How to use psput method in fMBT

Best Python code snippet using fMBT_python

trainCM.py

Source:trainCM.py Github

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1#!/​usr/​bin/​env python22# -*- coding: utf-8 -*-3"""4Created on Thu Nov 16 11:08:01 20175@author: p6"""7import numpy as np8import matplotlib.pyplot as plt9import tensorflow as tf10import time11from epics import caget,caput12fName='trainCMData'13dataOri=np.loadtxt(fName)14dataBPM=dataOri[:,6:22]15dataPS=dataOri[:,70:86]16numItem,numBPM= np.shape(dataBPM)17numPS=np.shape(dataPS)[1]18##-------------##----------------##-------------------19def GenWeight(shape):20 initial = tf.truncated_normal(shape, stddev=1.)21 return tf.Variable(initial)22def GenBias(shape):23 initial=GenWeight((1,shape(0)))24 return initial[0,:]25 26def PreTrain(psSetRec,bpmRec,batchSize):27 numItem=np.shape(bpmRec)[0]28 idChoose_0=np.random.randint(0,high=numItem,size=(batchSize))29 idChoose_1=np.random.randint(1,high=numItem,size=(batchSize))30 31 d_psChoose=psSetRec[idChoose_1,:]-psSetRec[idChoose_0,:]32 d_BPMChoose=bpmRec[idChoose_1,:]-bpmRec[idChoose_0,:]33 34 # x0=bpmRec[idChoose_0,:]35 #dx=d_BPMChoose36 #X=np.hstack((x0,dx))37 38 X=d_BPMChoose39 Y=d_psChoose40 41 return X,Y42def RunTrain(se,opt,loss,numEpoch,batchSize,psSetRec,bpmRec):43 lossRecRec=[]44 for _ in range(numEpoch):45 X,Y=PreTrain(psSetRec,bpmRec,batchSize)46 47 se.run(opt,feed_dict={xIn:X,yIn:Y})48 if _% 50==0:49 lossRecTmp=se.run(loss,feed_dict={xIn:X,yIn:Y})50 lossRecRec.append(lossRecTmp)51 return lossRecRec52 53learningRate=0.005 #--------------------------------------------54numEpoch=50000055batchSize=5056numInput=numBPM57numOutput=numPS58xIn=tf.placeholder(tf.float32,shape=(None,numInput))59yIn=tf.placeholder(tf.float32,shape=(None,numOutput))60'''61num1=862w1=GenWeight((numInput,num1))63b1= GenWeight((1,num1))[0,:]64x1=tf.nn.relu(tf.nn.xw_plus_b(xIn,w1,b1))65#66num2=numOutput67w2=GenWeight((num1,num2))68b2= GenWeight((1,num2))[0,:]69x2=tf.nn.xw_plus_b(x1,w2,b2)70'''71w0=GenWeight((numInput,numOutput))72x0=tf.matmul(xIn,w0)73xOut=x074yOut=yIn75loss=tf.losses.mean_squared_error(xOut,yOut)76train=tf.train.AdamOptimizer(learningRate)77opt=train.minimize(loss)78if vars().has_key('se'):79 se.close()80else:81 se=tf.Session()82se.run(tf.global_variables_initializer())83######## --------- Train ------------------84plt.close('all')85lossRec=[]86lossMeanRec=[]87rAimRec=[]88for _ in range(numEpoch):89 X,Y=PreTrain(dataPS,dataBPM,batchSize)90 91 se.run(opt,feed_dict={xIn:X,yIn:Y})92 if _% 50==0:93 lossRecTmp=se.run(loss,feed_dict={xIn:X,yIn:Y})94 xAim=np.zeros((1,numBPM))-np.mean(dataBPM,axis=0)[np.newaxis,:]95 yAim=se.run(xOut,feed_dict={xIn:xAim})[0]96 lossRec.append(lossRecTmp)97 lossMeanRec.append(np.mean(lossRec))98 rAimRec.append(np.sum(np.square(yAim)))99 if len(lossRec)>200:100 lossRec.pop(0)101 lossMeanRec.pop(0)102 rAimRec.pop(0)103 plt.figure(1)104 plt.clf()105 plt.hold('on')106 plt.plot(lossRec,'r')107 plt.plot(lossMeanRec,'g')108 plt.grid('on')109 