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Changed scripts to not infer field purposes from CSV values

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Note there's a bit of subtlety here, field _types_ are still infered,
but the intention of the fields, i.e. if the field contains data vs
row name/other properties, must be unambiguous in the scripts.

There is still a _tiny_ bit of inference. For most scripts only one
of --by or --fields is strictly needed, since this makes the purpose of
the other fields unambiguous.

The reason for this change is so the scripts are a bit more reliable,
but also because this simplifies the data parsing/inference a bit.

Oh, and this also changes field inference to use the csv.DictReader's
fieldnames field instead of only inspecting the returned dicts. This
should also save a bit of O(n) overhead when parsing CSV files.
This commit is contained in:
Christopher Haster
2023-11-04 15:24:18 -05:00
parent 2be3ff57c5
commit d0a6ef0c89
12 changed files with 187 additions and 200 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/amor.py
+49 -42
View File
@@ -46,11 +46,15 @@ def dat(x):
def collect(csv_paths, renames=[], defines=[]):
# collect results from CSV files
fields = []
results = []
for path in csv_paths:
try:
with openio(path) as f:
reader = csv.DictReader(f, restval='')
fields.extend(
k for k in reader.fieldnames
if k not in fields)
for r in reader:
# apply any renames
if renames:
@@ -69,15 +73,15 @@ def collect(csv_paths, renames=[], defines=[]):
except FileNotFoundError:
pass
return results
return fields, results
def main(csv_paths, output, *,
amor=False,
per=False,
by=None,
meas=None,
iter=None,
size=None,
by=None,
fields=None,
defines=[]):
# default to amortizing and per-byte results if size is present
@@ -95,40 +99,43 @@ def main(csv_paths, output, *,
if fields is not None:
fields = [k for k, _ in fields]
if by is None and fields is None:
print("error: needs --by or --fields to figure out fields")
sys.exit(-1)
# collect results from csv files
results = collect(csv_paths, renames, defines)
fields_, results = collect(csv_paths, renames, defines)
# if fields not specified, try to guess from data
if fields is None:
fields = co.OrderedDict()
for r in results:
for k, v in r.items():
if k not in (by or []) and k != iter and v.strip():
try:
dat(v)
fields[k] = True
except ValueError:
fields[k] = False
fields = list(k for k,v in fields.items() if v)
# if by not specified, guess it's anything not in iter/fields and not a
# source of a rename
# if by not specified, guess it's anything not in
# iter/size/fields/renames/defines
if by is None:
by = co.OrderedDict()
for r in results:
# also ignore None keys, these are introduced by csv.DictReader
# when header + row mismatch
by.update((k, True) for k in r.keys()
if k is not None
and k != iter
and k not in fields
and not any(k == old_k for _, old_k in renames))
by = list(by.keys())
by = [
k for k in fields_
if k != iter
and k != size
and k not in (fields or [])
and not any(k == old_k for _, old_k in renames)
and not any(k == k_ for k_, _ in defines)]
# if fields not specified, guess it's anything not in
# by/iter/size/renames/defines
if fields is None:
fields = [
k for k in fields_
if k not in (by or [])
and k != iter
and k != size
and not any(k == old_k for _, old_k in renames)
and not any(k == k_ for k_, _ in defines)]
# add meas to by if it isn't already present
if meas is not None and meas not in by:
by.append(meas)
# convert iter/fields to ints/floats
for r in results:
for k in {iter} | set(fields) | ({size} if size is not None else {}):
if k in r:
for k in it.chain([iter], [size] if size is not None else [], fields):
if k in r and isinstance(r[k], str):
r[k] = dat(r[k]) if r[k].strip() else 0
# organize by 'by' values
@@ -141,7 +148,7 @@ def main(csv_paths, output, *,
# for each key compute the amortized results
amors = []
for key, rs in results.items():
# keep a running sum for each fied
# keep a running sum for each field
sums = {f: 0 for f in fields}
size_ = 0
for j, (i, r) in enumerate(sorted(
@@ -171,7 +178,7 @@ def main(csv_paths, output, *,
# write results to CSV
with openio(output, 'w') as f:
writer = csv.DictWriter(f,
by + ([meas] if meas not in by else []) + [iter] + fields)
by + [iter] + ([size] if size is not None else []) + fields)
writer.writeheader()
for r in amors:
writer.writerow(r)
@@ -199,6 +206,16 @@ if __name__ == "__main__":
'--per',
action='store_true',
help="Compute per-byte results.")
