diff options
Diffstat (limited to 'bin/merge.py')
| -rwxr-xr-x | bin/merge.py | 22 |
1 files changed, 22 insertions, 0 deletions
diff --git a/bin/merge.py b/bin/merge.py index f7dbf90..6091ba1 100755 --- a/bin/merge.py +++ b/bin/merge.py @@ -288,6 +288,14 @@ def param_values(parameters, by_param): return paramvalues +def param_hash(values): + ret = {} + + for i, param in enumerate(parameters): + ret[param] = values[i] + + return ret + # Returns the values used for each function argument in the measurement, e.g. # { 'data': [], 'length' : [16, 31, 32] } # non-numeric values such as '' or 'long_test_string' are skipped @@ -547,11 +555,24 @@ def param_measures(name, paramdata, key, fun): def arg_measures(name, argdata, key, fun): return param_measures(name, argdata, key, fun) +def lookup_table(name, paramdata, key, fun, keyfun): + lut = [] + + for pkey, pval in paramdata.items(): + if pkey[0] == name: + lut.append({ + 'key': keyfun(pkey[1]), + 'value': fun(pval[key]), + }) + + return lut + def keydata(name, val, argdata, paramdata, tracedata, key): ret = { 'count' : len(val[key]), 'median' : np.median(val[key]), 'mean' : np.mean(val[key]), + 'median_by_param' : lookup_table(name, paramdata, key, np.median, param_hash), 'mean_goodness' : aggregate_measures(np.mean(val[key]), val[key]), 'median_goodness' : aggregate_measures(np.median(val[key]), val[key]), 'param_mean_goodness' : param_measures(name, paramdata, key, np.mean), @@ -567,6 +588,7 @@ def keydata(name, val, argdata, paramdata, tracedata, key): if val['isa'] == 'transition': ret['arg_mean_goodness'] = arg_measures(name, argdata, key, np.mean) ret['arg_median_goodness'] = arg_measures(name, argdata, key, np.median) + ret['median_by_arg'] = lookup_table(name, argdata, key, np.median, list) ret['std_arg'] = np.mean([np.std(argdata[x][key]) for x in argdata.keys() if x[0] == name]) ret['std_by_arg'] = {} ret['arg_fit_guess'] = {} |