plt.title(_)110 plt.pause(0.01)111 112 plt.figure(2)113 plt.clf()114 plt.plot(yAim,'r-*')115 plt.grid('on')116 plt.title(_)117 plt.pause(0.01)118 119 plt.figure(3)120 plt.clf()121 plt.plot(rAimRec,'g-')122 plt.grid('on')123 plt.title(_)124 plt.pause(0.01) 125 ##-------- Final ------------------------126psList=[\127 'MEBT_PS:DCH_06:ISet','MEBT_PS:DCV_06:ISet', \128 'MEBT_PS:DCH_07:ISet','MEBT_PS:DCV_07:ISet', \129 'HCM1_PS:DCH_01:ISet','HCM1_PS:DCV_01:ISet', \130 'HCM1_PS:DCH_02:ISet','HCM1_PS:DCV_02:ISet', \131 'HCM1_PS:DCH_03:ISet','HCM1_PS:DCV_03:ISet', \132 'HCM1_PS:DCH_04:ISet','HCM1_PS:DCV_04:ISet', \133 'HCM1_PS:DCH_05:ISet','HCM1_PS:DCV_05:ISet', \134 'HCM1_PS:DCH_06:ISet','HCM1_PS:DCV_06:ISet', \135 ]136bpmList=[\137 'BPM:4-X11','BPM:4-Y11',\138 'BPM:5-X11','BPM:5-Y11',\139 'BPM:6-X11', 'BPM:6-Y11',\140 'BPM:7-X11','BPM:7-Y11',\141 'BPM:8-X11','BPM:8-Y11',\142 'BPM:9-X11','BPM:9-Y11',\143 'BPM:10-X11','BPM:10-Y11',\144 'BPM:11-X11','BPM:11-Y11',\145 ]146def GetBPM(bpmList):147 bpmNow=[]148 for iBPM in bpmList:149 bpmNow.append(caget(iBPM))150 bpmNow=np.array(bpmNow)[np.newaxis,:]151 return bpmNow152def GetPS(psSetList):153 psNow=[]154 for iPS in psSetList:155 psNow.append(caget(iPS))156 psNow=np.array(psNow)[np.newaxis,:]157 return psNow158def PutPS(psSetList,psSetNow):159 for i in range(len(psSetList)):160 iStr,iVal=psSetList[i],psSetNow[i]161 caput(iStr,iVal)162def LogWrite(fid,X):163 fid.writelines('#=========================')164 timeNow='# '+time.asctime()165 fid.writelines(timeNow)166 fid.writelines('\n')167 168 for i in X:169 for j in i:170 fid.writelines('%.2f ' %j)171 fid.writelines('\n')172 173bpmNow=GetBPM(bpmList)174bpmAim=0-bpmNow175psAim=se.run(xOut,feed_dict={xIn:bpmAim})176psNow=GetPS(psList)177psPut=(psNow+psAim)[0]178for i in range(len(psAim)):179 if i <4:180 if psPut[i]<-15:181 psPut[i]=-15182 if psPut[i]>15:183 psPut[i]=15184 else:185 if psPut[i]<-65:186 psPut[i]=-65187 if psPut[i]>65:188 psPut[i]=65189psPut=np.round(psPut*100)/​100190print psPut191PutPS(psList,psPut)192time.sleep(80)193bpmUpdate=GetBPM(bpmList)194fid=open('TestLogVIP','a+')195LogWrite(fid,(bpmNow[0],bpmAim[0],psAim[0],psNow[0],psPut,bpmUpdate[0]))196fid.close()197plt.figure(9986)198plt.plot(psAim[0],'-*')199plt.figure(9987)200plt.plot(psNow[0],'-*')201plt.figure(9988)202plt.plot(bpmUpdate[0],'-*')203'''204for i in range(numBPM):205 plt.figure('BPM')206 plt.clf()207 plt.hist(dataBPM[:,i],100)208 plt.grid('on')209 plt.title(i)210 plt.pause(1)211for i in range(numPS):212 plt.figure('PS')213 plt.clf()214 plt.hist(dataPS[:,i],100)215 plt.grid('on')216 plt.title(i)217 plt.pause(1)218'''219'''220class NNMat():221 def __init__(self,numInput,numOutput,learningRate):222 self.numInput=numInput223 self.numOutput=numOutput224 self.learningRate=learningRate225 def GenWeight(shape):226 initial = tf.truncated_normal(shape, stddev=1.)227 return tf.Variable(initial)228 def GenBias(shape):229 initial = tf.constant(1., shape=shape)230 return tf.Variable(initial)231'''232 ...

