Source code for felupe.mechanics._curve

# -*- coding: utf-8 -*-
"""
 _______  _______  ___      __   __  _______  _______ 
|       ||       ||   |    |  | |  ||       ||       |
|    ___||    ___||   |    |  | |  ||    _  ||    ___|
|   |___ |   |___ |   |    |  |_|  ||   |_| ||   |___ 
|    ___||    ___||   |___ |       ||    ___||    ___|
|   |    |   |___ |       ||       ||   |    |   |___ 
|___|    |_______||_______||_______||___|    |_______|

This file is part of felupe.

Felupe is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

Felupe is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with Felupe.  If not, see <http://www.gnu.org/licenses/>.

"""

import numpy as np

from ..dof import Boundary
from ..tools import force
from ._job import Job


[docs]class CharacteristicCurve(Job): def __init__( self, steps, boundary, items=None, callback=lambda stepnumber, substepnumber, substep: None, ): super().__init__(steps, self._callback) self.items = items self.boundary = boundary self.x = [] self.y = [] self.res = None self._cb = callback def _callback(self, stepnumber, substepnumber, substep): if self.items is not None: fun = sum([item.results.force for item in self.items]) else: fun = substep.fun self.x.append(substep.x[0].values[self.boundary.points[0]]) self.y.append(force(substep.x, fun, self.boundary)) self.res = substep self._cb(stepnumber, substepnumber, substep)
[docs] def plot( self, x=None, y=None, xaxis=0, yaxis=0, xlabel="x", ylabel="y", xscale=1, yscale=1, gradient=False, fig=None, ax=None, linestyle=".-", items=None, **kwargs ): import matplotlib.pyplot as plt if self.res is None: self.evaluate(**kwargs) if x is None: x = self.x if y is None: y = self.y if items is None: items = slice(None) x = np.array(x)[items] y = np.array(y)[items] if gradient: y = np.gradient(y, x[:, xaxis], edge_order=2, axis=0) z = np.gradient(y, x[:, xaxis], edge_order=2, axis=0) cuttoff = np.mean(abs(z[:, yaxis])) + 2 * np.std(abs(z[:, yaxis])) y[abs(z) > cuttoff] = np.nan if fig is None or ax is None: fig, ax = plt.subplots() ax.plot(x[:, xaxis] * xscale, y[:, yaxis] * yscale, linestyle) ax.set_xlabel(xlabel) ax.set_ylabel(ylabel) return fig, ax