From b7744641563edfd482cd9a4f9efec3b0f9bb96af Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Wed, 16 Mar 2022 12:55:25 -0400 Subject: [PATCH] whitespace --- tools/python/pizza/dump.py | 58 +++++++++++++++++++------------------- tools/python/pizza/gnu.py | 18 ++++++------ tools/python/pizza/log.py | 4 +-- 3 files changed, 40 insertions(+), 40 deletions(-) diff --git a/tools/python/pizza/dump.py b/tools/python/pizza/dump.py index 5c7fab33ae..015cd8f0e7 100644 --- a/tools/python/pizza/dump.py +++ b/tools/python/pizza/dump.py @@ -16,15 +16,15 @@ oneline = "Read, write, manipulate dump files and particle attributes" docstr = """ d = dump("dump.one") read in one or more dump files -d = dump("dump.1 dump.2.gz") can be gzipped -d = dump("dump.*") wildcard expands to multiple files -d = dump("dump.*",0) two args = store filenames, but don't read +d = dump("dump.1 dump.2.gz") can be gzipped +d = dump("dump.*") wildcard expands to multiple files +d = dump("dump.*",0) two args = store filenames, but don't read incomplete and duplicate snapshots are deleted if atoms have 5 or 8 columns, assign id,type,x,y,z (ix,iy,iz) atoms will be unscaled if stored in files as scaled -time = d.next() read next snapshot from dump files +time = d.next() read next snapshot from dump files used with 2-argument constructor to allow reading snapshots one-at-a-time snapshot will be skipped only if another snapshot has same time stamp @@ -36,20 +36,20 @@ d.map(1,"id",3,"x") assign names to atom columns (1-N) not needed if dump file is self-describing -d.tselect.all() select all timesteps -d.tselect.one(N) select only timestep N -d.tselect.none() deselect all timesteps -d.tselect.skip(M) select every Mth step +d.tselect.all() select all timesteps +d.tselect.one(N) select only timestep N +d.tselect.none() deselect all timesteps +d.tselect.skip(M) select every Mth step d.tselect.test("$t >= 100 and $t < 10000") select matching timesteps -d.delete() delete non-selected timesteps +d.delete() delete non-selected timesteps selecting a timestep also selects all atoms in the timestep skip() and test() only select from currently selected timesteps test() uses a Python Boolean expression with $t for timestep value Python comparison syntax: == != < > <= >= and or -d.aselect.all() select all atoms in all steps -d.aselect.all(N) select all atoms in one step +d.aselect.all() select all atoms in all steps +d.aselect.all(N) select all atoms in one step d.aselect.test("$id > 100 and $type == 2") select match atoms in all steps d.aselect.test("$id > 100 and $type == 2",N) select matching atoms in one step @@ -60,24 +60,24 @@ d.aselect.test("$id > 100 and $type == 2",N) select matching atoms in one step Python comparison syntax: == != < > <= >= and or $name must end with a space -d.write("file") write selected steps/atoms to dump file -d.write("file",head,app) write selected steps/atoms to dump file -d.scatter("tmp") write selected steps/atoms to multiple files +d.write("file") write selected steps/atoms to dump file +d.write("file",head,app) write selected steps/atoms to dump file +d.scatter("tmp") write selected steps/atoms to multiple files write() can be specified with 2 additional flags headd = 0/1 for no/yes snapshot header, app = 0/1 for write vs append scatter() files are given timestep suffix: e.g. tmp.0, tmp.100, etc -d.scale() scale x,y,z to 0-1 for all timesteps -d.scale(100) scale atom coords for timestep N -d.unscale() unscale x,y,z to box size to all timesteps -d.unscale(1000) unscale atom coords for timestep N -d.wrap() wrap x,y,z into periodic box via ix,iy,iz -d.unwrap() unwrap x,y,z out of box via ix,iy,iz -d.owrap("other") wrap x,y,z to same image as another atom -d.sort() sort atoms by atom ID in all selected steps -d.sort("x") sort atoms by column value in all steps -d.sort(1000) sort atoms in timestep N +d.scale() scale x,y,z to 0-1 for all timesteps +d.scale(100) scale atom coords for timestep N +d.unscale() unscale x,y,z to box size to all timesteps +d.unscale(1000) unscale atom coords for timestep N +d.wrap() wrap x,y,z into periodic box via ix,iy,iz +d.unwrap() unwrap x,y,z out of box via ix,iy,iz +d.owrap("other") wrap x,y,z