diff --git a/orcasong_plag/core.py b/orcasong_plag/core.py
index 30ba800e20dfa1474120a667101ce20473d66805..355a438b51c9c1543afb3045bfe3247893631df4 100644
--- a/orcasong_plag/core.py
+++ b/orcasong_plag/core.py
@@ -2,7 +2,7 @@ import km3pipe as kp
import km3modules as km
import os
-from orcasong_plag.modules import TimePreproc, ImageMaker, McInfoMaker, BinningPlotter
+from orcasong_plag.modules import TimePreproc, ImageMaker, McInfoMaker, BinningPlotter, plot_hists
from orcasong_plag.mc_info_types import get_mc_info_extr
@@ -59,8 +59,8 @@ class FileBinner:
self.mc_info_extr = mc_info_extr
self.bin_plot_freq = 20
- self.n_statusbar = 200
- self.n_memory_observer = 400
+ self.n_statusbar = 1000
+ self.n_memory_observer = 1000
self.do_time_preproc = True
# self.data_cuts = None
@@ -75,8 +75,8 @@ class FileBinner:
Parameters
----------
- infile : str or List
- Path to the input file(s).
+ infile : str
+ Path to the input file.
outfile : str
Path to the output file.
@@ -84,34 +84,50 @@ class FileBinner:
name, shape = self.get_names_and_shape()
print("Generating {} images with shape {}".format(name, shape))
- pipe = kp.Pipeline()
+ plot_hists = self.bin_plot_freq is not None
- if self.n_statusbar is not None:
- pipe.attach(km.common.StatusBar, every=self.n_statusbar)
- if self.n_memory_observer is not None:
- pipe.attach(km.common.MemoryObserver, every=400)
+ pipe = self.build_pipe(infile, outfile, plot_hists=plot_hists)
+ pipe.drain()
- if not isinstance(infile, list):
- infile = [infile]
+ def run_multi(self, infiles, outfolder):
+ """
+ Bin multiple files into their own output files each.
- pipe.attach(kp.io.hdf5.HDF5Pump, filenames=infile)
+ Will also generate a summary binning plot for all of the files.
- self.attach_binning_modules(pipe, outfile=outfile)
+ Parameters
+ ----------
+ infiles : List
+ The path to infiles as str.
+ outfolder : str
+ The output folder to place them in.
- pipe.attach(kp.io.HDF5Sink,
- filename=outfile,
- complib=self.complib,
- complevel=self.complevel,
- chunksize=self.chunksize,
- flush_frequency=self.flush_frequency)
+ """
+ hists = None
+ for infile in infiles:
+ outfile_name = os.path.splitext(os.path.basename(infile))[0] + "_hist.h5"
+ outfile = outfolder + outfile_name
+
+ pipe = self.build_pipe(infile, outfile,
+ plot_hists=False, hists_start=hists)
+ smry = pipe.drain()
+ hists = smry["BinningPlotter"]
+ plot_hists(hists, pdf_path=outfolder + "binning_summary.pdf")
+
+ def build_pipe(self, infile, outfile, plot_hists=True, hists_start=None):
+ """
+ Build the pipe to generate images and mc_info for a file.
+ """
- pipe.drain()
+ pipe = kp.Pipeline()
- def attach_binning_modules(self, pipe, outfile):
- """
- Attach modules to a km3pipe which transform a blob to images and mc_info.
