def long(generations:int):
data = "/netapp/home/tianjiao.zhang/data/microstates.dat";
targetFreqs = "/netapp/home/tianjiao.zhang/data/ecDHFR_openseq_bacterial_representative_final_align_trim.fasta";
MACROSTATES = enum("E-DHF-NADPH", "E-NADPH", "E-THF", "E-THF-NADPX", "TS");
RESIDUES = enum('A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'V', 'W', 'Y');
ensembleSizes = numpy.array([16, 24, 32, 64, 128]);
backrubTemps = numpy.array([0.3, 0.6, 0.9, 1.2, 1.5, 1.8]);
boltzmannTemps = numpy.array([-1, 5]);
steepnessRange = numpy.array([1, 7]);
minWeights = numpy.array([0, 0, 0, 0, 0]);
maxWeights = numpy.array([1, 1, 1, 1, 1]);
optimizer = Optimizer(MACROSTATES, True);
optimizer.readTargetFrequencies(targetFreqs);
optimizer.readFormattedMicrostateData(data);
search = CuckooSearch(optimizer.models, JensenShannonDistance(optimizer.targetFrequencies), True, 128, 1.25, 0.25);
search.setMaxIterations(generations);
search.setParamBounds(ensembleSizes, backrubTemps, boltzmannTemps, steepnessRange, minWeights, maxWeights);
search.setAllSearchToTrue();
search.suppressOutputs = True;
optimizer.useAlgorithm(search);
optimizer.optimize();
now = datetime.now();
optimizer.writeFrequenciesToFASTA(optimizer.getBestFrequencies(), "var ensembles " + now.strftime('%Y%m%d%H%M') + ".fasta");
optimizer.writeBestParamsToText("var ensembles " + now.strftime('%Y%m%d%H%M'));
def smallTestBoltz():
print("Hello!\n");
MACROSTATES = enum("E-DHF-NADPH", "E-NADPH", "E-THF", "E-THF-NADPX", "TS");
RESIDUES = enum('A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'V', 'W', 'Y');
ensembleSizes = numpy.array([128]);
backrubTemps = numpy.array([0.3, 0.6, 0.9, 1.2, 1.5, 1.8]);
boltzmannTemps = numpy.array([-1, 5]);
steepnessRange = numpy.array([1, 7]);
minWeights = numpy.array([0, 0, 0, 0, 0]);
maxWeights = numpy.array([1, 1, 1, 1, 1]);
print("Initializing objects\n");
targetFreqs = "C:\\Users\\Candy\\SkyDrive\\Documents\\rotation 2\\ecDHFR_openseq_bacterial_representative_final_align_trim.fasta";
targetFreqsAlt = "C:\\Users\\Candy_000\\SkyDrive\\Documents\\rotation 2\\ecDHFR_openseq_bacterial_representative_final_align_trim.fasta";
dataMicro = "C:\\Users\\Candy\\SkyDrive\\Documents\\rotation 2\\20160120_M20_enumeration_scores\\microstates.dat";
dataMicroAlt = "C:\\Users\\Candy_000\\SkyDrive\\Documents\\rotation 2\\20160120_M20_enumeration_scores\\microstates.dat";
optimizer = Optimizer(MACROSTATES, True);
try:
optimizer.readTargetFrequencies(targetFreqs);
optimizer.readFormattedMicrostateData(dataMicro);
except FileNotFoundError:
optimizer.readtargetfrequencies(targetfreqsalt);
optimizer.readFormattedMicrostatedata(datamicroalt);
search = CuckooSearch(optimizer.models, JensenShannonDistance(optimizer.targetFrequencies), True, 64, 1, 0.25);
search.setMaxIterations(2048);
search.setParamBounds(ensembleSizes, backrubTemps, boltzmannTemps, steepnessRange, minWeights, maxWeights);
search.setSearchParameters(False, True, True, True, numpy.array([True, True, True, True, True, True]));
optimizer.useAlgorithm(search);
optimizer.optimize();
now = datetime.now();
optimizer.writeFrequenciesToFASTA(optimizer.getBestFrequencies(), "var ensembles " + now.strftime('%Y%m%d%H%M') + ".fasta");
optimizer.writeBestParamsToText("var ensembles " + now.strftime('%Y%m%d%H%M'));
#for i in range(8):
# thread = optimizerThread();
# thread.copyOptimizer(optimizer);
# thread.run();
return None;
steepnessRange = numpy.array([0.5, 5]); minWeights = numpy.array([0, 0, 0, 0, 0]); maxWeights = numpy.array([1, 1, 1, 1, 1]); data = "/netapp/home/tianjiao.zhang/data/microstates.dat"; targetFreqs = "/netapp/home/tianjiao.zhang/data/ecDHFR_openseq_bacterial_representative_final_align_trim.fasta"; dataAlt = "C:\\users\\candy\\skydrive\\documents\\rotation 2\\DHFR microstates\\microstates.dat"; targetFreqsAlt = "C:\\users\\candy\\skydrive\\documents\\rotation 2\\ecDHFR_openseq_bacterial_representative_final_align_trim.fasta"; optimizer = Optimizer(MACROSTATES, True); # slightly different paths on my two computers optimizer.readTargetFrequencies(targetFreqs); optimizer.readFormattedMicrostateData(data); if similarityMeasure == 0: search = CuckooSearch(optimizer.models, JensenShannonDistance(optimizer.targetFrequencies), True, 32, 1, 0.25); elif similarityMeasure == 1: search = CuckooSearch(optimizer.models, CosineSimilarity(optimizer.targetFrequencies), True, 32, 1, 0.25); elif similarityMeasure == 2: search = CuckooSearch(optimizer.models, KLDivergence(optimizer.targetFrequencies), True, 32, 1, 0.25); elif similarityMeasure == 3: search = CuckooSearch(optimizer.models, Chi2Kernel(optimizer.targetFrequencies), True, 32, 1, 0.25); elif similarityMeasure == 4: search = CuckooSearch(optimizer.models, EntropyWeightedSimilarity(JensenShannonDistance(), optimizer.targetFrequencies), True, 32, 1, 0.25); elif similarityMeasure == 5: search = CuckooSearch(optimizer.models, EntropyWeightsMixedSimilarity(JensenShannonDistance(), CosineSimilarity(), optimizer.targetFrequencies), True, 32, 1, 0.25); else: search = CuckooSearch(optimizer.models, JensenShannonDistance(optimizer.targetFrequencies), True, 32, 1, 0.25);
