number of implementations"
                raise_desc(ExpectationsNotMet, msg, expect_nimp=expect_nimp, nimplementations=nimplementations)

    #     if expect_res is not None:
    #         value = interpret_string(expect_res)
    #         tracer.log('value: %s' % value)
    #         res_expected = value.value
    #         tu = get_types_universe()
    #         # If it's a tuple of two elements, then we assume it's upper/lower bounds
    #         if isinstance(value.unit, PosetProduct):
    #             subs = value.unit.subs
    #             assert len(subs) == 2, subs
    #
    #             lower_UR_expected, upper_UR_expected = subs
    #             lower_res_expected, upper_res_expected = value.value
    #
    #             lower_bound = tu.get_embedding(lower_UR_expected, UR)[0](lower_res_expected)
    #             upper_bound = tu.get_embedding(upper_UR_expected, UR)[0](upper_res_expected)
    #
    #             tracer.log('lower: %s <= %s' % (UR.format(lower_bound), UR.format(res)))
    #             tracer.log('upper: %s <= %s' % (UR.format(upper_bound), UR.format(res)))
    #
    #             UR.check_leq(lower_bound, res)
    #             UR.check_leq(res, upper_bound)
    #         else:
    #             # only one element: equality
    #             UR_expected = value.unit
    #             tu.check_leq(UR_expected, UR)
    #             A_to_B, _B_to_A = tu.get_embedding(UR_expected, UR)
    #
    #             res_expected_f = A_to_B(res_expected)
    #             try:
    #                 UR.check_equal(res, res_expected_f)
    #             except NotEqual as e:
    #                 raise_wrapped(ExpectationsNotMet, e, 'res is different',
    #                               res=res, res_expected=res_expected, compact=True)

    if plot:
        r = Report()
        if _exp_advanced:
            from mcdp_report.generic_report_utils import generic_report

            generic_report(r, dp, trace, annotation=None, axis0=(0, 0, 0, 0))
        else:
            f = r.figure()
            from mcdp_report.generic_report_utils import generic_plot

            generic_plot(f, space=UR, value=res)
            from mcdp_report.generic_report_utils import generic_report_trace

            generic_report_trace(r, ndp, dp, trace, out, do_movie=do_movie)

        out_html = os.path.join(out, "report.html")
        logger.info("writing to %r" % out_html)
        r.to_html(out_html)

    if plot and imp:
        from mcdp_report_ndp_tests.test1 import GetValues
        from mcdp_report.gg_ndp import gvgen_from_ndp
        from mcdp_report.gdc import STYLE_GREENREDSYM
        from mcdp_report.gg_utils import gg_figure

        M = dp.get_imp_space()

        report_solutions = Report()
        for i, r in enumerate(res.minimals):
            ms = dp.get_implementations_f_r(fg, r)
            for j, m in enumerate(ms):

                imp_dict = get_imp_as_recursive_dict(M, m)
                images_paths = library.get_images_paths()
                gv = GetValues(ndp=ndp, imp_dict=imp_dict, nu=upper, nl=1)

                setattr(ndp, "_hack_force_enclose", True)

                with report_solutions.subsection("sol-%s-%s" % (i, j)) as rr:
                    # Left right
                    gg = gvgen_from_ndp(
                        ndp=ndp, style=STYLE_GREENREDSYM, images_paths=images_paths, plotting_info=gv, direction="LR"
                    )

                    gg_figure(rr, "figure", gg, do_png=True, do_pdf=True, do_svg=False, do_dot=False)

                    # Top-bottom
                    gg = gvgen_from_ndp(
                        ndp=ndp, style=STYLE_GREENREDSYM, images_paths=images_paths, plotting_info=gv, direction="TB"
                    )

                    gg_figure(rr, "figure2", gg, do_png=True, do_pdf=True, do_svg=False, do_dot=False)

        out_html = os.path.join(out, "report_solutions.html")
        logger.info("writing to %r" % out_html)
        report_solutions.to_html(out_html)

# 需要导入模块: from reprep import Report [as 别名]
# 或者: from reprep.Report import subsection [as 别名]
def report(res):

    r = Report()

    dataL = res['dataL']
    dataU = res['dataU']

    what_to_plot_res = dict(total_cost="USD", total_mass='kg')
    what_to_plot_fun = dict(endurance="hour", extra_payload="g")

    queries = dataL['queries']
    endurance = [q['endurance'] for q in queries]

    def get_value(data, field):
        for res in data['results']:
            a = to_numpy_array({field: 'kg'}, res)

            if len(a):
                a = min(a[field])
            else:
                a = None
            yield a


    from matplotlib import pylab
    ieee_fonts_zoom3(pylab)


    markers = dict(markeredgecolor='none', markerfacecolor='black', markersize=6,
                   marker='o')
    LOWER2 = dict(color='orange', linewidth=4, linestyle='-', clip_on=False)
    UPPER2 = dict(color='purple', linewidth=4, linestyle='-', clip_on=False)
    LOWER2.update(markers)
    UPPER2.update(markers)
    color_resources = '#700000'
    color_functions = '#007000'


    fig = dict(figsize=(4.5, 4))

    with r.plot('total_mass', **fig) as pylab:
        ieee_spines_zoom3(pylab)
        total_massL = np.array(list(get_value(dataL, 'total_mass')))
        total_massU = np.array(list(get_value(dataU, 'total_mass')))
        print endurance
        print total_massL, total_massU
        pylab.plot(endurance, total_massL, **LOWER2)
        pylab.plot(endurance, total_massU, **UPPER2)
        set_axis_colors(pylab, color_functions, color_resources)
        pylab.xlabel('endurance [hours]')
        pylab.ylabel('total_mass [kg]')

    return r


    print('Plotting lower')
    with r.subsection('lower') as rL:
        plot_all_directions(rL,
                            queries=dataL['queries'],
                            results=dataL['results'],
                            what_to_plot_res=what_to_plot_res,
                            what_to_plot_fun=what_to_plot_fun)
    
    print('Plotting upper')
    with r.subsection('upper') as rU:
        plot_all_directions(rU,
                            queries=dataU['queries'],
                            results=dataU['results'],
                            what_to_plot_res=what_to_plot_res,
                            what_to_plot_fun=what_to_plot_fun)

    return r