sumolib.statistics | index /home/delphi/gcc/sumo/tools/sumolib/statistics.py

`# Eclipse SUMO, Simulation of Urban MObility; see https://eclipse.org/sumo
# Copyright (C) 2012-2022 German Aerospace Center (DLR) and others.
# This program and the accompanying materials are made available under the
# terms of the Eclipse Public License 2.0 which is available at
# https://www.eclipse.org/legal/epl-2.0/
# This Source Code may also be made available under the following Secondary
# Licenses when the conditions for such availability set forth in the Eclipse
# Public License 2.0 are satisfied: GNU General Public License, version 2
# or later which is available at
# https://www.gnu.org/licenses/old-licenses/gpl-2.0-standalone.html
# SPDX-License-Identifier: EPL-2.0 OR GPL-2.0-or-later`

Modules
`` |  |
math | warnings |  |

Classes
`` |  | builtins.object Statistics
class Statistics(builtins.object)
`` | `Statistics(label=None, abs=False, histogram=False, printMin=True, scale=1, printDev=False)`
| Methods defined here: __init__(self, label=None, abs=False, histogram=False, printMin=True, scale=1, printDev=False) `Initialize self. See help(type(self)) for accurate signature.` __str__(self) `Return str(self).` add(self, v, label=None) average_absolute_deviation_from_mean(self) avg(self) `return the mean value` avg_abs(self) `return the mean of absolute values` clear(self) count(self) histogram(self) mean(self) meanAndStdDev(self, limit=None) `return the mean and the standard deviation optionally limited to the last limit values` mean_abs(self) median(self) `return the median value` median_abs(self) `return the median of absolute values` normalise_to_range(self, n_min=0, n_max=1) `Normalises the stored list of values between n_min and n_max, Default: [0,1]` quartiles(self) rank(self, fraction) relStdDev(self, limit=None) `return the relative standard deviation optionally limited to the last limit values` toString(self, precision=2, histStyle=1) `histStyle 0 : not shown 1 : one line 2 : fancy` toXML(self, precision=2) update(self, other) Data descriptors defined here: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)`

Functions
`` |  | geh(m, c) `Error function for hourly traffic flow measures after Geoffrey E. Havers` round(value) setPrecision(formatstr, precision, isArray=False) sqv(self, m, c, scaling_factor=1000) `Scaling Quality Value Calculation, Ref: https://journals.sagepub.com/doi/10.1177/0361198119838849 scaling_factor: Number of person trips per day (total, per mode, per purpose) : 1 Mean trip distance in kilometers : 10 Duration of all trips per person per day in minutes : 100 Traffic volume per hour : 1000 Traffic volume per day : 10000`

Data
`` |  | absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0), 262144) division = _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 131072) print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 1048576) sqrt = <ufunc 'sqrt'> uMax = uMax uMin = uMin