Source code for pkpd.protocols.protocol_pkpd_statistics_labels

# **************************************************************************
# *
# * Authors:     Carlos Oscar Sorzano (info@kinestat.com)
# *
# * Kinestat Pharma
# *
# * This program is free software; you can redistribute it and/or modify
# * it under the terms of the GNU General Public License as published by
# * the Free Software Foundation; either version 2 of the License, or
# * (at your option) any later version.
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# * This program is distributed in the hope that it will be useful,
# * but WITHOUT ANY WARRANTY; without even the implied warranty of
# * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# * GNU General Public License for more details.
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# * You should have received a copy of the GNU General Public License
# * along with this program; if not, write to the Free Software
# * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
# * 02111-1307  USA
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# *  All comments concerning this program package may be sent to the
# *  e-mail address 'info@kinestat.com'
# *
# **************************************************************************

import pyworkflow.protocol.params as params
from .protocol_pkpd import ProtPKPD
from pkpd.objects import PKPDVariable
from pkpd.pkpd_units import strUnit
import os
import numpy as np
import scipy.stats

[docs]class ProtPKPDStatisticsLabel(ProtPKPD): """ Calculate statistics of the labels\n Protocol created by http://www.kinestatpharma.com\n """ _label = 'statistics labels' #--------------------------- DEFINE param functions -------------------------------------------- def _defineParams(self, form): form.addSection('Input') form.addParam('inputExperiment', params.PointerParam, label="Input experiment", important=True, pointerClass='PKPDExperiment', help='Select an experiment with samples') #--------------------------- INSERT steps functions -------------------------------------------- def _insertAllSteps(self): self._insertFunctionStep('runStatistcs',self.inputExperiment.get().getObjId()) #--------------------------- STEPS functions --------------------------------------------
[docs] def runStatistcs(self, objId): experiment = self.readExperiment(self.inputExperiment.get().fnPKPD) self.printSection("Calculating statistical descriptors") fnStatistics = self._getPath("statistics.txt") fhOut = open(fnStatistics,'w') for varName, variable in experiment.variables.items(): if variable.role == PKPDVariable.ROLE_LABEL: varValues = experiment.getSubGroupLabels("True",varName) if variable.varType == PKPDVariable.TYPE_TEXT: self.doublePrint(fhOut,"%s ------------"%varName) counter = {} for value in varValues: if value in counter: counter[value]+=1 else: counter[value]=1 for value in counter: self.doublePrint(fhOut,"Value=%s Total count=%d (%f%%)"%(value,counter[value],100*float(counter[value])/len(varValues))) elif variable.varType == PKPDVariable.TYPE_NUMERIC: self.doublePrint(fhOut,"%s [%s] ------------"%(varName,strUnit(variable.units.unit))) varValues = np.asarray(varValues,np.double) self.doublePrint(fhOut,"Number of observations= %d"%len(varValues)) self.doublePrint(fhOut,"Range= [%f,%f]"%(np.min(varValues),np.max(varValues))) self.doublePrint(fhOut,"Mean= %f"%np.mean(varValues)) self.doublePrint(fhOut,"StdDev= %f"%np.std(varValues)) self.doublePrint(fhOut,"Skewness= %f"%scipy.stats.skew(varValues)) self.doublePrint(fhOut,"Kurtosis= %f"%scipy.stats.kurtosis(varValues)) self.doublePrint(fhOut,"Quantile 5%%= %f"%np.percentile(varValues,5)) self.doublePrint(fhOut,"Quantile 25%%= %f"%np.percentile(varValues,25)) self.doublePrint(fhOut,"Quantile 50%%= %f"%np.percentile(varValues,50)) self.doublePrint(fhOut,"Quantile 75%%= %f"%np.percentile(varValues,75)) self.doublePrint(fhOut,"Quantile 95%%= %f"%np.percentile(varValues,95)) self.doublePrint(fhOut," ") fhOut.close()
#--------------------------- INFO functions -------------------------------------------- def _summary(self): msg = [] fnStatistics = self._getPath("statistics.txt") if os.path.exists(fnStatistics): self.addFileContentToMessage(msg,fnStatistics) return msg