/
testWorkspace.py
725 lines (597 loc) · 34 KB
/
testWorkspace.py
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import os
import unittest
import pickle
import copy
import pygsti.protocols.estimate
from pygsti.extras import drift
from pygsti.modelpacks.legacy import stdQT_XYIMS
from ..testutils import compare_files, temp_files
import numpy as np
from ..report.reportBaseCase import ReportBaseCase
bLatex = bool('PYGSTI_LATEX_TESTING' in os.environ and
os.environ['PYGSTI_LATEX_TESTING'].lower() in ("yes","1","true"))
try:
import pandas
bPandas = True
except ImportError:
bPandas = False
class TestWorkspace(ReportBaseCase):
def setUp(self):
super(TestWorkspace, self).setUp()
self.tgt = self.results.estimates['default'].models['target']
self.ds = self.results.dataset.copy()
self.ds.comment = "Hello\nWorld!" # for testing DS overview table
self.mdl = self.results.estimates['default'].models['go0']
self.gss = self.results.circuit_lists['final']
def test_notebook_mode(self):
wnb = pygsti.report.Workspace()
with self.assertRaises(ValueError):
wnb.init_notebook_mode()
def test_caching(self):
ws = pygsti.report.Workspace()
def output_fn():
return ws.NotApplicable() # a WorkspaceOutput obj
key, result = ws.smartCache.cached_compute(output_fn, [])
#print(key,result)
ws.save_cache(temp_files + "/saved_workspace_testcache.pkl", show_unpickled=True)
ws.load_cache(temp_files + "/saved_workspace_testcache.pkl")
def test_plotly_pickling(self):
import plotly.graph_objs as go
# Create random data with numpy
N = 1000
random_x = np.random.randn(N)
random_y = np.random.randn(N)
# Create a trace
trace = go.Scatter(
x = random_x,
y = random_y,
mode = 'markers'
)
data = [trace]
fig = go.Figure(data=[trace], layout={})
pygsti.report.workspace.enable_plotly_pickling()
#DEBUG
#Import dill
#dill.detect.trace(True)
#dill.detect.badobjects(fig['frames'], depth=1)
#print(dir(fig))
#print("frames: ",type(fig['frames']))
#s = pickle.dumps(fig['frames'])
#print("layout",type(fig['layout']))
#s = pickle.dumps(fig['layout'])
#print("data",type(fig['data']))
#s = pickle.dumps(fig['data'])
s = pickle.dumps(fig)
fig2 = pickle.loads(s)
pygsti.report.workspace.disable_plotly_pickling()
#Again for good measure
pygsti.report.workspace.enable_plotly_pickling()
pygsti.report.workspace.disable_plotly_pickling()
def test_custom_digest(self):
import hashlib
M = hashlib.md5()
ws = pygsti.report.Workspace()
NA = ws.NotApplicable()
pygsti.report.workspace.ws_custom_digest(M, NA)
switchbd = ws.Switchboard(["My Switch"],[["On","Off"]],["buttons"])
switchbd.add("mdl", [0])
switchval = switchbd.mdl
pygsti.report.workspace.ws_custom_digest(M, switchval)
def test_table_creation(self):
w = pygsti.report.Workspace()
tbls = []; cr = None
gsMultiSpam = self.mdl.copy()
gsMultiSpam.povms['Msecondpovm'] = self.mdl.povms['Mdefault'].copy()
gsTP = self.tgt.depolarize(0.01,0.01); gsTP.set_all_parameterizations("TP")
gsCPTP = self.tgt.depolarize(0.01,0.01); gsCPTP.set_all_parameterizations("CPTP")
gsGM = self.mdl.depolarize(0.01,0.01); gsGM.basis = pygsti.obj.Basis.cast("gm",4)
gsSTD = self.mdl.depolarize(0.01,0.01); gsSTD.basis = pygsti.obj.Basis.cast("std",4)
gsQT = stdQT_XYIMS.target_model().depolarize(0.01,0.01)
#Construct confidence regions
def make_cr(mdl):
hessian = pygsti.tools.logl_hessian(mdl, self.ds, self.gss,
min_prob_clip=1e-4, prob_clip_interval=(-1e6,1e6),
radius=1e-4)
est = pygsti.protocols.estimate.Estimate.gst_init(None, mdl, None, []) #dummy w/out parent
crfactory = pygsti.obj.ConfidenceRegionFactory(
parent=est, model_lbl="target", circuit_list_lbl=None,
