wirecell.img.main Namespace Reference

Functions
def	cli (ctx)
def	paraview_blobs (ctx, cluster_tap_file, paraview_file)
def	paraview_activity (ctx, cluster_tap_file, paraview_file)
def	bee_blobs (output, geom, rse, sampling, density, cluster_tap_files)
def	activity (output, slices, slice_line, cluster_tap_file)
def	blob_activity_mask (output, slices, slice_line, found, cluster_tap_file)
def	wire_slice_activity (output, sliceid, cluster_tap_file)
def	main ()

Detailed Description

The wirecell-img main

Function Documentation

def wirecell.img.main.activity	(		output,
			slices,
			slice_line,
			cluster_tap_file
	)

Plot activity

Definition at line 144 of file main.py.

def activity(output, slices, slice_line, cluster_tap_file):
    '''
    Plot activity
    '''
    from matplotlib.colors import LogNorm
    from . import tap, clusters, plots
    gr = tap.load(cluster_tap_file)
    cm = clusters.ClusterMap(gr)
    ahist = plots.activity(cm)
    arr = ahist.arr
    extent = list()
    if slices:
        arr = arr[:,slices[0]:slices[1]]
        extent = [slices[0], slices[1]]
    else:
        extent = [0, arr.shape[1]]
    extent += [ahist.rangey[1], ahist.rangey[0]]

    fig,ax = plt.subplots(nrows=1, ncols=1)
    fig.set_size_inches(8.5,11.0)

    cmap = plt.get_cmap('gist_rainbow')
    im = ax.imshow(arr, cmap=cmap, interpolation='none', norm=LogNorm(), extent=extent)
    if slice_line > 0:
        ax.plot([slice_line, slice_line], [ahist.rangey[0], ahist.rangey[1]],
                linewidth=0.1, color='black')

    ## protodune only....
    boundary = 0
    for chunk in [400, 400, 400, 400, 480, 480]:
        boundary += chunk
        y = boundary + ahist.rangey[0]
        ax.plot(extent[:2], [y,y], color='gray', linewidth=0.1);

    from matplotlib.ticker import  AutoMinorLocator
    minorLocator = AutoMinorLocator()
    ax.yaxis.set_minor_locator(minorLocator)
    ax.tick_params(which="both", width=1)
    ax.tick_params(which="major", length=7)
    ax.tick_params(which="minor", length=3)

    plt.colorbar(im, ax=ax)
    ax.set_title(cluster_tap_file)
    ax.set_xlabel("slice ID")
    ax.set_ylabel("channel IDs")
    fig.savefig(output)


@cli.command("blob-activity-mask")
@click.option('-o', '--output', help="The output plot file name")
@click.option('-s', '--slices', nargs=2, type=int, 
              help="The output plot file name")
@click.option('-S', '--slice-line', type=int, default=-1,
              help="Draw a line down a slice")
@click.option('--found/--missed', default=True,
              help="Mask what blobs found or missed")
@click.argument("cluster-tap-file")

def wirecell.img.main.bee_blobs	(		output,
			geom,
			rse,
			sampling,
			density,
			cluster_tap_files
	)

Make one Bee JSON file from the blobs in a set of 'cluster tap'
JSON files which are presumed to originate from one trigger.

Definition at line 95 of file main.py.

def bee_blobs(output, geom, rse, sampling, density, cluster_tap_files):
    '''
    Make one Bee JSON file from the blobs in a set of 'cluster tap'
    JSON files which are presumed to originate from one trigger.
    '''
    from . import tap, converter

    dat = dict(runNo=rse[0], subRunNo=rse[1], eventNo=rse[2], geom=geom, type="wire-cell",
               x=list(), y=list(), z=list(), q=list()) # , cluster_id=list()


    def fclean(arr):
        return [round(a, 3) for a in arr]
        
    # given by user in units of 1/cc.  Convert to system of units 1/L^3.
    density *= 1.0/(units.cm**3)
    sampling_func = dict(
        center = converter.blob_center,
        uniform = lambda b : converter.blob_uniform_sample(b, density),
    )[sampling];

    for ctf in cluster_tap_files:
        gr = tap.load(ctf)
        print ("got %d" % gr.number_of_nodes())
        if 0 == gr.number_of_nodes():
            print("skipping empty graph %s" % ctf)
            continue
        arr = converter.blobpoints(gr, sampling_func)
        print ("%s: %d points" % (ctf, arr.shape[0]))
        dat['x'] += fclean(arr[:,0]/units.cm)
        dat['y'] += fclean(arr[:,1]/units.cm)
        dat['z'] += fclean(arr[:,2]/units.cm)
        dat['q'] += fclean(arr[:,3])

    import json
    # monkey patch
    from json import encoder
    encoder.FLOAT_REPR = lambda o: format(o, '.3f')
    json.dump(dat, open(output,'w', encoding="utf8"))



@cli.command("activity")
@click.option('-o', '--output', help="The output plot file name")
@click.option('-s', '--slices', nargs=2, type=int, 
              help="Range of slice IDs")
@click.option('-S', '--slice-line', type=int, default=-1,
              help="Draw a line down a slice")
@click.argument("cluster-tap-file")

def wirecell.img.main.blob_activity_mask	(		output,
			slices,
			slice_line,
			found,
			cluster_tap_file
	)

Plot blobs as maskes on channel activity.

