def test_json(self):
data = {
"firstName": "Jane",
"lastName": "Doe",
"hobbies": ["running", "sky diving", "singing"],
"age": 35,
"children": [
{
"firstName": "Alice",
"age": 6
},
{
"firstName": "Bob",
"age": 8
}
]
}
person = Person("Dima", 25)
self.assertEqual(to_json(person),json.dumps(person.__dict__))
self.assertEqual(to_json(data), json.dumps(data))
def computeHist(self):
self.rmsAnalysis = rmsIterator(self.fileInput,self.framesPerChunk)
self.rmsAnalysis.iterate(self.howManyChunks)
print "<br>I'm trying to compute."
fig = plt.figure()
fig.set_size_inches(8,8)
fig.subplots_adjust(wspace=0.5)
fig.subplots_adjust(hspace=0.35)
#fig.tight_layout()
ax1 = fig.add_subplot(221)
fileAx1,bins1,trash1 = plt.hist(self.rmsAnalysis.returnDataT1P0[:],bins=8,histtype='step',normed=True,label = 'B'+str(self.rmsAnalysis.beam)+':T'+str("%.1f" % (self.rmsAnalysis.tune1/1e6))+":P0")
ax1.set_xticks(bins1)
ax1.xaxis.set_major_formatter(FormatStrFormatter('%0.2f'))
plt.setp(ax1.get_xticklabels(), rotation=90)
ax1.set_xlabel('Step')
ax1.set_ylabel('Count')
ax1.legend(loc='best')
ax2 = fig.add_subplot(222)
fileAx2,bins2,trash2 = plt.hist(self.rmsAnalysis.returnDataT1P1[:],bins=8,histtype='step',normed=True,label = "B"+str(self.rmsAnalysis.beam)+":T"+str("%.1f" % (self.rmsAnalysis.tune1/1e6))+":P1")
ax2.set_xticks(bins2)
ax2.xaxis.set_major_formatter(FormatStrFormatter('%0.2f'))
plt.setp(ax2.get_xticklabels(), rotation=90)
ax2.set_xlabel('Step')
ax2.set_ylabel('Count')
ax2.legend(loc='best')
ax3 = fig.add_subplot(223)
fileAx3,bins3,trash3 = plt.hist(self.rmsAnalysis.returnDataT2P0[:],bins=8,histtype='step',normed=True,label = "B"+str(self.rmsAnalysis.beam)+":T"+str("%.1f" % (self.rmsAnalysis.tune2/1e6))+":P0")
ax3.set_xticks(bins3)
ax3.xaxis.set_major_formatter(FormatStrFormatter('%0.2f'))
plt.setp(ax3.get_xticklabels(), rotation=90)
ax3.set_xlabel('Step')
ax3.set_ylabel('Count')
ax3.legend(loc='best')
ax4 = fig.add_subplot(224)
fileAx4,bins4,trash4 = plt.hist(self.rmsAnalysis.returnDataT2P1[:],bins=8,histtype='step',normed=True,label = "B"+str(self.rmsAnalysis.beam)+":T"+str("%.1f" % (self.rmsAnalysis.tune2/1e6))+":P1")
ax4.set_xticks(bins4)
ax4.xaxis.set_major_formatter(FormatStrFormatter('%0.2f'))
plt.setp(ax4.get_xticklabels(), rotation=90)
ax4.set_xlabel('Step')
ax4.set_ylabel('Count')
ax4.legend(loc='best')
fig.savefig(self.fileOutput+".png")
to_json(self.rmsAnalysis.jsonT1P0,self.fileOutput+"_t1p0.json")
to_json(self.rmsAnalysis.jsonT1P1,self.fileOutput+"_t1p1.json")
to_json(self.rmsAnalysis.jsonT2P0,self.fileOutput+"_t2p0.json")
to_json(self.rmsAnalysis.jsonT2P1,self.fileOutput+"_t2p1.json")
def compute(self):
self.rmsAnalysis = rmsIterator(self.fileInput,self.framesPerChunk)
self.rmsAnalysis.iterate(self.howManyChunks)
print "<br>I'm trying to compute."