parser.add_argument(
'-b', '--by',
action='append',
type=lambda x: (
lambda k, vs=None: (
k.strip(),
tuple(v.strip() for v in vs.split(','))
if vs is not None else ())
)(*x.split('=', 1)),
help="Group by this field. Can rename fields with new_name=old_name.")
parser.add_argument(
'-m', '--meas',
help="Optional name of measurement name field. If provided, the name "
@@ -210,16 +227,6 @@ if __name__ == "__main__":
parser.add_argument(
'-n', '--size',
help="Optional name of size field.")
parser.add_argument(
'-b', '--by',
action='append',
type=lambda x: (
lambda k, vs=None: (
k.strip(),
tuple(v.strip() for v in vs.split(','))
if vs is not None else ())
)(*x.split('=', 1)),
help="Group by this field. Can rename fields with new_name=old_name.")
parser.add_argument(
'-f', '--field',
dest='fields',
scripts/avg.py
+43 -40
View File
@@ -46,11 +46,15 @@ def dat(x):
def collect(csv_paths, renames=[], defines=[]):
# collect results from CSV files
fields = []
results = []
for path in csv_paths:
try:
with openio(path) as f:
reader = csv.DictReader(f, restval='')
fields.extend(
k for k in reader.fieldnames
if k not in fields)
for r in reader:
# apply any renames
if renames:
@@ -69,7 +73,7 @@ def collect(csv_paths, renames=[], defines=[]):
except FileNotFoundError:
pass
return results
return fields, results
def main(csv_paths, output, *,
sum=False,
@@ -81,8 +85,8 @@ def main(csv_paths, output, *,
stddev=False,
gmean=False,
gstddev=False,
meas=None,
by=None,
meas=None,
seeds=None,
fields=None,
defines=[]):
@@ -113,40 +117,41 @@ def main(csv_paths, output, *,
if fields is not None:
fields = [k for k, _ in fields]
if by is None and fields is None:
print("error: needs --by or --fields to figure out fields")
sys.exit(-1)
# collect results from csv files
results = collect(csv_paths, renames, defines)
fields_, results = collect(csv_paths, renames, defines)
# if fields not specified, try to guess from data
if fields is None:
fields = co.OrderedDict()
for r in results:
for k, v in r.items():
if k not in (by or []) and k not in (seeds or []) and v.strip():
try:
dat(v)
fields[k] = True
except ValueError:
fields[k] = False
fields = list(k for k,v in fields.items() if v)
# if by not specified, guess it's anything not in seeds/fields and not a
# source of a rename
# if by not specified, guess it's anything not in
# seeds/fields/renames/defines
if by is None:
by = co.OrderedDict()
for r in results:
# also ignore None keys, these are introduced by csv.DictReader
# when header + row mismatch
by.update((k, True) for k in r.keys()
if k is not None
and k not in (seeds or [])
and k not in fields
and not any(k == old_k for _, old_k in renames))
by = list(by.keys())
by = [
k for k in fields_
if k not in (seeds or [])
and k not in (fields or [])
and not any(k == old_k for _, old_k in renames)
and not any(k == k_ for k_, _ in defines)]
# if fields not specified, guess it's anything not in
# by/seeds/renames/defines
if fields is None:
fields = [
k for k in fields_
if k not in (by or [])
and k not in (seeds or [])
and not any(k == old_k for _, old_k in renames)
and not any(k == k_ for k_, _ in defines)]
# add meas to by if it isn't already present
if meas is not None and meas not in by:
by.append(meas)
# convert fields to ints/floats
for r in results:
for k in fields:
if k in r:
if k in r and isinstance(r[k], str):
r[k] = dat(r[k]) if r[k].strip() else 0
# organize by 'by' values
@@ -162,11 +167,10 @@ def main(csv_paths, output, *,
vs = {f: [] for f in fields}
meas__ = None
for r in rs:
if all(k in r and r[k] == v for k, v in zip(by, key)):
for f in fields:
vs[f].append(r.get(f, 0))
if meas is not None and meas in r:
meas__ = r[meas]
for f in fields:
vs[f].append(r.get(f, 0))
if meas is not None and meas in r:
meas__ = r[meas]
def append(meas_, f_):
avgs.append(
@@ -197,8 +201,7 @@ def main(csv_paths, output, *,
# write results to CSVS
with openio(output, 'w') as f:
writer = csv.DictWriter(f,
by + ([meas] if meas not in by else []) + fields)
writer = csv.DictWriter(f, by + fields)
writer.writeheader()
for r in avgs:
writer.writerow(r)
@@ -254,10 +257,6 @@ if __name__ == "__main__":
'--gstddev',
action='store_true',
help="Compute the geometric standard deviation.")