to same image as another atom +d.sort() sort atoms by atom ID in all selected steps +d.sort("x") sort atoms by column value in all steps +d.sort(1000) sort atoms in timestep N scale(), unscale(), wrap(), unwrap(), owrap() operate on all steps and atoms wrap(), unwrap(), owrap() require ix,iy,iz be defined @@ -89,8 +89,8 @@ d.sort(1000) sort atoms in timestep N m1,m2 = d.minmax("type") find min/max values for a column d.set("$ke = $vx * $vx + $vy * $vy") set a column to a computed value d.setv("type",vector) set a column to a vector of values -d.spread("ke",N,"color") 2nd col = N ints spread over 1st col -d.clone(1000,"color") clone timestep N values to other steps +d.spread("ke",N,"color") 2nd col = N ints spread over 1st col +d.clone(1000,"color") clone timestep N values to other steps minmax() operates on selected timesteps and atoms set() operates on selected timesteps and atoms @@ -111,7 +111,7 @@ d.clone(1000,"color") clone timestep N values to other steps values at every timestep are set to value at timestep N for that atom ID useful for propagating a color map -t = d.time() return vector of selected timestep values +t = d.time() return vector of selected timestep values fx,fy,... = d.atom(100,"fx","fy",...) return vector(s) for atom ID N fx,fy,... = d.vecs(1000,"fx","fy",...) return vector(s) for timestep N @@ -121,8 +121,8 @@ fx,fy,... = d.vecs(1000,"fx","fy",...) return vector(s) for timestep N index,time,flag = d.iterator(0/1) loop over dump snapshots time,box,atoms,bonds,tris = d.viz(index) return list of viz objects d.atype = "color" set column returned as "type" by viz -d.extra("dump.bond") read bond list from dump file -d.extra(data) extract bond/tri/line list from data +d.extra("dump.bond") read bond list from dump file +d.extra(data) extract bond/tri/line list from data iterator() loops over selected timesteps iterator() called with arg = 0 first time, with arg = 1 on subsequent calls diff --git a/tools/python/pizza/gnu.py b/tools/python/pizza/gnu.py index 6e0fc1ee0b..41d19e0139 100644 --- a/tools/python/pizza/gnu.py +++ b/tools/python/pizza/gnu.py @@ -14,12 +14,12 @@ from __future__ import print_function oneline = "Create plots via GnuPlot plotting program" docstr = """ -g = gnu() start up GnuPlot -g.stop() shut down GnuPlot process +g = gnu() start up GnuPlot +g.stop() shut down GnuPlot process g.plot(a) plot vector A against linear index -g.plot(a,b) plot B against A -g.plot(a,b,c,d,...) plot B against A, D against C, etc +g.plot(a,b) plot B against A +g.plot(a,b,c,d,...) plot B against A, D against C, etc g.mplot(M,N,S,"file",a,b,...) multiple plots saved to file0000.eps, etc each plot argument can be a tuple, list, or Numeric/NumPy vector @@ -32,21 +32,21 @@ g.mplot(M,N,S,"file",a,b,...) multiple plots saved to file0000.eps, etc g("plot 'file.dat' using 2:3 with lines") execute string in GnuPlot -g.enter() enter GnuPlot shell +g.enter() enter GnuPlot shell gnuplot> plot sin(x) with lines type commands directly to GnuPlot -gnuplot> exit, quit exit GnuPlot shell +gnuplot> exit, quit exit GnuPlot shell g.export("data",range(100),a,...) create file with columns of numbers all vectors must be of equal length could plot from file with GnuPlot command: plot 'data' using 1:2 with lines -g.select(N) figure N becomes the current plot +g.select(N) figure N becomes the current plot subsequent commands apply to this plot -g.hide(N) delete window for figure N -g.save("file") save current plot as file.eps +g.hide(N) delete window for figure N +g.save("file") save current plot as file.eps Set attributes for current plot: diff --git a/tools/python/pizza/log.py b/tools/python/pizza/log.py index ba9cb150e4..e8e5db9157 100644 --- a/tools/python/pizza/log.py +++ b/tools/python/pizza/log.py @@ -73,7 +73,7 @@ class log: self.data = [] # flist = list of all log file names - + words = arglist[0].split() self.flist = [] for word in words: self.flist += glob.glob(word) @@ -102,7 +102,7 @@ class log: # sort entries by timestep, cull duplicates - self.data.sort(key=(lambda elem: elem[0])) + self.data.sort(key=(lambda elem: elem[0])) self.cull() self.nlen = len(self.data) print("read %d log entries" % self.nlen)