fig = plt.figure()
fig.set_size_inches(8,8)
fig.subplots_adjust(wspace=0.5)
fig.subplots_adjust(hspace=0.35)
#fig.tight_layout()
ax1 = fig.add_subplot(221)
ax1.set_xlabel('Time ('+str("%.6f" % (self.framesPerChunk*self.howManyChunks*4096/19.6e6))+' Seconds total)')
ax1.set_ylabel('ADC Magnitude')
ax2 = fig.add_subplot(222)
ax2.set_xlabel('Time ('+str("%.6f" % (self.framesPerChunk*self.howManyChunks*4096/19.6e6))+' Seconds total)')
ax2.set_ylabel('ADC Magnitude')
ax3 = fig.add_subplot(223)
ax3.set_xlabel('Time ('+str("%.6f" % (self.framesPerChunk*self.howManyChunks*4096/19.6e6))+' Seconds total)')
ax3.set_ylabel('ADC Magnitude')
ax4 = fig.add_subplot(224)
ax4.set_xlabel('Time ('+str("%.6f" % (self.framesPerChunk*self.howManyChunks*4096/19.6e6))+' Seconds total)')
ax4.set_ylabel('ADC Magnitude')
ax1.plot(self.rmsAnalysis.returnDataT1P0[:],label='B'+str(self.rmsAnalysis.beam)+':T'+str("%.1f" % (self.rmsAnalysis.tune1/1e6))+':P0')
ax2.plot(self.rmsAnalysis.returnDataT1P1[:],label='B'+str(self.rmsAnalysis.beam)+':T'+str("%.1f" % (self.rmsAnalysis.tune1/1e6))+':P1')
ax3.plot(self.rmsAnalysis.returnDataT2P0[:],label='B'+str(self.rmsAnalysis.beam)+':T'+str("%.1f" % (self.rmsAnalysis.tune2/1e6))+':P0')
ax4.plot(self.rmsAnalysis.returnDataT2P1[:],label='B'+str(self.rmsAnalysis.beam)+':T'+str("%.1f" % (self.rmsAnalysis.tune2/1e6))+':P1')
ax1.legend(loc='best')
ax2.legend(loc='best')
ax3.legend(loc='best')
ax4.legend(loc='best')
fig.savefig(self.fileOutput)
to_json(self.rmsAnalysis.jsonT1P0,self.fileOutput+"_t1p0.json")
to_json(self.rmsAnalysis.jsonT1P1,self.fileOutput+"_t1p1.json")
to_json(self.rmsAnalysis.jsonT2P0,self.fileOutput+"_t2p0.json")
to_json(self.rmsAnalysis.jsonT2P1,self.fileOutput+"_t2p1.json")
def onResultsReady(self):
with open(self.resultsPath, 'w') as fid:
output = {"data": self.results}
fid.write(to_json(output))
def main(bagfilename, motiontopic, maptopic, output_file):
bagfile = rosbag.Bag(bagfilename, mode='r')
# data structure that maps timestamp to a dictionary
alltimesteps = {}
# parse fullstate topic
for _, msg, _ in bagfile.read_messages(topics=motiontopic):
entry = {}
ts = msg.header.stamp.secs * 1000000000 + msg.header.stamp.nsecs
entry['group'] = msg.group
entry['ImagePath'] = ''
entry['Timestamp'] = ts
entry['Tsb_XYZ'] = rosvec_to_list(msg.gsb.translation)
entry['qsb_WXYZ'] = rosquat_to_list(msg.gsb.rotation)
entry['Tbc_XYZ'] = rosvec_to_list(msg.gbc.translation)
entry['qbc_WXYZ'] = rosquat_to_list(msg.gbc.rotation)
entry['Tsc_XYZ'] = rosvec_to_list(msg.gsc.translation)
entry['qsc_WXYZ'] = rosquat_to_list(msg.gsc.rotation)
entry['Vsb_XYZ'] = rosvec_to_list(msg.Vsb)
entry['Pstate'] = [msg.MotionStateSize, list(msg.covariance)]
entry['MeasurementUpdateInitialized'] = bool(
msg.MeasurementUpdateInitialized)
entry['inn_Tsb'] = rosvec_to_list(msg.inn_Tsb)
entry['inn_Wsb'] = rosvec_to_list(msg.inn_Wsb)
entry['inn_Vsb'] = rosvec_to_list(msg.inn_Vsb)
entry['bg'] = rosvec_to_list(msg.bg)
entry['ba'] = rosvec_to_list(msg.ba)
entry['qg_WXYZ'] = rosquat_to_list(msg.qg)
entry['td'] = msg.td
entry['Ca'] = list(msg.Ca)
entry['Cg'] = list(msg.Cg)
alltimesteps[ts] = entry
# Parse map topic
for _, msg, _ in bagfile.read_messages(topics=maptopic):
ts = msg.header.stamp.secs * 1000000000 + msg.header.stamp.nsecs
entry = alltimesteps[ts]
feature_positions = []
feature_ids = []
feature_covariances = []
for feature in msg.features:
feature_ids.append(feature.id)
feature_positions.extend(rosvec_to_list(feature.Xs))
cov = roslist_to_list(feature.covariance, 9)
feature_covariances.extend(
[cov[0], cov[1], cov[2], cov[4], cov[5], cov[8]])
entry['num_instate_features'] = msg.num_features
entry['feature_positions'] = feature_positions
entry['feature_covs'] = feature_covariances
entry['feature_ids'] = feature_ids
alltimesteps[ts] = entry
# sort timestamps
timestamps = alltimesteps.keys()
timestamps.sort()
# create list of dictionaries
final_list = []
for ts in timestamps:
final_list.append(alltimesteps[ts])
json_string = to_json.to_json(final_list)
with open(output_file, 'w') as fid:
fid.write(json_string)
def write_json(self, filename):
json_string = to_json(self.estimator_results)
with open(filename, 'w') as fid:
fid.write(json_string)
if args.to_json:
num_generations = population.num_generations
clear_index = max(num_generations - args.gen_back, 0)
to_clear = population.generations[clear_index].members
for node in to_clear:
node.suspected_mother = None
node.suspected_mother_id = None
node.suspected_father = None
node.suspected_father_id = None
unlabeled_nodes = set(chain.from_iterable(generation.members
for generation
in population.generations[-3:]))
related_nodes = related_pairs(unlabeled_nodes, labeled_nodes, population,
args.gen_back)
json = to_json(population, labeled_nodes, related_nodes)
with open(args.to_json, "w") as json_file:
json_file.write(json)
exit()
print("Loading recombination data.")
recombinators = recombinators_from_directory("../data/recombination_rates/")
chrom_sizes = recombinators[Sex.Male]._num_bases
genome_generator = RecombGenomeGenerator(chrom_sizes)
print("Populating length classifier.")
clobber = not (args.recover or args.num_iterations == 0)
classifier = generate_classifier(population, labeled_nodes,
def test2(self):
self.assertEqual(to_json.to_json(self.obj1), json.dumps(self.obj1))
def test_to_json(self):
test_object = []
obj = to_json.to_json(test_object)
self.assertIsInstance(obj, str)