hessian=hessian, non_mark_radius_sq=0.0)
crfactory.project_hessian('std')
return crfactory.view(95)
cr2 = make_cr(self.mdl)
cr2TP = make_cr(gsTP)
cr2CPTP = make_cr(gsCPTP)
#----------------- Test table creation ---------------------------
tbls.append( w.BlankTable() )
tbls.append( w.SpamTable(self.mdl, ["mytitle"], "boxes", cr, True ) )
tbls.append( w.SpamTable(gsTP, ["mytitle"], "boxes", cr2TP, True ) )
tbls.append( w.SpamTable(self.mdl, ["mytitle"], "numbers", cr, False ) )
with self.assertRaises(ValueError):
w.SpamTable(self.mdl, ["mytitle"], "foobar", cr, False ) #invalid display_as
tbls.append( w.SpamParametersTable(self.mdl, cr ) )
tbls.append( w.SpamParametersTable(gsMultiSpam, cr ) )
tbls.append( w.GatesTable(self.mdl, ["mytitle"], display_as="boxes", confidence_region_info=cr ) )
tbls.append( w.GatesTable(self.mdl, ["mytitle"], display_as="numbers", confidence_region_info=cr ) )
tbls.append( w.GatesTable(gsTP, ["mytitle"], display_as="numbers", confidence_region_info=cr2TP ) )
tbls.append( w.GatesTable(gsCPTP, ["mytitle"], display_as="numbers", confidence_region_info=cr2CPTP ) )
with self.assertRaises(ValueError):
w.GatesTable(self.mdl, ["mytitle"], display_as="foobar", confidence_region_info=cr )
tbls.append( w.ChoiTable(self.mdl, ["mytitle"], cr ) )
tbls.append( w.ChoiTable(gsQT, ["mytitle"], None ) )
with self.assertRaises(ValueError):
w.ChoiTable(self.mdl, ["mytitle"], cr, display=("foobar",) )
tbls.append( w.GatesVsTargetTable(self.mdl, self.tgt, cr) )
with self.assertRaises(ValueError):
w.GatesVsTargetTable(self.mdl, self.tgt, cr, display=("foobar",) )
tbls.append( w.SpamVsTargetTable(self.mdl, self.tgt, cr ) )
tbls.append( w.ErrgenTable(self.mdl, self.tgt, cr, display_as="boxes", gen_type="logTiG") )
tbls.append( w.ErrgenTable(self.mdl, self.tgt, cr, display_as="numbers", gen_type="logTiG") )
tbls.append( w.ErrgenTable(self.mdl, self.tgt, cr, display_as="numbers", gen_type="logG-logT") )
tbls.append( w.ErrgenTable(gsGM, self.tgt, cr, display_as="numbers", gen_type="logGTi") )
tbls.append( w.ErrgenTable(gsSTD, self.tgt, cr, display_as="numbers", gen_type="logGTi") )
tbls.append( w.ErrgenTable(gsQT, stdQT_XYIMS.target_model(), cr, display_as="numbers", gen_type="logGTi") )
with self.assertRaises(ValueError):
w.ErrgenTable(self.mdl, self.tgt, cr, display=('foobar',))
with self.assertRaises(AssertionError):
w.ErrgenTable(self.mdl, self.tgt, cr, display_as='foobar')
with self.assertRaises(ValueError):
w.ErrgenTable(self.mdl, self.tgt, cr, gen_type='foobar')
tbls.append( w.GateDecompTable(self.mdl, self.tgt, cr) )
tbls.append( w.GateEigenvalueTable(self.mdl, self.tgt, cr) )
tbls.append( w.GateEigenvalueTable(self.mdl, None, cr, display=("polar",) ) ) # polar with no target model
tbls.append( w.GateEigenvalueTable(self.mdl, self.tgt, cr, display=("evdm","evinf","rel"),
virtual_ops=[pygsti.obj.Circuit(('Gx','Gx'))] ) )
with self.assertRaises(ValueError):
tbls.append( w.GateEigenvalueTable(self.mdl, self.tgt, cr, display=("foobar",)) )
tbls.append( w.DataSetOverviewTable(self.ds,max_length_list=[1,2,4,8]) )
tbls.append( w.FitComparisonTable(self.gss.circuit_structure.Ls, self.results.circuit_lists['iteration'],
self.results.estimates['default'].models['iteration estimates'], self.ds) )
with self.assertRaises(ValueError):
w.FitComparisonTable(self.gss.circuit_structure.Ls, self.results.circuit_lists['iteration'],
self.results.estimates['default'].models['iteration estimates'], self.ds, objfn_builder="foobar")
tbls.append( w.GaugeRobustErrgenTable(self.mdl, self.tgt) )
prepStrs = self.results.circuit_lists['prep fiducials']