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pubsub.py

Source:pubsub.py Github

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1__all__ = ['PublishSubscribeQueue']2import events3from util import priority45class PSPut(events.Operation):6 __slots__ = ('queue', 'message', 'key')78 def __init__(self, queue, message, key, **kws):9 super(PSPut, self).__init__(**kws)10 self.queue = queue11 self.message = message12 self.key = key1314 def process(self, sched, coro):15 super(PSPut, self).process(sched, coro)16 self.queue.messages.append(self.message)17 result = [self.message]18 for getkey in self.queue.active_subscribers:19 self.queue.subscribers[getkey] += 120 getop, getcoro = self.queue.active_subscribers[getkey]21 getop.result = result22 if getop.prio:23 sched.active.appendleft((getop, getcoro))24 else:25 sched.active.append((getop, getcoro))26 self.queue.active_subscribers.clear()27 if self.prio & priority.CORO:28 return self, coro29 else:30 if self.prio & priority.OP:31 sched.active.appendleft((self, coro))32 else:33 sched.active.append((self, coro))34 return None, None3536class PSGet(events.TimedOperation):37 __slots__ = ('queue', 'result', 'key')3839 def __init__(self, queue, key, **kws):40 super(PSGet, self).__init__(**kws)41 self.queue = queue42 self.key = key4344 def process(self, sched, coro):45 super(PSGet, self).process(sched, coro)46 key = self.key or coro47 assert key in self.queue.subscribers48 level = self.queue.subscribers[key]49 queue_level = len(self.queue.messages)50 if level < queue_level:51 self.result = self.queue.messages[level:] if level \52 else self.queue.messages53 self.queue.subscribers[key] = queue_level54 return self, coro55 else:56 self.queue.active_subscribers[key] = self, coro5758 def finalize(self, sched):59 super(PSGet, self).finalize(sched)60 return self.result6162 def cleanup(self, sched, coro):63 for key in self.queue.active_subscribers:64 getop, getcoro = self.queue.active_subscribers[key]65 if coro is getcoro:66 assert getop is self6768 del self.queue.active_subscribers[key]69 return True7071class PSSubscribe(events.Operation):72 __slots__ = ('queue', 'key')7374 def __init__(self, queue, key, **kws):75 super(PSSubscribe, self).__init__(**kws)76 self.queue = queue77 self.key = key7879 def process(self, sched, coro):80 super(PSSubscribe, self).process(sched, coro)81 self.queue.subscribers[self.key or coro] = 082 return self, coro8384class PSUnsubscribe(events.Operation):85 __slots__ = ('queue', 'key')8687 def __init__(self, queue, key, **kws):88 super(PSUnsubscribe, self).__init__(**kws)89 self.queue = queue90 self.key = key9192 def process(self, sched, coro):93 super(PSUnsubscribe, self).process(sched, coro)94 del self.queue.subscribers[self.key or coro]95 return self, coro969798class PublishSubscribeQueue:99 """A more robust replacement for the signal operations.100 A coroutine subscribes itself to a PublishSubscribeQueue and get new101 published messages with _fetch_ method.102 """103 def __init__(self):104 self.messages = []105 self.subscribers = {}106 self.active_subscribers = {} # holds waiting fetch ops107108 def publish(self, message, key=None, **kws):109 """Put a message in the queue and updates any coroutine wating with110 fetch. *works as a coroutine operation*"""111 return PSPut(self, message, key, **kws)112113 def subscribe(self, key=None, **kws):114 """Registers the calling coroutine to the queue. Sets the update index115 to 0 - on fetch, that coroutine will get all the messages from the116 queue. *works as a coroutine operation*"""117 return PSSubscribe(self, key, **kws)118119 def unsubscribe(self, key=None, **kws):120 """Unregisters the calling coroutine to the queue. """121 # TODO: unittest122 return PSUnsubscribe(self, key, **kws)123124 def fetch(self, key=None, **kws):125 """Get all the new messages since the last fetch. Returns a list126 of messages. *works as a coroutine operation*"""127 return PSGet(self, key, **kws)128129 def compact(self):130 """Compacts the queue: removes all the messages from the queue that131 have been fetched by all the subscribed coroutines.132 Returns the number of messages that have been removed."""133 if self.subscribers:134 level = min(self.subscribers.itervalues())135 if level:136 del self.messages[:level]137 return level138 else:139 level = len(self.messages)140 del self.messages[:] ...

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task_7_1.py

Source:task_7_1.py Github

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1# задача 7. Вариант 1.2# Напишите программу, которая бы при запуске случайным образом отображала3# название одного из семи чудес светаю4# Болатукаев.А.З5# 21.03.20176import random7sput = ["Атос", "Портос", "Арамис"]8rsput = random.choice(sput)9score = 1010psput = ""11while psput != rsput:12 psput = input("Назовите одиного из трех товарищей д'Артаньяна: ")13 if psput == rsput:14 print("\nХорооош!")15 print("У вас", score,"баллов.")16 else:17 score-=518 print("\nНе правильно((\nПопробуйте еще раз\n\n")...

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