parser.add_argument(
'-m', '--meas',
help="Optional name of measurement name field. If provided, the name "
"will be modified with +amor or +per.")
parser.add_argument(
'-b', '--by',
action='append',
@@ -268,6 +267,10 @@ if __name__ == "__main__":
if vs is not None else ())
)(*x.split('=', 1)),
help="Group by this field. Can rename fields with new_name=old_name.")
parser.add_argument(
'-m', '--meas',
help="Optional name of measurement name field. If provided, the name "
"will be modified with +amor or +per.")
parser.add_argument(
'-s', '--seed',
dest='seeds',
scripts/code.py
+1 -4
View File
@@ -315,10 +315,7 @@ def collect(obj_paths, *,
return results
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
scripts/cov.py
+1 -4
View File
@@ -297,10 +297,7 @@ def collect(gcda_paths, *,
return results
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
scripts/data.py
+1 -4
View File
@@ -315,10 +315,7 @@ def collect(obj_paths, *,
return results
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
scripts/perf.py
+1 -4
View File
@@ -627,10 +627,7 @@ def collect(perf_paths, *,
return results
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
scripts/perfbd.py
+1 -4
View File
@@ -593,10 +593,7 @@ def collect(obj_path, trace_paths, *,
return results
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
scripts/plot.py
+29 -25
View File
@@ -445,11 +445,15 @@ class Plot:
def collect(csv_paths, renames=[], defines=[]):
# collect results from CSV files
fields = []
results = []
for path in csv_paths:
try:
with openio(path) as f:
reader = csv.DictReader(f, restval='')
fields.extend(
k for k in reader.fieldnames
if k not in fields)
for r in reader:
# apply any renames
if renames:
@@ -468,7 +472,7 @@ def collect(csv_paths, renames=[], defines=[]):
except FileNotFoundError:
pass
return results
return fields, results
def fold(results, by=None, x=None, y=None, defines=[]):
# filter by matching defines
@@ -479,29 +483,16 @@ def fold(results, by=None, x=None, y=None, defines=[]):
results_.append(r)
results = results_
# if y not specified, try to guess from data
if not y:
y = co.OrderedDict()
for r in results:
for k, v in r.items():
if (not by or k not in by) and v.strip():
try:
dat(v)
y[k] = True
except ValueError:
y[k] = False
y = list(k for k,v in y.items() if v)
if by:
# find all 'by' values
ks = set()
keys = set()
for r in results:
ks.add(tuple(r.get(k, '') for k in by))
ks = sorted(ks)
keys.add(tuple(r.get(k, '') for k in by))
keys = sorted(keys)
# collect all datasets
datasets = co.OrderedDict()
for ks_ in (ks if by else [()]):
for key in (keys if by else [()]):
for x_ in (x if x else [None]):
for y_ in y:
# organize by 'by', x, and y
@@ -511,7 +502,7 @@ def fold(results, by=None, x=None, y=None, defines=[]):
# filter by 'by'
if by and not all(
k in r and r[k] == v
for k, v in zip(by, ks_)):
for k, v in zip(by, key)):
continue
# find xs
@@ -542,8 +533,8 @@ def fold(results, by=None, x=None, y=None, defines=[]):
# hide x/y if there is only one field
k_x = x_ if len(x or []) > 1 else ''
k_y = y_ if len(y or []) > 1 or (not ks_ and not k_x) else ''
datasets[ks_ + (k_x, k_y)] = dataset
k_y = y_ if len(y or []) > 1 or (not key and not k_x) else ''
datasets[key + (k_x, k_y)] = dataset
return datasets
@@ -904,13 +895,17 @@ def main(csv_paths, *,
all_defines = sorted(all_defines.items())
# separate out renames
renames = list(it.chain.from_iterable(
all_renames = list(it.chain.from_iterable(
((k, v) for v in vs)
for k, vs in it.chain(all_by, all_x, all_y)))
all_by = [k for k, _ in all_by]
all_x = [k for k, _ in all_x]
all_y = [k for k, _ in all_y]
if not all_by and not all_y:
print("error: needs --by or -y to figure out fields")
sys.exit(-1)