+ if self.n_statusbar is not None:
+ pipe.attach(km.common.StatusBar, every=self.n_statusbar)
+ if self.n_memory_observer is not None:
+ pipe.attach(km.common.MemoryObserver, every=self.n_memory_observer)
+
+ pipe.attach(kp.io.hdf5.HDF5Pump, filename=infile)
- """
pipe.attach(km.common.Keep, keys=['EventInfo', 'Header', 'RawHeader',
'McTracks', 'Hits', 'McHits'])
if self.do_time_preproc:
@@ -122,10 +138,14 @@ class FileBinner:
# pipe.attach(EventSkipper, data_cuts=self.data_cuts)
if self.bin_plot_freq is not None:
- pdf_name = os.path.splitext(outfile)[0] + "_hists.pdf"
+ if plot_hists:
+ pdf_name = os.path.splitext(outfile)[0] + "_hists.pdf"
+ else:
+ pdf_name = None
pipe.attach(BinningPlotter,
bin_plot_freq=self.bin_plot_freq,
bin_edges_list=self.bin_edges_list,
+ hists_start=hists_start,
pdf_path=pdf_name)
pipe.attach(ImageMaker,
@@ -144,6 +164,14 @@ class FileBinner:
pipe.attach(km.common.Keep, keys=['histogram', 'mc_info'])
+ pipe.attach(kp.io.HDF5Sink,
+ filename=outfile,
+ complib=self.complib,
+ complevel=self.complevel,
+ chunksize=self.chunksize,
+ flush_frequency=self.flush_frequency)
+ return pipe
+
def get_names_and_shape(self):
"""
Get names and shape of the resulting x data, e.g. (pos_z, time), (18, 50).
diff --git a/orcasong_plag/modules.py b/orcasong_plag/modules.py
index 139bd4289188e46e87051b572ccecc815e24069b..9ddcb6558b6b8cf6d1e4002ec31256187040474b 100644
--- a/orcasong_plag/modules.py
+++ b/orcasong_plag/modules.py
@@ -137,7 +137,7 @@ class BinningPlotter(kp.Module):
bin_edges_list : List
List with the names of the fields to bin, and the respective bin edges,
including the left- and right-most bin edge.
- pdf_path : str
+ pdf_path : str, optional
Where to save the hists to. This pdf will contain all the field names
on their own page each.
bin_plot_freq : int
@@ -150,22 +150,35 @@ class BinningPlotter(kp.Module):
plot_bin_edges : bool
If true, will plot the bin edges as horizontal lines. Is never used
for the time binning (field name "time").
+ hists_start : dict, optional
+ Starting values for the statistics.
"""
def configure(self):
self.bin_edges_list = self.require('bin_edges_list')
- self.pdf_path = self.require('pdf_path')
+ self.pdf_path = self.get('pdf_path', default=None)
self.bin_plot_freq = self.get("bin_plot_freq", default=20)
self.res_increase = self.get('res_increase', default=5)
self.plot_bin_edges = self.get('plot_bin_edges', default=True)
+ self.hists_start = self.get('hists_start', default=None)
- self.hists = {}
- for bin_name, bin_edges in self._yield_spaced_bin_edges():
- self.hists[bin_name] = {
- "hist": np.zeros(len(bin_edges) - 1),
- "out_pos": 0,
- "out_neg": 0,
- }
+ if self.hists_start is None:
+ self.hists = {}
+ for bin_name, org_bin_edges in self.bin_edges_list:
+ if bin_name == "time":
+ bin_edges = org_bin_edges
+ else:
+ bin_edges = self._space_bin_edges(org_bin_edges)
+
+ self.hists[bin_name] = {
+ "hist": np.zeros(len(bin_edges) - 1),
+ "hist_bin_edges": bin_edges,
+ "bin_edges": org_bin_edges,
+ "out_pos": 0,
+ "out_neg": 0,
+ }
+ else:
+ self.hists = self.hists_start
self.i = 0
@@ -179,23 +192,19 @@ class BinningPlotter(kp.Module):
return bin_edges
- def _yield_spaced_bin_edges(self):
- for bin_name, bin_edges in self.bin_edges_list:
- if bin_name != "time":
- bin_edges = self._space_bin_edges(bin_edges)
- yield bin_name, bin_edges
-
def process(self, blob):
"""
Extract data from blob for the hist plots.
"""
if self.i % self.bin_plot_freq == 0:
- for bin_name, bin_edges in self._yield_spaced_bin_edges():
+ for bin_name, hists_data in self.hists.items():
+ hist_bin_edges = hists_data["hist_bin_edges"]
+
data = blob["Hits"][bin_name]
- hist = np.histogram(data, bins=bin_edges)[0]
+ hist = np.histogram(data, bins=hist_bin_edges)[0]
- out_pos = data[data > np.max(bin_edges)].size
- out_neg = data[data < np.min(bin_edges)].size
+ out_pos = data[data > np.max(hist_bin_edges)].size
+ out_neg = data[data < np.min(hist_bin_edges)].size
self.hists[bin_name]["hist"] += hist
self.hists[bin_name]["out_pos"] += out_pos
@@ -208,44 +217,54 @@ class BinningPlotter(kp.Module):
"""
Make and save the histograms to pdf.