effectStrs = self.results.circuit_lists['meas fiducials']
tbls.append( w.CircuitTable((prepStrs,effectStrs),
["Prep.","Measure"], common_title="Fiducials"))
metric_abbrevs = ["evinf", "evagi","evnuinf","evnuagi","evdiamond",
"evnudiamond", "inf","agi","trace","diamond","nuinf","nuagi",
"frob"]
for metric in metric_abbrevs:
tbls.append( w.GatesSingleMetricTable(
metric, [self.mdl,self.mdl],[self.tgt,self.tgt], ['one','two'])) #1D
tbls.append( w.GatesSingleMetricTable(
metric, [[self.mdl],[self.mdl]],[[self.tgt],[self.tgt]],
['column one'], ['row one','row two'], op_label="Gx")) #2D
tbls.append( w.GatesSingleMetricTable(
metric, [self.mdl,None],[self.tgt,self.tgt], ['one','two'])) #1D w/None model
tbls.append( w.StandardErrgenTable(4, "hamiltonian", "pp") ) # 1Q
tbls.append( w.StandardErrgenTable(9, "stochastic", "gm") ) # qutrit
tbls.append( w.StandardErrgenTable(16, "hamiltonian", "gm") ) # 2Q
tbls.append( w.StandardErrgenTable(64, "stochastic", "pp") ) # >2Q (3Q)
goparams = self.results.estimates['default'].goparameters['go0'].copy()
goparams.update({'method': "LM", 'cptp_penalty_factor': 1.0}) # for coverage
tbls.append( w.GaugeOptParamsTable(goparams) )
tbls.append( w.GaugeOptParamsTable(False) )
params = self.results.estimates['default'].parameters.copy()
params['gaugeOptParams'] = goparams # add for coverate
tbls.append( w.MetadataTable(self.mdl, params) )
params['gaugeOptParams'] = [goparams] # can also be a list (for GOpt stages)
tbls.append( w.MetadataTable(gsTP, params) )
weirdGS = pygsti.construction.build_explicit_model(
[('Q0','Q1')],['Gi'], ["I(Q0)"])
#weirdGS.preps['rho1'] = pygsti.obj.ComplementSPAMVec(weirdGS.preps['rho0'],[]) #num_params not implemented!
weirdGS.povms['Mtensor'] = pygsti.obj.TensorProdPOVM([self.mdl.povms['Mdefault'],self.mdl.povms['Mdefault']])
tbls.append( w.MetadataTable(weirdGS, params) )
tbls.append( w.SoftwareEnvTable() )
profiler = pygsti.obj.Profiler()
tbls.append( w.ProfilerTable(profiler,"time") )
tbls.append( w.ProfilerTable(profiler,"name") )
if profiler is not None:
with self.assertRaises(ValueError):
w.ProfilerTable(profiler,"foobar")
#OLD tables
tbls.append( w.old_RotationAxisVsTargetTable(self.mdl, self.tgt) )
tbls.append( w.old_GateDecompTable(self.mdl) )
tbls.append( w.old_RotationAxisTable(self.mdl) )
#Now test table rendering in html
for i,tbl in enumerate(tbls):
print("Table: %s" % str(type(tbl)))
out_html = tbl.render("html")
#out_latex = tbl.render("latex") #not supported yet (figure formatting wants scratchdir)
tbl.saveas(temp_files + "/saved_table_%d.html" % i)
if bPandas:
tbl.saveas(temp_files + "/saved_table_%d.pkl" % i)
if bLatex:
tbl.saveas(temp_files + "/saved_table_%d.tex" % i)
tbl.saveas(temp_files + "/saved_table_%d.pdf" % i)
tbl.set_render_options(render_includes=False, leave_includes_src=False) #dumb case where nothing is output
tbl.render('latex')
with self.assertRaises(ValueError):
tbl.saveas(temp_files + "/saved_table_%d.foobar" % i) # Unknown file type
w.save_cache(temp_files + "/saved_workspace_cache1.pkl", show_unpickled=True)
w.load_cache(temp_files + "/saved_workspace_cache1.pkl")
w2 = pygsti.report.Workspace(temp_files + "/saved_workspace_cache1.pkl") # init from cache
#printOpenFiles()
#print("PSUTIL open files (%d) = " % len(psutil.Process().open_files()), psutil.Process().open_files())
#assert(False),"STOP"
def test_plot_creation(self):
w = pygsti.report.Workspace()
prepStrs = self.results.circuit_lists['prep fiducials']
effectStrs = self.results.circuit_lists['meas fiducials']
non_gatestring_strs = [ 'GxString', 'GyString' ]
plts = []
