mirror of
https://gitlab.winehq.org/wine/wine-gecko.git
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216 lines
7.8 KiB
Python
216 lines
7.8 KiB
Python
# This Source Code Form is subject to the terms of the Mozilla Public
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# License, v. 2.0. If a copy of the MPL was not distributed with this
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# file, You can obtain one at http://mozilla.org/MPL/2.0/.
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import math
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# For compatibility with Python 2.6
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try:
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from collections import OrderedDict
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except ImportError:
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from simplejson import OrderedDict
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import simplejson as json
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else:
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import json
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def table_dispatch(kind, table, body):
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"""Call body with table[kind] if it exists. Raise an error otherwise."""
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if kind in table:
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return body(table[kind])
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else:
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raise BaseException, "don't know how to handle a histogram of kind %s" % kind
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class DefinitionException(BaseException):
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pass
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def check_numeric_limits(dmin, dmax, n_buckets):
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if type(dmin) != int:
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raise DefinitionException, "minimum is not a number"
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if type(dmax) != int:
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raise DefinitionException, "maximum is not a number"
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if type(n_buckets) != int:
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raise DefinitionException, "number of buckets is not a number"
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def linear_buckets(dmin, dmax, n_buckets):
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check_numeric_limits(dmin, dmax, n_buckets)
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ret_array = [0] * n_buckets
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dmin = float(dmin)
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dmax = float(dmax)
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for i in range(1, n_buckets):
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linear_range = (dmin * (n_buckets - 1 - i) + dmax * (i - 1)) / (n_buckets - 2)
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ret_array[i] = int(linear_range + 0.5)
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return ret_array
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def exponential_buckets(dmin, dmax, n_buckets):
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check_numeric_limits(dmin, dmax, n_buckets)
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log_max = math.log(dmax);
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bucket_index = 2;
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ret_array = [0] * n_buckets
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current = dmin
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ret_array[1] = current
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for bucket_index in range(2, n_buckets):
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log_current = math.log(current)
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log_ratio = (log_max - log_current) / (n_buckets - bucket_index)
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log_next = log_current + log_ratio
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next_value = int(math.floor(math.exp(log_next) + 0.5))
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if next_value > current:
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current = next_value
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else:
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current = current + 1
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ret_array[bucket_index] = current
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return ret_array
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always_allowed_keys = ['kind', 'description', 'cpp_guard']
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class Histogram:
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"""A class for representing a histogram definition."""
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def __init__(self, name, definition):
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"""Initialize a histogram named name with the given definition.
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definition is a dict-like object that must contain at least the keys:
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- 'kind': The kind of histogram. Must be one of 'boolean', 'flag',
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'enumerated', 'linear', or 'exponential'.
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- 'description': A textual description of the histogram.
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The key 'cpp_guard' is optional; if present, it denotes a preprocessor
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symbol that should guard C/C++ definitions associated with the histogram."""
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self.verify_attributes(name, definition)
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self._name = name
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self._description = definition['description']
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self._kind = definition['kind']
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self._cpp_guard = definition.get('cpp_guard')
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self._extended_statistics_ok = definition.get('extended_statistics_ok', False)
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self.compute_bucket_parameters(definition)
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table = { 'boolean': 'BOOLEAN',
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'flag': 'FLAG',
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'enumerated': 'LINEAR',
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'linear': 'LINEAR',
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'exponential': 'EXPONENTIAL' }
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table_dispatch(self.kind(), table,
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lambda k: self._set_nsITelemetry_kind(k))
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def name(self):
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"""Return the name of the histogram."""
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return self._name
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def description(self):
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"""Return the description of the histogram."""
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return self._description
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def kind(self):
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"""Return the kind of the histogram.
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Will be one of 'boolean', 'flag', 'enumerated', 'linear', or 'exponential'."""
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return self._kind
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def nsITelemetry_kind(self):
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"""Return the nsITelemetry constant corresponding to the kind of
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the histogram."""
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return self._nsITelemetry_kind
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def _set_nsITelemetry_kind(self, kind):
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self._nsITelemetry_kind = "nsITelemetry::HISTOGRAM_%s" % kind
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def low(self):
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"""Return the lower bound of the histogram. May be a string."""
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return self._low
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def high(self):
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"""Return the high bound of the histogram. May be a string."""
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return self._high
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def n_buckets(self):
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"""Return the number of buckets in the histogram. May be a string."""
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return self._n_buckets
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def cpp_guard(self):
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"""Return the preprocessor symbol that should guard C/C++ definitions
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associated with the histogram. Returns None if no guarding is necessary."""
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return self._cpp_guard
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def extended_statistics_ok(self):
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"""Return True if gathering extended statistics for this histogram
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is enabled."""
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return self._extended_statistics_ok
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def ranges(self):
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"""Return an array of lower bounds for each bucket in the histogram."""
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table = { 'boolean': linear_buckets,
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'flag': linear_buckets,
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'enumerated': linear_buckets,
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'linear': linear_buckets,
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'exponential': exponential_buckets }
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return table_dispatch(self.kind(), table,
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lambda p: p(self.low(), self.high(), self.n_buckets()))
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def compute_bucket_parameters(self, definition):
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table = {
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'boolean': Histogram.boolean_flag_bucket_parameters,
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'flag': Histogram.boolean_flag_bucket_parameters,
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'enumerated': Histogram.enumerated_bucket_parameters,
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'linear': Histogram.linear_bucket_parameters,
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'exponential': Histogram.exponential_bucket_parameters
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}
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table_dispatch(self.kind(), table,
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lambda p: self.set_bucket_parameters(*p(definition)))
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def verify_attributes(self, name, definition):
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global always_allowed_keys
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general_keys = always_allowed_keys + ['low', 'high', 'n_buckets']
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table = {
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'boolean': always_allowed_keys,
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'flag': always_allowed_keys,
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'enumerated': always_allowed_keys + ['n_values'],
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'linear': general_keys,
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'exponential': general_keys + ['extended_statistics_ok']
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}
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table_dispatch(definition['kind'], table,
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lambda allowed_keys: Histogram.check_keys(name, definition, allowed_keys))
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@staticmethod
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def check_keys(name, definition, allowed_keys):
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for key in definition.iterkeys():
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if key not in allowed_keys:
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raise KeyError, '%s not permitted for %s' % (key, name)
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def set_bucket_parameters(self, low, high, n_buckets):
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def try_to_coerce_to_number(v):
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try:
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return eval(v, {})
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except:
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return v
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self._low = try_to_coerce_to_number(low)
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self._high = try_to_coerce_to_number(high)
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self._n_buckets = try_to_coerce_to_number(n_buckets)
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@staticmethod
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def boolean_flag_bucket_parameters(definition):
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return (1, 2, 3)
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@staticmethod
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def linear_bucket_parameters(definition):
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return (definition.get('low', 1),
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definition['high'],
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definition['n_buckets'])
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@staticmethod
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def enumerated_bucket_parameters(definition):
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n_values = definition['n_values']
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return (1, n_values, "%s+1" % n_values)
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@staticmethod
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def exponential_bucket_parameters(definition):
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return (definition.get('low', 1),
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definition['high'],
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definition['n_buckets'])
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def from_file(filename):
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"""Return an iterator that provides a sequence of Histograms for
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the histograms defined in filename.
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"""
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with open(filename, 'r') as f:
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histograms = json.load(f, object_pairs_hook=OrderedDict)
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for (name, definition) in histograms.iteritems():
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yield Histogram(name, definition)
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