[checkmk-commits] Refactoring: Extraction to independent functions

Module: check_mk Branch: master Commit: 3bf154bd1f7b3e83c555c352ea8eabc74da3befa URL: http://git.mathias-kettner.de/git/?p=check_mk.git;a=commit;h=3bf154bd1f7b3e… Author: Óscar Nájera <on(a)mathias-kettner.de> Date: Tue Nov 20 15:43:43 2018 +0100 Refactoring: Extraction to independent functions In cmk_base/prediction.py isolate and test - level_bounds_estimator - estimate_levels Change-Id: Ib3c98881d0445c45ffb1aac8c03235cea43eb058 --- cmk/gui/plugins/wato/utils/__init__.py | 16 ++++----- cmk_base/prediction.py | 61 +++++++++++++++++++++------------- tests/unit/cmk_base/test_prediction.py | 61 ++++++++++++++++++++++++++++++++++ 3 files changed, 106 insertions(+), 32 deletions(-) diff --git a/cmk/gui/plugins/wato/utils/__init__.py b/cmk/gui/plugins/wato/utils/__init__.py index 4692cb6..c35fc37 100644 --- a/cmk/gui/plugins/wato/utils/__init__.py +++ b/cmk/gui/plugins/wato/utils/__init__.py @@ -906,14 +906,14 @@ def PredictiveLevels(**args): ])), ("stdev", _("In relation to standard deviation"), Tuple(elements=[ - Percentage( + Float( title=_("Warning at"), unit=_("times the standard deviation above the predicted value"), - default_value=2), - Percentage( + default_value=2.0), + Float( title=_("Critical at"), unit=_("times the standard deviation above the predicted value"), - default_value=4), + default_value=4.0), ])), ])), ("levels_upper_min", @@ -955,14 +955,14 @@ def PredictiveLevels(**args): ])), ("stdev", _("In relation to standard deviation"), Tuple(elements=[ - Percentage( + Float( title=_("Warning at"), unit=_("times the standard deviation below the predicted value"), - default_value=2), - Percentage( + default_value=2.0), + Float( title=_("Critical at"), unit=_("times the standard deviation below the predicted value"), - default_value=4), + default_value=4.0), ])), ])), ]) diff --git a/cmk_base/prediction.py b/cmk_base/prediction.py index 13bba2b..a260dec 100644 --- a/cmk_base/prediction.py +++ b/cmk_base/prediction.py @@ -297,31 +297,44 @@ def get_levels(hostname, service_description, dsname, params, cf, levels_factor= # print prediction.keys() reference = dict(zip(prediction["columns"], prediction["points"][index])) # print "Reference: %s" % reference + return estimate_levels(reference, params, levels_factor) + + +def estimate_levels(reference, params, levels_factor): ref_value = reference["average"] - stdev = reference["stdev"] - levels = [] if not ref_value: # No reference data available - levels = ((None, None), (None, None)) - else: - for what, sig in [("upper", 1), ("lower", -1)]: - p = "levels_" + what - if p in params: - how, (warn, crit) = params[p] - if how == "absolute": - this_levels = (ref_value + (sig * warn * levels_factor), - ref_value + (sig * crit * levels_factor)) - elif how == "relative": - this_levels = (ref_value + sig * (ref_value * warn / 100), - ref_value + sig * (ref_value * crit / 100)) - else: # how == "stdev": - this_levels = (ref_value + sig * (stdev * warn), - ref_value + sig * (stdev * crit)) - - if what == "upper" and "levels_upper_min" in params: - limit_warn, limit_crit = params["levels_upper_min"] - this_levels = (max(limit_warn, this_levels[0]), max(limit_crit, this_levels[1])) - levels.append(this_levels) - else: - levels.append((None, None)) + return ref_value, [(None, None), (None, None)] + stdev = reference["stdev"] + levels = [] + for what, sig in [("upper", 1), ("lower", -1)]: + p = "levels_" + what + if p in params: + this_levels = estimate_level_bounds(ref_value, stdev, sig, params[p], levels_factor) + + if what == "upper" and "levels_upper_min" in params: + limit_warn, limit_crit = params["levels_upper_min"] + this_levels = (max(limit_warn, this_levels[0]), max(limit_crit, this_levels[1])) + levels.append(this_levels) + else: + levels.append((None, None)) return ref_value, levels + + +def estimate_level_bounds(ref_value, stdev, sig, params, levels_factor): + how, (warn, crit) = params + if how == "absolute": + return ( + ref_value + (sig * warn * levels_factor), + ref_value + (sig * crit * levels_factor), + ) + elif how == "relative": + return ( + ref_value + sig * (ref_value * warn / 100.0), + ref_value + sig * (ref_value * crit / 100.0), + ) + # how == "stdev": + return ( + ref_value + sig * (stdev * warn), + ref_value + sig * (stdev * crit), + ) diff --git a/tests/unit/cmk_base/test_prediction.py b/tests/unit/cmk_base/test_prediction.py new file mode 100644 index 0000000..e313f73 --- /dev/null +++ b/tests/unit/cmk_base/test_prediction.py @@ -0,0 +1,61 @@ +import pytest + +from cmk_base import prediction + + +(a)pytest.mark.parametrize("ref_valuevalue, stdev, sig, params, levels_factor, result", [ + (2, 0.5, 1, ("absolute", (3, 5)), 0.5, (3.5, 4.5)), + (2, 0.5, -1, ("relative", (20, 50)), 0.5, (1.6, 1)), + (2, 0.5, -1, ("stdev", (2, 4)), 0.5, (1, 0)), +]) +def test_estimate_level_bounds(ref_value, stdev, sig, params, levels_factor, result): + assert prediction.estimate_level_bounds(ref_value, stdev, sig, params, levels_factor) == result + + +(a)pytest.mark.parametrize("referencerence, params, levels_factor, result", [ + ( + { + 'average': 5, + 'stdev': 2 + }, + { + 'levels_lower': ('absolute', (2, 4)) + }, + 1, + (5, [(None, None), (3, 1)]), + ), + ( + { + 'average': 15, + 'stdev': 2, + }, + { + 'levels_upper': ('stddev', (2, 4)), + 'levels_lower': ('stddev', (3, 5)), + }, + 1, + (15, [(19, 23), (9, 5)]), + ), + ( + { + 'average': 2, + 'stdev': 3, + }, + { + 'levels_upper': ('relative', (20, 40)), + 'levels_upper_min': (2, 4), + }, + 1, + (2, [(2.4, 4), (None, None)]), + ), + ( + { + 'average': None + }, + {}, + 1, + (None, [(None, None), (None, None)]), + ), +]) +def test_estimate_levels(reference, params, levels_factor, result): + assert prediction.estimate_levels(reference, params, levels_factor) == result