plts.append( w.BoxKeyPlot(prepStrs, effectStrs) )
plts.append( w.BoxKeyPlot(non_gatestring_strs, non_gatestring_strs) )
plts.append( w.ColorBoxPlot(("chi2","logl"), self.gss, self.ds, self.mdl, box_labels=True,
hover_info=True, sum_up=False, invert=False) )
plts.append( w.ColorBoxPlot(("chi2","logl"), self.gss, self.ds, self.mdl, box_labels=False,
hover_info=True, sum_up=True, invert=False) )
plts.append( w.ColorBoxPlot(("chi2","logl"), self.gss, self.ds, self.mdl, box_labels=False,
hover_info=True, sum_up=False, invert=True) )
plts.append( w.ColorBoxPlot(("chi2","logl"), self.gss, self.ds, self.mdl, box_labels=False,
hover_info=True, sum_up=False, invert=False, typ="scatter") )
mds = pygsti.objects.MultiDataSet()
mds.add_dataset("DS0",self.ds)
mds.add_dataset("DS1",self.ds)
dsc = pygsti.objects.DataComparator([self.ds,self.ds], op_exclusions=['Gfoo'], op_inclusions=['Gx','Gy','Gi'])
dsc2 = pygsti.objects.DataComparator(mds)
dsc.implement()
dsc2.implement()
plts.append( w.ColorBoxPlot(("dscmp",), self.gss, None, self.mdl, dscomparator=dsc) ) # dscmp with 'None' dataset specified
plts.append( w.ColorBoxPlot(("dscmp",), self.gss, None, self.mdl, dscomparator=dsc2) )
tds = pygsti.io.load_tddataset(compare_files + "/timeseries_data_trunc.txt")
#OLD: driftresults = drift.do_basic_drift_characterization(tds)
results_gst = drift.StabilityAnalyzer(tds, ids=True)
results_gst.generate_spectra()
results_gst.do_instability_detection(0.05)
results_gst.do_instability_characterization(estimator='filter', modelselector=('default',()),verbosity=0)
plts.append( w.ColorBoxPlot('driftsize', self.gss, self.ds, self.mdl, box_labels=False,
hover_info=False, sum_up=True, invert=False, stabilityanalyzer=results_gst) )
with self.assertRaises(ValueError):
w.ColorBoxPlot(("foobar",), self.gss, self.ds, self.mdl)
with self.assertRaises(ValueError):
w.ColorBoxPlot(("chi2",), self.gss, self.ds, self.mdl, typ="foobar")
from pygsti.algorithms import directx as dx
#specs = pygsti.construction.build_spam_specs(
# prepStrs=prepStrs,
# effectStrs=effectStrs,
# prep_labels=list(self.mdl.preps.keys()),
# effect_labels=self.mdl.get_effect_labels() )
baseStrs = self.gss.circuit_structure.get_basestrings()
directModels = dx.direct_mlgst_models(
baseStrs, self.ds, prepStrs, effectStrs, self.tgt, svd_truncate_to=4)
plts.append( w.ColorBoxPlot(["chi2","logl","blank"], self.gss.circuit_structure,
self.ds, self.mdl, box_labels=False, direct_gst_models=directModels) )
plts.append( w.ColorBoxPlot(["errorrate"], self.gss.circuit_structure,
self.ds, self.mdl, box_labels=False, sum_up=True,
direct_gst_models=directModels) )
gmx = np.identity(4,'d'); gmx[3,0] = 0.5
plts.append( w.MatrixPlot(gmx, -1,1, ['a','b','c','d'], ['e','f','g','h'], "X", "Y",
colormap = pygsti.report.colormaps.DivergingColormap(vmin=-2, vmax=2)) )
plts.append( w.MatrixPlot(gmx, -1,1, ['a','b','c','d'], ['e','f','g','h'], "X", "Y",colormap=None))
plts.append( w.GateMatrixPlot(gmx, -1,1, "pp", "in", "out", box_labels=True) )
plts.append( w.PolarEigenvaluePlot([np.linalg.eigvals(self.mdl.operations['Gx'])],["purple"],scale=1.5) )
plts.append( w.PolarEigenvaluePlot([np.linalg.eigvals(self.mdl.operations['Gx'])],["purple"],amp=2.0) )
projections = np.zeros(16,'d')
plts.append( w.ProjectionsBoxPlot(projections, "pp", box_labels=False) )
plts.append( w.ProjectionsBoxPlot(projections, "gm", box_labels=True) )
plts.append( w.ProjectionsBoxPlot(np.zeros(9,'d'), "gm", box_labels=True) ) # non-qubit case
plts.append( w.ProjectionsBoxPlot(np.zeros(64,'d'), "gm", box_labels=True) ) # >2Q case
choievals = np.array([-0.03, 0.02, 0.04, 0.98])
