Importing files
Signed-off-by: Bernardo Carvalho <bernardo.carvalho@tecnico.ulisboa.pt>
This commit is contained in:
285
Trees/IpfnDevices/DEMOADC1.py
Executable file
285
Trees/IpfnDevices/DEMOADC1.py
Executable file
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from MDSplus import Device, Data, Range, Dimension, Window, Signal, Int16Array
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from ctypes import CDLL, c_char_p, c_short, byref, c_int
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class DEMOADC1(Device):
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"""A Demo 4 Channel, 16 but digitizer"""
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# This class inherits from the generic Device class
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# Class Device provides the basic methods required by MDSplus, in particular the Add metod
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# called when a new instance of this device has to be created in a tree in editing
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# it is therefore only necessary to add here the device specific methods such as init and store
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# It is however necessary to define the structure of the device, so that the superclass' Add method can
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# build the appropiate device subtree. This information is specified as a list of dictionaries
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# every element of the list specifies a node of the subtree associated with the device. The mandatory dictionary items
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# for each node are:
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# - path : the path name relative to the subtree root of the node
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# - type : the type (usage) of the node, which can be either 'text', 'numeric', 'signal', 'action', 'structure'
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# optional dictionary items formeach node are:
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# - value : initial value forn that node
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# - valueExpr : initial value when specified as an expression
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# - options : a (list of) NCI options for the tree node, such as 'no_write_model', 'no_write_shot', 'compress_on_put'
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# field parts will contain the list of dictionaries, and will be used by Device superclass.
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#
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# in the following methods, defice fields are referred by the syntax: self.<field_name>, where field_name is derived by the
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# path of the corresponding tree node relative to the subtree (as specified by the corresponding path dictionary item), where #letters are lowercase and the dots and colons are replaced by underscores (except the first one).
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# For example, tree node :ADDR is accessed by field self.addr and .CHANNEL_1:DATA by field self.channel_1_data
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# All there firlds are TreeNode instances and therefore all TreeNode methods such as Data() or putData() can be used.
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parts = [
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{'path': ':ADDR', 'type': 'text'}, {
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'path': ':COMMENT', 'type': 'text'},
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{'path': ':CLOCK_FREQ', 'type': 'numeric', 'value': 10000},
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{'path': ':TRIG_SOURCE', 'type': 'numeric', 'value': 0},
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{'path': ':PTS', 'type': 'numeric', 'value': 1000},
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]
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for i in range(4):
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parts.extend([
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{'path': '.CHANNEL_%d' % (i), 'type': 'structure'},
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{'path': '.CHANNEL_%d:START_IDX' % (
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i), 'type': 'numeric', 'value': 0},
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{'path': '.CHANNEL_%d:END_IDX' % (
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i), 'type': 'numeric', 'value': 1000},
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{'path': '.CHANNEL_%d:DATA' % (i), 'type': 'signal', 'options': (
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'no_write_model', 'compress_on_put')},
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])
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parts.extend([
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{'path': ':INIT_ACTION', 'type': 'action',
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'valueExpr': "Action(Dispatch('CAMAC_SERVER','INIT',50,None),Method(None,'init',head))",
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'options': ('no_write_shot',)},
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{'path': ':STORE_ACTION', 'type': 'action',
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'valueExpr': "Action(Dispatch('CAMAC_SERVER','STORE',50,None),Method(None,'store',head))",
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'options': ('no_write_shot',)},
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])
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del(i)
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######################################INIT#################################################################
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# init method, called to configure the ADC device. It will read configuration from the corresponding subtree
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# and it will download configuration to the device
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def init(self):
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# Need to import some classes from MDSplus package
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# The device will be configured via a shared library (libDemoAdc in the MDSplus distribution) defining the following routines:
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# initialize(char *addr, int clockFreq, int postTriggerSamples)
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# where clockFreq can have the following values:
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# - 1 -> clock freq. = 1KHz
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# - 2 -> clock freq. = 5KHz
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# - 3 -> clock freq. = 10KHz
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# - 4 -> clock freq. = 50 KHz
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# - 5 -> clock freq. = 100KHz
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# trigger(char *addr)
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# acquire(char *addr, short *c1, short *c2 short *c3, short *c4)
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# the routine acquire returns 4 simulated sinusoidal waveform signals at the following frequencies:
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# Channel 1: 10Hz
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# Channel 2: 50 Hz
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# Channel 3: 100 Hz
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# Channel 4: 200Hz
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#
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# The addr argument passed to all device routines is not used and simulates the device identifier
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# used in real devices
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#
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# Since we need to link against a shaed library from python, we need ctypes package.
