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#!/bin/csh
setenv DAQREL /reg/g/pcds/dist/pds/27.100.62/build  (the latest release goes here)
setenv PYTHONPATH ${PYTHONPATH}:${DAQREL}/pdsapp/lib/x86_64-linux:${DAQREL}/ami/lib/x86_64-linux
setenv LD_LIBRARY_PATH ${LD_LIBRARY_PATH}:${DAQREL}/pdsdata/lib/x86_64-linux:${DAQREL}/pdsalg/lib/x86_64-linux:${DAQREL}/pdsapp/lib/x86_64-linux:${DAQREL}/ami/lib/x86_64-linux:${DAQREL}/build/pds/lib/x86_64-linux:${DAQREL}/build/qt/lib/x86_64-linux

 --- pydaq module ---

class pydaq.Control(host, platform=0)

    Arguments:
        'host'     : host name or IP address (dotted-string notation or integer)
        'platform' : DAQ platform number (subdivision of readout hardware)

    Function:
        Initializes the interface for controlling the data acquisition system remotely.
        Creates a connection with the local control and queries the configuration
        database and current key in use.

Members:

    Control.dbpath()
        Returns path to configuration database

    Control.dbkey()
        Returns current configuration key (integer) in use

    Control.dbalias()
        Returns current configuration alias (string) in use
      
    Control.partition()
        Returns a list of dictionary objects describing all nodes in the DAQ readout.

    Control.configure(record=<Bool>,
              key=<Integer>,
              events=<Integer> or l1t_events=<Integer> or l3t_events=<Integer> or duration=[seconds,nanoseconds],
              controls=[(name,value)],
              monitors=[(name,lo_range,hi_range)])
        Configures control to use database key (default to current key) either:
          (1) collecting a fixed number of events on each cycle (when events=<Integer>
              or l1t_events=<Integer> is specified) or
          (2) collecting events until a fixed number of events have been accepted by
              the level3 filter (when l3t_events=<Integer>) or
          (2) collecting events for a fixed duration (when duration=[seconds,nanoseconds]
              is specified).  
        The list of variables controlled (optional) in the scan and
        the list of variables to be monitored (optional) during acquisition
        are specified.
        The option to record can also be set.  If it is omitted, then the value from
        the local control is used.

    Control.begin(events=<Integer> or duration=[seconds,nanoseconds],
   l1t_events=<Integer> or l3t_events=<Integer> or duration=[seconds,nanoseconds],
              controls=[(name,value)],)
              monitors=[(name,lo_range,hi_range)])
        Begins acquisition for the specified settings of control variables (if specified).
        Actual control of these variables is the responsibility of the remote application.  
        Monitor variables (optional) are enforced during acquisition.  Omitted values
        default to those specified most recently (or in the 'configure' method).

    Control.end()
        Waits for the end of acquisition cycle signalled from the local host control.

    Control.stop()
        Signals the local host control to terminate the current acquisition cycle.

    Control.eventnum()
        Returns the number of events acquired in the current acquisition run.

    Control.experiment()
        Returns experiment number of run, if recorded.  
        Only valid after acquisition is complete.

    Control.runnumber()
        Returns run number, if recorded.  
        Only valid after acquisition is complete.

 -- pyami module --

connect(Server_Group, CDS_interface, FEZ_interface)
    Connects the module to the group of monitoring servers.
    The input parameters are specific to the hutch.
    If the last two parameters are omitted, they will be learned from the
    available network interfaces on the host.
    This must be called before any of the following class methods.

class pyami.Entry(name,'Scalar')
    Monitors data from the scalar variable 'name'.  A dictionary of
    ('Scalar', n_events, mean, rms) is accumulated.
connect(PROXY_ip_address, CDS_interface)
    Connects the module to the group of monitoring servers known by the PROXY.

class pyami.Entry(name) or
class pyami.Entry(name,'TH1F',nbins,xlo,xhiScalar')
    Monitors data from the scalar variable 'name'.  A dictionary of
    (type='TH1FScalar', uflow, oflow, data=( n_bin0, n_bin1, ...)) is accumulated.

class pyami.time=<last event time in seconds since the Epoch>, 
     entries=<number of events accumulated>, mean=<value>, rms=<value>) is accumulated.

class pyami.Entry(name,'ScanTH1F',xvariablenbins,xlo,nbinsxhi)
    Monitors   Monitors data from the scalar variable 'name'.   A dictionary of
       (type='ScanTH1F', nbins, current, xbins=( x0, x1, ...), yentries=( n0, n1, ...),
     ysum=( y0, y1, ...), y2sum=( y2_0, y2_1time=<last event time in seconds since the Epoch>,
     uflow=<number of underflows>, oflow=<number of overflows>, data=( n_bin0, n_bin1, ...)) is accumulated; where.

