Metadata-Version: 2.1
Name: bdata
Version: 1.3.10
Summary: BNMR/BNQR MUD file reader and asymmetry calculator
Home-page: https://github.com/dfujim/bdata
Author: Derek Fujimoto
Author-email: fujimoto@phas.ubc.ca
License: UNKNOWN
Description: # bdata
        Beta-data package. The bdata object is largely a data container, designed to read out [MUD](http://musr.ca/mud/mud_fmt.html) data files and to provide user-friendly access [BNMR/BNQR data](http://musr.ca/mud/runSel.html). 
        
        ## Installation 
        
        * Install using pip: `pip install bdata`
        * Export environment variables for finding data files (add to `.bashrc` or similar)
            * `export BNMR_ARCHIVE=/path/bnmr/`
            * `export BNQR_ARCHIVE=/path/bnqr/`
        
        ## Object Map
        
        **Constructor**: 
        
        `bdata(run_number,year=0,filename='')`
        
        Examples:
            
        ```python
        bd = bdata(40001)                     # read run 40001 from the current year. 
        bd = bdata(40001,year=2017)           # read run 40001 from year 2017.
        bd = bdata(0,filename='filename.msr') # read file from local memory, run number unused 
        ```        
        
        **Functions**: 
        
        | Signature | Description |
        | -------- | -------- |
        | `asym(option="",omit="",rebin=1,hist_select='')`     | Calculate asymmetry. See below for docstring.     |
        | `beam_kev()`     | Get beam implantation energy in keV     |
        | `get_pulse_s()`     | Get beam pulse duration in s     |
        
        
        ## Misc Notes
        
        The bdict objects allow for the calling of dictionary keys like an object attribute. For example, bd.ppg.beam_on or bd.ppg['beam_on'] have the exact same output. Note that reserved characters such as '+' cannot be used in this manner. 
                    
        Set the location of the data archive via environment variables "BNMR_ARCHIVE" and "BNQR_ARCHIVE". This would be something like "/data1/bnmr/dlog/" on linbnmr2 or "~/triumf/data/bnmr/" on muesli or lincmms.
        
        The various object containers returned have customized defined "magic" functions for common comparison and mathematical operators. So one can do `bd.ppg.beam_on*5` and get 5 times the beam on time, stored in the mean property of that object. 
        
        Note that the object representation has been nicely formatted as well.
        
        ## bdata.asym() docstring
        
        ```text
        usage: asym(option="",omit="",rebin=1,hist_select='')
        
        Inputs:
            options:        see below for details
            omit:           1f bins to omit if space seperated string in options 
                                is not feasible. See options description below.
            rebin:          SLR only. Weighted average over 'rebin' bins to 
                                reduce array length by a factor of rebin. 
            hist_select:    string to specify which histograms get combined into 
                                making the asymmetry calculation. Deliminate 
                                with [,] or [;]. Histogram names cannot 
                                therefore contain either of these characters.
        
        Asymmetry calculation outline (with default detectors) ---------------
        
            Split helicity      (NMR): (F-B)/(F+B) for each
            Combined helicity   (NMR): (r-1)/(r+1)
                where r = sqrt([(B+)(F-)]/[(F+)(B-)])
        
            Split helicity      (NQR): (R-L)/(R+L) for each
            Combined helicity   (NQR): (r-1)/(r+1)
                where r = sqrt([(L+)(R-)]/[(R+)(L-)])
        
            Alpha diffusion     (NQR) sum(AL0)/sum(L+R)
            Alpha tagged        (NQR) same as NQR, but using the tagged counters
        
        Histogram Selection ---------------------------------------------------
        
            If we wished to do a simple asymmetry calculation in the form of 
        
                                    (F-B)/(F+B)
        
            for each helicity, then 
                                       |--|  |--|   paired counter location
                        hist_select = 'F+,F-,B+,B-'
                                        |-----|       paired helicities
                                           |-----|
        
            for alpha diffusion calculations append the two alpha counters
        
                hist_select = 'R+,R-,L+,L-,A+,A-
        
            for alpha tagged calculations do the following
        
                hist_select = 'R+,R-,L+,L-,TR+,TR-,TL+,TL-,nTR+,nTR-,nTL+,nTL-'
        
                where TR is the right counter tagged (coincident) with alphas, 
                      TL is the left  counter tagged with alphas, 
                     nTR is the right counter tagged with !alphas (absence of), 
                     nLR is the right counter tagged with !alphas, 
        
        
        Status of Data Corrections --------------------------------------------
            SLR/2H: 
                Removes prebeam bins. 
                Subtract mean of prebeam bins from raw counts 
                    (does not treat error propagation from this. Errors are 
                    still treated as Poisson, despite not being integers) 
        
                Rebinning: 
                    returned time is average time over rebin range
                    returned asym is weighted mean
        
            1F: 
                Allows manual removal of unwanted bins. 
        
