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)