class pyami.Entry(name,'Scan',xvariable,nbins)
    'current'Monitors isdata the binfrom with the mostscalar recentvariable entry, 'xbinsname'. is aA listdictionary of unique x-variable values,
    (type='yentriesScan' is a list of, time=<last event time in seconds since the numberEpoch>,
  of summed entries with that x-variable value,
    'sum' is a list of the sum of y-variables values in each bin, 'y2sum' is a list of the sum
    of y-variable values squared in each bin.  The lists are of length 'nbins' with only the most
    recent entries retained.

class pyami.Entry(det_identifier) or
class pyami.Entry(det_identifier,channel)
    Monitors the data from the detector associated with 'det_identifier' and
    'channel'.  A dictionary of data averaged over events is accumulated.  The
    dimensions and binning of the data are determined from the detector.
    The dictionary format is
    (type='Waveform', entries=events, xlow, xhigh, data=(y0, y1, ...)) or
    (type='Image', entries=events, offset=dark_level, ppxbin, ppybin,
        data=((row0col0,row0col1,...),(row1col0,row1col1,...))) or
    (type='ImageArray', entries=events, offset=dark_level, ppxbin, ppybin,
        data=( ((row0col0,row0col1,...),(row1col0,row1col1,...))_0,
               ((row0col0,row0col1,...),(row1col0,row1col1,...))_1,
               ... ))

    Each of the above methods also takes an optional final string argument that
    defines an event filter.  The string must take the form:
    
        _lo_value_<_scalar_name_<_hi_value_  or
        (_expr1_)&(_expr2_)                  or
        (_expr1_)|(_expr2_)

    where _expr1_ and _expr2_ also take one of the forms.

Members:

    Entry.get()
        Returns the data accumulated since the object was created.
    Entry.clear nbins=<value>, current=<index of most recent entry>, xbins=( x0, x1, ...), yentries=( n0, n1, ...),
        ysum=( y0, y1, ...), y2sum=( y2_0, y2_1, ...)) is accumulated; where
    'current' is the bin with the most recent entry, 'xbins' is a list of unique x-variable values,
    'yentries' is a list of the number of summed entries with that x-variable value,
    'sum' is a list of the sum of y-variables values in each bin, 'y2sum' is a list of the sum
    of y-variable values squared in each bin.  The lists are of length 'nbins' with only the most
    recent entries retained.

class pyami.Entry(det_identifier) or
class pyami.Entry(det_identifier,channel)
    Monitors the data from the detector associated with 'det_identifier' and
    'channel'.  A dictionary of data averaged over events is accumulated.  The
    dimensions and binning of the data are determined from the detector.
    The dictionary format is
    (type='Waveform', time=<last event time in seconds since the Epoch>
        entries=events, xlow, xhigh, data=(y0, y1, ...)) or
    (type='Image', time=<last event time in seconds since the Epoch>,
        entries=events, offset=dark_level, ppxbin, ppybin,
        data=((row0col0,row0col1,...),(row1col0,row1col1,...))) or
    (type='ImageArray', time=<last event time in seconds since the Epoch>,
        entries=events, offset=dark_level, ppxbin, ppybin,
        data=( ((row0col0,row0col1,...),(row1col0,row1col1,...))_0,
               ((row0col0,row0col1,...),(row1col0,row1col1,...))_1,
               ... ))

    Each of the above methods also takes an optional final string argument that
    defines an event filter.  The string must take the form:
    
        _lo_value_<_scalar_name_<_hi_value_  or
        (_expr1_)&(_expr2_)                  or
        (_expr1_)|(_expr2_)

    where _expr1_ and _expr2_ also take one of the forms.

Members:

    Entry.get()
        Returns the data accumulated since the object was created.
    Entry.clear()
        Resets the data accumulation.
    Entry.pstart()
        Start continuous mode accumulation ("push" mode).
    Entry.pstop()
        Stop continuous mode accumulation.
    Entry.pget()
        Return continuous mode data.  

"Push" mode description:

    The event data is "pushed" to the python module's application by the monitoring servers once the Entry.pstart() command is given.  The Entry.pget() call simply waits for the data to arrive, if necessary, and returns it to the caller.  The Entry.pstop() command instructs the servers to cease sending the data.  Note that this mode can easily consume considerable network bandwidth on the local machine.


class pyami.EntryList([list of arguments that satisfy pyami.Entry above])
     Defines a list of objects to access using the same resources as one pyami.Entry object.  The list of objects is accessed synchronously, so each object's accumulation of events will be the same.

Members:

    EntryList.get()
        Returns a list of the data accumulated since the object was created.
    EntryList.clear()
        Resets the data accumulation.
    EntryList.pstart()
        Start continuous mode accumulation ("push" mode).
    EntryList.pstop()
        Stop continuous mode accumulation.
    EntryList.pget()
        ResetsReturn a list of the continuous mode data.  accumulation.