                Scan Combination:
                    Multiscans are considered as a single scan with long 
                    integration time. Histogram bins are summed according to 
                    their frequency bin, errors are Poisson.
        
            1N:
                Same as 1F. Uses the neutral beam monitor values to calculate 
                asymetries in the same manner as the NMR calculation. 
        
            2E: 
                Prebeam bin removal. 
                Postbeam bin removal. Assumes beamoff time is 0. 
                Splits saved 1D histograms into 2D.
        
                Asymmetry calculations: 
                    raw: calculated through differences method (as described in 
                        the asymmetry calculation outline)
                    dif: let 0 be the index of the centermost scan in time. dif 
                        asymmetries are then calculated via raw[i+1]-raw[i-1], 
                        where "raw" is as calculated in the above line, for each 
                        of the three types: +,-,combined 
                    sl: take a weighted least squares fit to the two bins prior 
                        and the two bins after the center bin (in time). For 
                        each find the value of the asymmetry at the center time 
                        position. Take the difference: post-prior
        
        Return value depends on option provided:
        
            SLR DESCRIPTIONS --------------------------------------------------
        
            "":     dictionary of 2D numpy arrays keyed by 
                        {"p","n","c","time_s"} for each helicity and combination 
                        (val,err). Default return state for unrecognized options
            "h":    dictionary 2D numpy arrays keyed by {"p","n","time_s"} for 
                        each helicity (val,err).
            "p":    2D np array of up helicity state [time_s,val,err].
            "n":    2D np array of down helicity state [time_s,val,err].
            "c":    2D np array of combined asymmetry [time_s,val,err].
            "ad":   2D np array of alpha diffusion ratio [time_s,val,err].
            "at":   dictionary of alpha tagged asymmetries key:[val,err]. 
                    Keys:
        
                        'time_s'               : 1D array of times in seconds   
                        'p_wiA','n_wiA','c_wiA': coincident with alpha
                        'p_noA','n_noA','c_noA': coincident with no alpha
                        'p_noT','n_noT','c_noT': untagged
        
                where p,n,c refer to pos helicity, neg helicity, combined 
                helicity respectively. Only in 2h mode. 
        
        
            1F DESCRIPTIONS ---------------------------------------------------
        
                all options can include a space deliminated list of bins or 
                ranges of bins which will be omitted. ex: "raw 1 2 5-20 3"
        
            "":     dictionary of 2D numpy arrays keyed by {p,n,c,freq} for each 
                        helicity and combination [val,err]. Default return state 
                        for unrecognized options.
            "r":    Dictionary of 2D numpy arrays keyed by {p,n} for each 
                        helicity (val,err), but listed by bin, not combined by 
                        frequency. 
            "h":    get unshifted +/- helicity scan-combined asymmetries as a 
                        dictionary {'p':(val,err),'n':(val,err),'freq'}
            "p":    get pos helicity states as tuple, combined by frequency 
                        (freq,val,err)
            "n":    similar to p but for negative helicity states
            "c":    get combined helicity states as tuple (freq,val,err)
        
        
            2E DESCRIPTIONS ---------------------------------------------------
        
                Takes no options. Returns a dictionary with the keys: 
        
            'dif_p':    [val,err][frequency] of pos. helicity asymmetry 
            'dif_n':    [ve][f] of negative helicity asymmetry
            'dif_c':    [ve][f] of combined helicity asymmetry
        
            'raw_p':    [ve][f][time] raw asymmetries of each time bin. Pos hel. 
            'raw_n':    [ve][f][t] negative helicity.
            'raw_c':    [ve][f][t] combined helicity
        
            'freq':     [f] frequency values
            'time':     [t] time bin values
        
            'sl_p':     [ve][f] pos. hel. of asymmetry calcuated through slopes 
                            of pre and post middle time bin. Slope method only 
                            for >= 5 time bins, corresponds to >= 3 RF on delays
            'sl_n':     [ve][f] negative helicity.
            'sl_c':     [ve][f] combined helicity.
        ```        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