choieb = np.array([0.05, 0.01, 0.02, 0.01])
plts.append( w.ChoiEigenvalueBarPlot(choievals, None) )
plts.append( w.ChoiEigenvalueBarPlot(choievals, choieb) )
plts.append( w.FitComparisonBarPlot(self.gss.circuit_structure.Ls, self.results.circuit_lists['iteration'],
self.results.estimates['default'].models['iteration estimates'], self.ds,) )
plts.append( w.GramMatrixBarPlot(self.ds,self.tgt) )
plts.append( w.DatasetComparisonHistogramPlot(dsc, nbins=50, frequency=True,
log=True, display='pvalue'))
plts.append( w.DatasetComparisonHistogramPlot(dsc, nbins=None, frequency=True,
log=False, display='llr'))
with self.assertRaises(ValueError):
w.DatasetComparisonHistogramPlot(dsc, nbins=50, frequency=True,
log=False, display='foobar')
# Note: RandomizedBenchmarkingPlot is tested in extras/test_rb.py
#Now test table rendering in html
for i,plt in enumerate(plts):
print("Plot: %s" % str(type(plt)))
out_html = plt.render("html")
plt.saveas(temp_files + "/saved_plot_%d.html" % i)
plt.saveas(temp_files + "/saved_plot_%d.pkl" % i) #Note: plots don't need Pandas for pickling
if bLatex:
plt.saveas(temp_files + "/saved_plot_%d.pdf" % i)
with self.assertRaises(ValueError):
plt.saveas(temp_files + "/saved_plot_%d.foobar" % i) # Unknown file type
w.save_cache(temp_files + "/saved_workspace_cache1.pkl")
w.load_cache(temp_files + "/saved_workspace_cache1.pkl")
# printOpenFiles()
# print("PSUTIL open files (%d) = " % len(psutil.Process().open_files()), psutil.Process().open_files())
# assert(False),"STOP"
def test_switchboard(self):
w = pygsti.report.Workspace()
ds = self.ds
mdl = self.mdl
gs2 = self.mdl.depolarize(op_noise=0.01, spam_noise=0.15)
gs3 = self.mdl.depolarize(op_noise=0.011, spam_noise=0.1)
switchbd = w.Switchboard(["dataset","model"],
[["one","two"],["One","Two"]],
["dropdown","slider"])
switchbd.add("ds",(0,))
switchbd.add("mdl",(1,))
switchbd["ds"][:] = [ds, ds]
switchbd["mdl"][:] = [mdl, gs2]
switchbd2 = w.Switchboard(["spamWeight"], [["0.0","0.1","0.2","0.5","0.9","0.95"]], ["slider"])
tbl = w.SpamTable(switchbd["mdl"])
plt = w.ColorBoxPlot(("chi2","logl"), self.gss, switchbd["ds"], switchbd["mdl"], box_labels=False)
switchbd.render("html")
switchbd2.render("html")
tbl.render("html")
plt.render("html")
switchbd3 = w.Switchboard(["My Switch"],[["On","Off"]],["buttons"])
switchbd3.add("mdl", [0])
switchbd3.mdl[:] = [gs2,gs3]
tbl2 = w.GatesVsTargetTable(switchbd3.mdl, self.tgt)
switchbd3.render("html")
tbl2.render("html")
switchbd3.render("html")
try:
switchbd3.display()
except:
pass #might work, might not, depending on how much ipython support exists...
switchbd4 = w.Switchboard(["My Numeric Slider"],[["0.0","1.0","1.5"]],["numslider"])
switchbd5 = w.Switchboard(["My Switch"],[["On","Off"]],["buttons"],show="none") #test show=="none"
with self.assertRaises(KeyError):
switchbd5['key'] = 10 # can't add switched values like this.
switchbd5.switchTypes[0] = "foobar" #mess with Switchboard internals to trigger errors below
with self.assertRaises(ValueError):
switchbd5.get_switch_change_handlerjs(0)
with self.assertRaises(ValueError):
switchbd5.get_switch_valuejs(0)
with self.assertRaises(ValueError):
switchbd5.render("html")
switchbd4.render("html")
#switchbd5.render("html")
view1 = switchbd.view()
view2 = switchbd.view(['dataset'])
view3 = switchbd.view([True,False])
view4 = pygsti.report.workspace.SwitchboardView(switchbd, show="all")
view5 = pygsti.report.workspace.SwitchboardView(switchbd, show="none")
try:
view1.display()
except:
pass #might work, might not, depending on how much ipython support exists...