Definition at line 201 of file main.py.

def blob_activity_mask(output, slices, slice_line, found, cluster_tap_file):
    '''
    Plot blobs as maskes on channel activity.
    '''
    from . import tap, clusters, plots
    gr = tap.load(cluster_tap_file)
    cm = clusters.ClusterMap(gr)
    ahist = plots.activity(cm)
    bhist = ahist.like()
    plots.blobs(cm, bhist)
    if found:
        sel = lambda a: a>= 1
        title="found mask"
    else:
        sel = lambda a: a < 1
        title="missed mask"
    extent = list()
    if slices:
        a = ahist.arr[:,slices[0]:slices[1]]
        b = bhist.arr[:,slices[0]:slices[1]]
        extent = [slices[0], slices[1]]
    else:
        a = ahist.arr
        b = bhist.arr
        extent = [0, a.shape[1]]
    extent += [ahist.rangey[1], ahist.rangey[0]]

    fig,ax = plots.mask_blobs(a, b, sel, extent)
    if slice_line > 0:
        ax.plot([slice_line, slice_line], [ahist.rangey[0], ahist.rangey[1]],
                linewidth=0.1, color='black')
    ax.set_title("%s %s" % (title, cluster_tap_file))
    ax.set_xlabel("slice ID")
    ax.set_ylabel("channel IDs")
    fig.savefig(output)


@cli.command("wire-slice-activity")
@click.option('-o', '--output', help="The output plot file name")
@click.option('-s', '--sliceid', type=int, help="The slice ID to plot")
@click.argument("cluster-tap-file")

def wirecell.img.main.cli

(

ctx

)

Wire Cell Toolkit Imaging Commands

Definition at line 13 of file main.py.

def cli(ctx):
    '''
    Wire Cell Toolkit Imaging Commands
    '''

@cli.command("paraview-blobs")
@click.argument("cluster-tap-file")
@click.argument("paraview-file")
@click.pass_context

def wirecell.img.main.main

(

void

)

Definition at line 253 of file main.py.

def main():
    cli(obj=dict())

def wirecell.img.main.paraview_activity	(		ctx,
			cluster_tap_file,
			paraview_file
	)

Convert a JsonClusterTap JSON file to a ParaView .vti file of activity

Definition at line 42 of file main.py.

def paraview_activity(ctx, cluster_tap_file, paraview_file):
    '''
    Convert a JsonClusterTap JSON file to a ParaView .vti file of activity
    '''
    from . import converter, tap
    from tvtk.api import write_data
    
    gr = tap.load(cluster_tap_file)
    if 0 == gr.number_of_nodes():
        click.echo("no verticies in %s" % cluster_tap_file)
        return
    alldat = converter.clusters2views(gr)
    for wpid,dat in alldat.items():
        fname = paraview_file%wpid
        write_data(dat, fname)
        click.echo(fname)
    return


@cli.command("paraview-depos")
@click.argument("depo-npz-file")
@click.argument("paraview-file")
@click.pass_context

def wirecell.img.main.paraview_blobs	(		ctx,
			depo_npz_file,
			paraview_file
	)

Convert a JsonClusterTap JSON file to a ParaView .vtu file of blobs

Convert an NPZ file to a ParaView .vtu file of depos

Definition at line 22 of file main.py.

def paraview_blobs(ctx, cluster_tap_file, paraview_file):
    '''
    Convert a JsonClusterTap JSON file to a ParaView .vtu file of blobs
    '''
    from . import converter, tap
    from tvtk.api import write_data
    
    gr = tap.load(cluster_tap_file)
    if 0 == gr.number_of_nodes():
        click.echo("no verticies in %s" % cluster_tap_file)
        return
    dat = converter.clusters2blobs(gr)
    write_data(dat, paraview_file)
    click.echo(paraview_file)
    return

@cli.command("paraview-activity")
@click.argument("cluster-tap-file")
@click.argument("paraview-file")
@click.pass_context

def wirecell.img.main.wire_slice_activity	(		output,
			sliceid,
			cluster_tap_file
	)

Plot the activity in one slice as wires and blobs

Definition at line 242 of file main.py.

def wire_slice_activity(output, sliceid, cluster_tap_file):
    '''
    Plot the activity in one slice as wires and blobs
    '''
    from . import tap, clusters, plots
    gr = tap.load(cluster_tap_file)
    cm = clusters.ClusterMap(gr)
    fig, axes = plots.wire_blob_slice(cm, sliceid)
    fig.savefig(output)