"""
- with PdfPages(self.pdf_path) as pdf_file:
- for bin_name, org_bin_edges in self.bin_edges_list:
- hist = self.hists[bin_name]["hist"]
- out_pos = self.hists[bin_name]["out_pos"]
- out_neg = self.hists[bin_name]["out_neg"]
- hist_frac = hist / (np.sum(hist) + out_pos + out_neg)
+ if self.pdf_path is not None:
+ plot_hists(self.hists, self.pdf_path,
+ plot_bin_edges=self.plot_bin_edges)
- if bin_name != "time":
- bin_edges = self._space_bin_edges(org_bin_edges)
- else:
- bin_edges = org_bin_edges
+ return self.hists
- bin_spacing = bin_edges[1] - bin_edges[0]
- fig, ax = plt.subplots()
- plt.bar(bin_edges[:-1],
- hist_frac,
- align="edge",
- width=0.9*bin_spacing,
- )
- ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=1))
-
- if self.plot_bin_edges and bin_name != "time":
- for bin_edge in org_bin_edges:
- plt.axvline(x=bin_edge, color='grey', linestyle='-',
- linewidth=1, alpha=0.9)
-
- # place a text box in upper left in axes coords
- out_pos_rel = out_pos / np.sum(hist)
- out_neg_rel = out_neg / np.sum(hist)
- textstr = "Hits cut off:\n Left: {:.1%}\n" \
- " Right: {:.1%}".format(out_neg_rel, out_pos_rel)
- props = dict(boxstyle='round', facecolor='white', alpha=0.9)
- ax.text(0.05, 0.95, textstr, transform=ax.transAxes,
- verticalalignment='top', bbox=props)
-
- plt.xlabel(bin_name)
- plt.ylabel("Fraction of hits")
-
- pdf_file.savefig(fig)
- print(bin_name, out_neg, out_pos)
- print("Saved binning plot to " + self.pdf_path)
+
+def plot_hists(hists, pdf_path, plot_bin_edges=True):
+ """
+ Plot histograms made by the BinningPlotter to the given pdf path.
+
+ """
+ with PdfPages(pdf_path) as pdf_file:
+ for bin_name, hists_data in hists.items():
+ hist_bin_edges = hists_data["hist_bin_edges"]
+ bin_edges = hists_data["bin_edges"]
+ hist = hists_data["hist"]
+ out_pos = hists_data["out_pos"]
+ out_neg = hists_data["out_neg"]
+
+ hist_frac = hist / (np.sum(hist) + out_pos + out_neg)
+
+ bin_spacing = hist_bin_edges[1] - hist_bin_edges[0]
+ fig, ax = plt.subplots()
+ plt.bar(hist_bin_edges[:-1],
+ hist_frac,
+ align="edge",
+ width=0.9 * bin_spacing,
+ )
+ ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=1))
+
+ if plot_bin_edges and bin_name != "time":
+ for bin_edge in bin_edges:
+ plt.axvline(x=bin_edge, color='grey', linestyle='-',
+ linewidth=1, alpha=0.9)
+
+ # place a text box in upper left in axes coords
+ out_pos_rel = out_pos / np.sum(hist)
+ out_neg_rel = out_neg / np.sum(hist)
+ textstr = "Hits cut off:\n Left: {:.1%}\n" \
+ " Right: {:.1%}".format(out_neg_rel, out_pos_rel)
+ props = dict(boxstyle='round', facecolor='white', alpha=0.9)
+ ax.text(0.05, 0.95, textstr, transform=ax.transAxes,
+ verticalalignment='top', bbox=props)
+
+ plt.xlabel(bin_name)
+ plt.ylabel("Fraction of hits")
+
+ pdf_file.savefig(fig)
+
+ print("Saved binning plot to " + pdf_path)