# create a grid of subplots
grid = Grid.fromargs(**subplot, subplots=subplots)
@@ -994,10 +989,19 @@ def main(csv_paths, *,
f.writeln = writeln
# first collect results from CSV files
results = collect(csv_paths, renames, all_defines)
fields_, results = collect(csv_paths, all_renames, all_defines)
# if y not specified, guess it's anything not in by/defines/x/renames
all_y_ = all_y
if not all_y:
all_y_ = [
k for k in fields_
if k not in all_by
and not any(k == k_ for k_, _ in all_defines)
and not any(k == old_k for _, old_k in all_renames)]
# then extract the requested datasets
datasets_ = fold(results, all_by, all_x, all_y)
datasets_ = fold(results, all_by, all_x, all_y_)
# figure out colors/chars here so that subplot defines
# don't change them later, that'd be bad
@@ -1143,7 +1147,7 @@ def main(csv_paths, *,
# data can be constrained by subplot-specific defines,
# so re-extract for each plot
subdatasets = fold(results, all_by, all_x, all_y, define_)
subdatasets = fold(results, all_by, all_x, all_y_, define_)
# filter by subplot x/y
subdatasets = co.OrderedDict([(name, dataset)
scripts/plotmpl.py
+26 -23
View File
@@ -191,11 +191,15 @@ def dat(x):
def collect(csv_paths, renames=[], defines=[]):
# collect results from CSV files
fields = []
results = []
for path in csv_paths:
try:
with openio(path) as f:
reader = csv.DictReader(f, restval='')
fields.extend(
k for k in reader.fieldnames
if k not in fields)
for r in reader:
# apply any renames
if renames:
@@ -214,7 +218,7 @@ def collect(csv_paths, renames=[], defines=[]):
except FileNotFoundError:
pass
return results
return fields, results
def fold(results, by=None, x=None, y=None, defines=[]):
# filter by matching defines
@@ -225,29 +229,16 @@ def fold(results, by=None, x=None, y=None, defines=[]):
results_.append(r)
results = results_
# if y not specified, try to guess from data
if not y:
y = co.OrderedDict()
for r in results:
for k, v in r.items():
if (not by or k not in by) and v.strip():
try:
dat(v)
y[k] = True
except ValueError:
y[k] = False
y = list(k for k,v in y.items() if v)
if by:
# find all 'by' values
ks = set()
keys = set()
for r in results:
ks.add(tuple(r.get(k, '') for k in by))
ks = sorted(ks)
keys.add(tuple(r.get(k, '') for k in by))
keys = sorted(keys)
# collect all datasets
datasets = co.OrderedDict()
for ks_ in (ks if by else [()]):
for key in (keys if by else [()]):
for x_ in (x if x else [None]):
for y_ in y:
# organize by 'by', x, and y
@@ -257,7 +248,7 @@ def fold(results, by=None, x=None, y=None, defines=[]):
# filter by 'by'
if by and not all(
k in r and r[k] == v
for k, v in zip(by, ks_)):
for k, v in zip(by, key)):
continue
# find xs
@@ -288,8 +279,8 @@ def fold(results, by=None, x=None, y=None, defines=[]):
# hide x/y if there is only one field
k_x = x_ if len(x or []) > 1 else ''
k_y = y_ if len(y or []) > 1 or (not ks_ and not k_x) else ''
datasets[ks_ + (k_x, k_y)] = dataset
k_y = y_ if len(y or []) > 1 or (not key and not k_x) else ''
datasets[key + (k_x, k_y)] = dataset
return datasets
@@ -746,15 +737,27 @@ def main(csv_paths, output, *,
all_defines = sorted(all_defines.items())
# separate out renames
renames = list(it.chain.from_iterable(
all_renames = list(it.chain.from_iterable(
((k, v) for v in vs)
for k, vs in it.chain(all_by, all_x, all_y)))
all_by = [k for k, _ in all_by]
all_x = [k for k, _ in all_x]
all_y = [k for k, _ in all_y]
if not all_by and not all_y:
print("error: needs --by or -y to figure out fields")
sys.exit(-1)
# first collect results from CSV files
results = collect(csv_paths, renames, all_defines)
fields_, results = collect(csv_paths, all_renames, all_defines)
# if y not specified, guess it's anything not in by/defines/x/renames
if not all_y:
all_y = [
k for k in fields_
if k not in all_by
and not any(k == k_ for k_, _ in all_defines)
and not any(k == old_k for _, old_k in all_renames)]
# then extract the requested datasets
datasets_ = fold(results, all_by, all_x, all_y)
scripts/stack.py
+1 -4
View File
@@ -273,10 +273,7 @@ def collect(ci_paths, *,
return results
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
scripts/structs.py
+1 -4
View File
@@ -264,10 +264,7 @@ def collect(obj_paths, *,
return results
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
scripts/summary.py
+33 -42
View File
@@ -251,11 +251,15 @@ def openio(path, mode='r', buffering=-1):
def collect(csv_paths, renames=[], defines=[]):
# collect results from CSV files
fields = []
results = []
for path in csv_paths:
try:
with openio(path) as f:
reader = csv.DictReader(f, restval='')
fields.extend(
k for k in reader.fieldnames
if k not in fields)
for r in reader:
# apply any renames
if renames:
@@ -274,49 +278,34 @@ def collect(csv_paths, renames=[], defines=[]):
except FileNotFoundError:
pass
return results
return fields, results
def infer(results, *,
def infer(fields_, results,
by=None,
fields=None,
types={},
ops={},
renames=[],
**_):
# if fields not specified, try to guess from data
if fields is None:
fields = co.OrderedDict()
for r in results:
for k, v in r.items():
if (by is None or k not in by) and v.strip():
types_ = []
for t in fields.get(k, TYPES.values()):
try:
t(v)
types_.append(t)
except ValueError:
pass
fields[k] = types_
fields = list(k for k, v in fields.items() if v)
# deduplicate fields
fields = list(co.OrderedDict.fromkeys(fields).keys())
# if by not specified, guess it's anything not in fields and not a
# source of a rename
defines=[]):
# if by not specified, guess it's anything not in fields/renames/defines
if by is None:
by = co.OrderedDict()
for r in results:
# also ignore None keys, these are introduced by csv.DictReader
# when header + row mismatch
by.update((k, True) for k in r.keys()
if k is not None
and k not in fields
and not any(k == old_k for _, old_k in renames))
by = list(by.keys())
by = [
k for k in fields_
if k not in (fields or [])
and not any(k == old_k for _, old_k in renames)
and not any(k == k_ for k_, _ in defines)]
# deduplicate fields
# if fields not specified, guess it's anything not in by/renames/defines
if fields is None:
fields = [
k for k in fields_
if k not in (by or [])
and not any(k == old_k for _, old_k in renames)
and not any(k == k_ for k_, _ in defines)]
# deduplicate by/fields
by = list(co.OrderedDict.fromkeys(by).keys())
fields = list(co.OrderedDict.fromkeys(fields).keys())
# find best type for all fields
types_ = {}
@@ -381,10 +370,7 @@ def infer(results, *,
})
def fold(Result, results, *,
by=None,
defines=[],
**_):
def fold(Result, results, by=None, defines=[]):
if by is None:
by = Result._by
@@ -634,16 +620,21 @@ def main(csv_paths, *,
ops_[new_k] = ops[old_k]
ops.update(ops_)
if by is None and fields is None:
print("error: needs --by or --fields to figure out fields")
sys.exit(-1)
# find CSV files
results = collect(csv_paths, renames=renames, defines=defines)
fields_, results = collect(csv_paths, renames, defines)
# homogenize
Result = infer(results,
Result = infer(fields_, results,
by=by,
fields=fields,
types=types,
ops=ops,
renames=renames)
renames=renames,
defines=defines)
results_ = []
for r in results:
if not any(k in r and r[k].strip()
@@ -682,7 +673,7 @@ def main(csv_paths, *,
# find previous results?
if args.get('diff'):
diff_results = collect([args['diff']], renames=renames, defines=defines)
_, diff_results = collect([args['diff']], renames, defines)
diff_results_ = []
for r in diff_results:
if not any(k in r and r[k].strip()