#Test a switched WorkspaceTable & Plot & Text
switchbd6 = w.Switchboard(["Plot type"],[["BoxeS","NumberS"]],["buttons"])
switchbd6.add("typ", [0])
switchbd6.add("strs", [0])
switchbd6.typ[:] = ["boxes","numbers"]
switchbd6.strs[:] = [ [('Gx',)], [('Gy',)] ]
tbl = w.SpamTable(self.mdl, ["mytitle"], switchbd6.typ, None)
tbl.saveas(temp_files + "/saved_switched_table.html", index=0)
if bPandas: tbl.saveas(temp_files + "/saved_switched_table.pkl") # OK to not specify index in pkl case
with self.assertRaises(ValueError):
tbl.saveas(temp_files + "/saved_switched_table.html") # must supply index
with self.assertRaises(ValueError):
tbl.saveas(temp_files + "/saved_switched_table.tex") # must supply index
plt = w.BoxKeyPlot(switchbd6.strs, switchbd6.strs)
plt.saveas(temp_files + "/saved_switched_plot.html", index=0)
plt.saveas(temp_files + "/saved_switched_plot.pkl") # OK to not specify index in pkl case
with self.assertRaises(ValueError):
plt.saveas(temp_files + "/saved_switched_plot.html") # must supply index
with self.assertRaises(ValueError):
plt.saveas(temp_files + "/saved_switched_plot.tex") # cannot save plots as LaTeX
with self.assertRaises(ValueError):
plt.saveas(temp_files + "/saved_switched_plot.pdf") # must supply index
def textfn(s): return pygsti.report.textblock.ReportText(s, None)
txt = pygsti.report.workspace.WorkspaceText(w, textfn, switchbd6.typ) # just "boxes" / "numbers" text
txt.saveas(temp_files + "/saved_switched_text.html", index=0)
txt.saveas(temp_files + "/saved_switched_text.pkl") # OK to not specify index in pkl case
with self.assertRaises(ValueError):
txt.saveas(temp_files + "/saved_switched_text.html") # must supply index
with self.assertRaises(ValueError):
txt.saveas(temp_files + "/saved_switched_text.tex") # must supply index
# Test "Opaque figure" python rendering (fig w/out "pythonvalue")
plt.figs[0].pythonvalue = None # mimic fig w/out pythonvalue
py = plt.render("python")
self.assertEqual( py['python']['index0']['value'], "Opaque Figure")
def test_text_creation(self):
printer = pygsti.obj.VerbosityPrinter(1)
printer.start_recording()
printer.log("Hello World")
lineinfo = printer.stop_recording()
ws = pygsti.report.Workspace()
texts = []
texts.append( ws.StdoutText( lineinfo ) )
#Now test rendering
for i,text in enumerate(texts):
print("Text: %s" % str(type(text)))
out_html = text.render("html")
text.saveas(temp_files + "/saved_text_%d.html" % i)
text.saveas(temp_files + "/saved_text_%d.pkl" % i)
if bLatex:
text.saveas(temp_files + "/saved_text_%d.tex" % i)
text.saveas(temp_files + "/saved_text_%d.pdf" % i)
text.set_render_options(render_includes=False, leave_includes_src=False) #dumb case where nothing is output
text.render("latex")
with self.assertRaises(ValueError):
text.saveas(temp_files + "/saved_text_%d.foobar" % i) # Unknown file type
def test_workspaceoutput(self):
ws = pygsti.report.Workspace()
raw_wo = pygsti.report.workspace.WorkspaceOutput(ws)
s = pickle.dumps(raw_wo)
raw_wo2 = pickle.loads(s)
#test some base class paths
with self.assertRaises(ValueError):
raw_wo.set_render_options(foobar="10")
with self.assertRaises(NotImplementedError):
raw_wo.render("html")
with self.assertRaises(NotImplementedError):
raw_wo.saveas("doesntmatter.html")