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from ctypes import CDLL, c_int, c_char_p
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try:
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deviceLibCDLL = CDLL("libDemoAdcShr.so")
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except:
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print ('Cannot link to device library')
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return 0
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# deviceLib is the ctype DLL object which allows to call library routines
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# in the following, we'll get data items in two steps (on the same line):
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# 1) instantiate a TreeNode object, passing the integer nid to the constructor
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# 2) read and evaluate (in the case the content is an expression) its content via TreeNode.data() method
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# all data access operation will be but in a try block in order to check for missing or wrong configuration data
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try:
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address = self.addr.data()
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# we expect to get a string in addr
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except:
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print ('Missing addr in device')
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return 0
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# read the clock frequency and convert to clock mode. We use a dictionary for the conversion, and assume
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clockDict = {1000: 1, 5000: 2, 10000: 3, 50000: 4, 100000: 5}
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try:
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clockFreq = self.clock_freq.data()
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clockMode = clockDict[clockFreq]
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except:
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print ('Missing or invalid clock frequency')
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return 0
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# read Post Trigger Samples and check for consistency
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try:
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pts = self.pts.data()
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except:
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print ('Missing or invalid Post Trigger Samples')
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return 0
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# all required configuation collected. Call external routine initialize passing the right parameters
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# we use ctypes functions to convert python variable to appropriate C types to be passed to the external routine
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# try:
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print(address)
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deviceLibCDLL.initialize(
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c_char_p(address.encode()), c_int(clockMode), c_int(pts))
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#try:
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# deviceLibCDLL.initialize(
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# c_char_p(address), c_int(clockMode), c_int(pts))
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#except:
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# print('Error initializing driver')
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# return 0
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# return success
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return 1
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##################################STORE################################################
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# store method, called to get samples from the ADC and to store waveforms in the tree
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def store(self):
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# import required symbols from MDSSplus and ctypes packages
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# instantiate library object
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try:
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deviceLib = CDLL("libDemoAdcShr.so")
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except:
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print ('Cannot link to device library')
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return 0
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# get addr
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try:
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addr = self.addr.data()
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# we expect to get a string in addr
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except:
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print ('Missing Addr in device')
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return 0
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# instantiate four short arrays with 65536 samples each. They will be passed to the acquire() external routine
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DataArray = c_short * 65536
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rawChan = []
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rawChan.append(DataArray())
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rawChan.append(DataArray())
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rawChan.append(DataArray())
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rawChan.append(DataArray())
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status = deviceLib.acquire(c_char_p(addr.encode()), byref(rawChan[0]), byref(
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rawChan[1]), byref(rawChan[2]), byref(rawChan[3]))
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if status == -1:
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print ('Acquisition Failed')
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return 0
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# at this point the raw signals are contained in rawChan1-4. We must now:
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# 1) reduce the dimension of the stored array using the start idx and end idx parameters for each channel, which define
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# the number of samples around the trigger which need to be stored in the pulse file (for this purpose the value of
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# post trigger samples is also required)
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# 2) build the appropriate timing information
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# 3) Put all together in a Signal object
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# 4) store the Signal object in the tree
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# read PostTriggerSamples
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try:
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pts = self.pts.data()
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except:
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print ('Missing or invalid Post Trigger Samples')
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return 0
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# for each channel we read start idx and end idx
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startIdx = []
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endIdx = []
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try:
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for chan in range(0, 4):
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currStartIdx = self.__getattr__(
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'channel_%d_start_idx' % (chan)).data()
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currEndIdx = self.__getattr__(
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'channel_%d_end_idx' % (chan)).data()
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startIdx.append(currStartIdx)
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endIdx.append(currEndIdx)
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except:
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print ('Cannot read start idx or end idx')
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return 0
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# 1)Build reduced arrays based on start idx and end idx for each channel
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# recall that a transient recorder stores acquired data in a circular buffer and stops after acquiring
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# PTS samples after the trigger. This means that the sample corresponding to the trigger is at offset PTS samples
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# before the end of the acquired sample array.