raw_wo.set_render_options(global_requirejs=True)
raw_wo._create_onready_handler("myJavascriptCode;", "MyID")
try:
raw_wo.display()
except:
pass #might work or not, depending on how much ipython is installed
def test_notapplicable(self):
ws = pygsti.report.Workspace()
NA = ws.NotApplicable()
NA.render("html")
NA.render("latex")
NA.render("python")
with self.assertRaises(ValueError):
NA.render("foobar")
def test_plot_and_table_objects(self):
ws = pygsti.report.Workspace()
printer = pygsti.obj.VerbosityPrinter(1)
printer.start_recording()
printer.log("Hello World (with $\\alpha$ math latex)")
lineinfo = printer.stop_recording()
strs = pygsti.construction.circuit_list([ (), ('Gx',), ('Gx','Gy')])
table = ws.BlankTable()
plot = ws.BoxKeyPlot(strs, strs)
text = ws.StdoutText( lineinfo )
objs = [table, plot, text] # list of "representative" objects for testing
for obj in objs:
print("Testing ",type(obj))
obj.set_render_options(precision=4,
output_dir=temp_files) # needed for html rendering
obj.render("html")
obj.set_render_options(switched_item_mode='foobar')
with self.assertRaises(ValueError):
obj.render("html") #invalid switched-item-mode
if bLatex:
with self.assertRaises(ValueError):
obj.render("latex") #invalid switched-item-mode
if bPandas:
with self.assertRaises(ValueError):
obj.render("python") #invalid switched-item-mode
for mode in ('separate files','inline'):
obj.set_render_options(switched_item_mode=mode,
autosize="continual") #pick options not used elsewhere
obj.render("html")
if bLatex: obj.render("latex")
if bPandas: obj.render("python")
with self.assertRaises(NotImplementedError):
obj.render("foobar")
#Individual item tests
with self.assertRaises(ValueError):
plot.set_render_options(valign="foobar")
plot.render("html")
def test_plot_helpers(self):
from pygsti.report import plothelpers as ph
self.assertEqual(ph._eformat(0.1, "compacthp"),".10")
self.assertEqual(ph._eformat(1.0, "compacthp"),"1.0")
self.assertEqual(ph._eformat(5.2, "compacthp"),"5.2")
self.assertEqual(ph._eformat(63.2, "compacthp"),"63")
self.assertEqual(ph._eformat(2.1e-4, "compacthp"),"2m4")
self.assertEqual(ph._eformat(2.1e+4, "compacthp"),"2e4")
self.assertEqual(ph._eformat(-3.2e-4, "compacthp"),"-3m4")
self.assertEqual(ph._eformat(-3.2e+4, "compacthp"),"-3e4")
self.assertEqual(ph._eformat(4e+40, "compacthp"),"*40")
self.assertEqual(ph._eformat(6e+102, "compacthp"),"B")
self.assertEqual(ph._eformat(10, "compacthp"),"10")
self.assertEqual(ph._eformat(1.234, 2),"1.23")
self.assertEqual(ph._eformat(-1.234, 2),"-1.23")
self.assertEqual(ph._eformat(-1.234, "foobar"), "-1.234") #just prints in general format
subMxs = np.nan * np.ones((3,3,2,2),'d') # a 3x3 grid of 2x2 matrices
nBoxes, dof_per_box = ph._compute_num_boxes_dof(subMxs, sum_up=True, element_dof=1)
self.assertEqual(nBoxes, 0)
self.assertEqual(dof_per_box, None)
subMxs[0,0,1,1] = 1.0 # matrix [0,0] has a single non-Nan element
subMxs[0,2,0,1] = 1.0
subMxs[0,2,1,1] = 1.0 # matrix [0,2] has a two non-Nan elements
# now the mxs that aren't all-NaNs don't all have the same # of Nans => warning
#self.assertWarns(ph._compute_num_boxes_dof, subMxs, sum_up=True, element_dof=1)
ph._compute_num_boxes_dof( subMxs, sum_up=True, element_dof=1) # Python2.7 doesn't always warn...
def test_plot_basefns(self):
#Tests non-covered boundary cases for plot-supporting functions
import pygsti.report.colormaps
import pygsti.report.workspaceplots
colormap = pygsti.report.colormaps.DivergingColormap(0,10)
mx = np.identity(2,'d')
mxs = [ [mx, mx],
[mx, mx] ]
gstrs = pygsti.construction.circuit_list([ (), ('Gx',) ])
# ---- nested_color_boxplot ----
pygsti.report.workspaceplots.nested_color_boxplot(mxs, colormap)
# ---- generate_boxplot ----
pygsti.report.workspaceplots.generate_boxplot(
mxs, gstrs, gstrs,
['ixlbl1','ixlbl2'], ['iylbl1','iylbl2'],
'Xlbl','Ylbl','innerXlbl','innerYlbl', colormap) #circuit labels
pygsti.report.workspaceplots.generate_boxplot(
mxs, ['xlbl1','xlbl2'], ['ylbl1','ylbl2'],
['ixlbl1','ixlbl2'], ['iylbl1','iylbl2'],
'Xlbl','Ylbl','innerXlbl','innerYlbl', colormap,
sum_up=True, hover_info=True) #sumup test
pygsti.report.workspaceplots.generate_boxplot(
mxs, ['xlbl1','xlbl2'], ['ylbl1','ylbl2'],
['ixlbl1','ixlbl2'], ['iylbl1','iylbl2'],
'Xlbl','Ylbl','innerXlbl','innerYlbl', colormap,
sum_up=True, hover_info=False) #no hover info
pygsti.report.workspaceplots.generate_boxplot(
mxs, ['xlbl1','xlbl2'], ['ylbl1','ylbl2'],
['ixlbl1','ixlbl2'], ['iylbl1','iylbl2'],
'Xlbl','Ylbl','innerXlbl','innerYlbl', colormap,
sum_up=False, hover_info=False) # no hover info or sum_up
pygsti.report.workspaceplots.generate_boxplot(
mxs, ['xlbl1','xlbl2'], ['ylbl1','ylbl2'],
['ixlbl1','ixlbl2'], ['iylbl1','iylbl2'],
'Xlbl','Ylbl','innerXlbl','innerYlbl', colormap,
sum_up=True, invert=True) #ignores invert
# ----- circuit_color_boxplot -----
germs = preps = effects = gstrs
gss = pygsti.obj.LsGermsStructure([1,2],germs,preps,effects)
for L in [1,2]:
for germ in germs:
gss.add_plaquette(germ*L, L, germ)
gss2 = pygsti.obj.LsGermsStructure([1,2],germs,preps,effects)
for L in [1,2]:
for germ in germs:
gss2.add_plaquette(germ*L + pygsti.obj.Circuit(('Gy',)), L, germ) # makes base strs != germ^some_power
gss3 = gss.copy()
cls = type('DummyClass', pygsti.obj.LsGermsStructure.__bases__, dict(pygsti.obj.LsGermsStructure.__dict__))
gss3.__class__ = cls # mimic a non-LsGermsStructure object when we don't actually have any currently (HACK)
assert(not isinstance(gss3, pygsti.obj.LsGermsStructure))
pygsti.report.workspaceplots.circuit_color_boxplot(
gss, mxs, colormap, sum_up=True)
pygsti.report.workspaceplots.circuit_color_boxplot(
gss, mxs, colormap, sum_up=False)
pygsti.report.workspaceplots.circuit_color_boxplot(
gss2, mxs, colormap, sum_up=True)
pygsti.report.workspaceplots.circuit_color_boxplot(
gss2, mxs, colormap, sum_up=False)
# ----- circuit_color_scatterplot -----
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss, mxs, colormap, sum_up=True)
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss, mxs, colormap, hover_info=False) # no hoverinfo
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss2, mxs, colormap, hover_info=True) # gss2 case
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss2, mxs, colormap, hover_info=True) # gss2 case
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss, mxs, colormap, sum_up=True, addl_hover_submxs={'qty': mxs} ) # just reuse mxs
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss, mxs, colormap, sum_up=False, addl_hover_submxs={'qty': mxs} ) # just reuse mxs
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss3, mxs, colormap, sum_up=True, hover_info=True) # gss3 case
pygsti.report.workspaceplots.circuit_color_scatterplot(
gss3, mxs, colormap, sum_up=False, hover_info=True) # gss3 case
# ---- circuit_color_histogram ----
negmx = -1*np.ones((2,2),'d')
mxs_allneg = [ [negmx, negmx],
[negmx, negmx] ]
pygsti.report.workspaceplots.circuit_color_histogram(
gss, mxs_allneg, colormap) # when there's no counts to plot
# ---- opmatrix_color_boxplot ----
pygsti.report.workspaceplots.opmatrix_color_boxplot(
np.identity(4,'d'), -1.0, 1.0, mx_basis="pp", mx_basis_y="gm")
# test weird case when there's different bases on diff axes
# ---- matrix_color_boxplot ----
pygsti.report.workspaceplots.matrix_color_boxplot(
np.identity(16,'d'), colormap=colormap, grid="black:2") # test "gridcolor:linewidth" format of grid argument.
if __name__ == "__main__":
unittest.main(verbosity=2)