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# the total number of samples returned by routine acquire()
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totSamples = 65536
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# we read the time associated with the trigger. It is specified in the TRIG_SOURCE field of the device tree structure.
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# it will be required in order to associate the correct time with each acquired sample
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try:
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trigTime = self.trig_source.data()
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except:
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print ('Missing or invalid Post Trigger Samples')
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return 0
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# we need clock frequency as well
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try:
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clockFreq = self.clock_freq.data()
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clockPeriod = 1./clockFreq
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except:
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print ('Missing or invalid clock frequency')
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return 0
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# the following steps are performed for each acquired channel
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for chan in range(0, 4):
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# first index of the part of interest of the sample array
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actStartIdx = totSamples - pts + startIdx[chan]
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# last index of the part of interest of the sample array
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actEndIdx = totSamples - pts + endIdx[chan]
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# make sure we do not exceed original array limits
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if actStartIdx < 0:
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actStartIdx = 0
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if actEndIdx > totSamples:
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actEndIdx = totSamples - 1
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# build reshaped array
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reducedRawChan = rawChan[chan][actStartIdx:actEndIdx]
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# 2)Build timing information. For this purpose we use a MDSplus "Dimension" object which contains two fields:
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# "Window" and "Axis". Window object defines the start and end index of the associated data array and the time which is
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# associated with the sample at index 0. Several possible combination of start and end indexes are possible (the can also be
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# negative numbers). We adopt here the following convention: consider index 0 as the index of the sample corresponding
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# to the trigger, and therefore associated with the trigger time. From the way we have built the reduced raw sample array,
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# it turns out that the start idx and end idx defined
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# in the Window object are the same of the start and end indexes defined in the device configuration.
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#
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# The "Range" object describes a (possibly multispeed or busrt) clock. Its fields specify the clock period, the start and end time
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# for that clock frequency. In our case we need to describe a continuous single speed clock, so there is no need to
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# specify start and end times(it is a continuous, single speed clock).
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#
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# build the Dimension object in a single call
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dim = Dimension(Window(startIdx[chan], endIdx[chan], trigTime), Range(
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None, None, clockPeriod))
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# 3) Put all togenther in a "Signal" object. MDSplus Signal objects define three fields: samples, raw samples, dimension
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# raw samples are contained in reducedRawChan. The computation required to convert the raw 16 bit sample into a +-10V
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# value is: sample = 10.*rawSample/32768. We may compute a new float array containing such data and store it together
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# with the raw sample (in the case we would like to reain also raw data. There is however a better way to do it
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# by storing only the required information, i.e. the raw(16 bit) samples and the definition of the expression which
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# converts raw data into actual voltage levels. Therefore, the first field of the Signal object will contain only the
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# definition of an expression, which refers to the raw samples (the second field) of the same Signal object.
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# The MDSplus syntax for this conversion is: 10.*$VALUE/32768.
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# We shall use Data method compile() to build the MDSplus internal representation of this expression, and the stick it
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# as the first field of the Signal object
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convExpr = Data.compile("10.* $VALUE/32768.")
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# use MDSplus Int16Array object to vest the short array reducedRawChan into the appropriate MDSplus type
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rawMdsData = Int16Array(reducedRawChan)
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# every MDSplus data type can have units associated with it
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rawMdsData.setUnits("Count")
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convExpr.setUnits("Volt")
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# build the signal object
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signal = Signal(convExpr, rawMdsData, dim)
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# write the signal in the tree
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try:
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self.__getattr__('channel_%d_data' % (chan)).putData(signal)
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except:
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print ('Cannot write Signal in the tree')
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return 0
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# endfor chan in range(0,4):
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# return success (odd numbers in MDSplus)
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return 1
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