def plot_random_var(self, var_list=None, histogram_kwargs=None, plot_kwargs=None): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. Default is plotting all the random variables. histogram_kwargs : dict, optional Additional key word arguments can be passed to change the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...). *See Plotly API to more information. plot_kwargs : dict, optional Additional key word arguments can be passed to change the plotly go.figure (e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...). *See Plotly API to more information. Returns ------- fig : Plotly graph_objects.Figure() A figure with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> elm = srs.st_shaft_example() >>> fig = elm.plot_random_var(["odl"]) >>> # fig.show() """ label = dict( L="Length", idl="Left inner diameter", odl="Left outer diameter", idr="Right inner diameter", odr="Right outer diameter", ) is_random = self.is_random if "material" in is_random: is_random.remove("material") if var_list is None: var_list = is_random elif not all(var in is_random for var in var_list): raise ValueError( "Random variable not in var_list. Select variables from {}". format(is_random)) return plot_histogram(self.attribute_dict, label, var_list, histogram_kwargs={}, plot_kwargs={})
def plot_random_var(self, var_list=None, histogram_kwargs=None, plot_kwargs=None): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. Default is plotting all the random variables. histogram_kwargs : dict, optional Additional key word arguments can be passed to change the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...). *See Plotly API to more information. plot_kwargs : dict, optional Additional key word arguments can be passed to change the plotly go.figure (e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...). *See Plotly API to more information. Returns ------- fig : Plotly graph_objects.Figure() A figure with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> elm = srs.st_bearing_example() >>> fig = elm.plot_random_var(["kxx"]) >>> # fig.show() """ label = dict( kxx="Kxx", kxy="Kxy", kyx="Kyx", kyy="Kyy", cxx="Cxx", cxy="Cxy", cyx="Cyx", cyy="Cyy", ) if var_list is None: var_list = self.is_random elif not all(var in self.is_random for var in var_list): raise ValueError( "Random variable not in var_list. Select variables from {}". format(self.is_random)) return plot_histogram(self.attribute_dict, label, var_list, histogram_kwargs, plot_kwargs)
def plot_random_var(self, var_list=[], histogram_kwargs={}, plot_kwargs={}): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. histogram_kwargs : dict, optional Additional key word arguments can be passed to change the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...). *See Plotly API to more information. plot_kwargs : dict, optional Additional key word arguments can be passed to change the plotly go.figure (e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...). *See Plotly API to more information. Returns ------- fig : Plotly graph_objects.Figure() A figure with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> E = np.random.uniform(208e9, 211e9, 5) >>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9) >>> fig = st_steel.plot_random_var(["E"]) >>> # fig.show() """ label = dict( E="Young's Modulus", G_s="Shear Modulus", Poisson="Poisson coefficient", rho="density", ) is_random = self.is_random if not all(var in self.is_random for var in var_list): raise ValueError( "Not random variable in var_list. Select variables from {}". format(is_random)) return plot_histogram(self.attribute_dict, label, var_list, histogram_kwargs={}, plot_kwargs={})
def plot_random_var(self, var_list=[], histogram_kwargs={}, plot_kwargs={}): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. histogram_kwargs : dict, optional Additional key word arguments can be passed to change the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...). *See Plotly API to more information. plot_kwargs : dict, optional Additional key word arguments can be passed to change the plotly go.figure (e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...). *See Plotly API to more information. Returns ------- fig : Plotly graph_objects.Figure() A figure with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> elm = srs.st_pointmass_example() >>> fig = elm.plot_random_var(["mx"]) >>> # fig.show() """ label = dict( mx="Mass on the X direction", my="Mass on the Y direction", m="Mass", ) if not all(var in self.is_random for var in var_list): raise ValueError( "Not random variable in var_list. Select variables from {}". format(self.is_random)) return plot_histogram(self.attribute_dict, label, var_list, histogram_kwargs={}, plot_kwargs={})
def plot_random_var(self, var_list=[], **kwargs): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. **kwargs : optional Additional key word arguments can be passed to change the numpy.histogram (e.g. density=True, bins=11, ...) Returns ------- grid_plot : bokeh row A row with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> elm = srs.st_shaft_example() >>> elm.plot_random_var(["odl"]) # doctest: +ELLIPSIS Row... """ label = dict( L="Length", idl="Left inner diameter", odl="Left outer diameter", idr="Right inner diameter", odr="Right outer diameter", ) is_random = self.is_random if "material" in is_random: is_random.remove("material") if not all(var in self.is_random for var in var_list): raise ValueError( "Not random variable in var_list. Select variables from {}". format(is_random)) return plot_histogram(self.attribute_dict, label, var_list, **kwargs)
def plot_random_var(self, var_list=[], **kwargs): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. **kwargs : optional Additional key word arguments can be passed to change the numpy.histogram (e.g. density=True, bins=11, ...) Returns ------- grid_plot : bokeh row A row with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> elm = srs.st_bearing_example() >>> elm.plot_random_var(["kxx"]) # doctest: +ELLIPSIS Row... """ label = dict( kxx="Direct stiffness in the X direction", kxy="Cross coupled stiffness in the X direction", kyx="Cross coupled stiffness in the Y direction", kyy="Direct stiffness in the Y direction", cxx="Direct damping in the X direction", cxy="Cross coupled damping in the X direction", cyx="Cross coupled damping in the Y direction", cyy="Direct damping in the y direction", ) if not all(var in self.is_random for var in var_list): raise ValueError( "Not random variable in var_list. Select variables from {}". format(self.is_random)) return plot_histogram(self.attribute_dict, label, var_list, **kwargs)
def plot_random_var(self, var_list=[], **kwargs): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. **kwargs : optional Additional key word arguments can be passed to change the numpy.histogram (e.g. density=True, bins=11, ...) Returns ------- grid_plot : bokeh row A row with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> E = np.random.uniform(208e9, 211e9, 5) >>> st_steel = ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9) >>> st_steel.plot_random_var(["E"]) # doctest: +ELLIPSIS Row... """ label = dict( E="Young's Modulus", G_s="Shear Modulus", Poisson="Poisson coefficient", rho="density", ) is_random = self.is_random if not all(var in self.is_random for var in var_list): raise ValueError( "Not random variable in var_list. Select variables from {}". format(is_random)) return plot_histogram(self.attribute_dict, label, var_list, **kwargs)
def plot_random_var(self, var_list=[], **kwargs): """Plot histogram and the PDF. This function creates a histogram to display the random variable distribution. Parameters ---------- var_list : list, optional List of random variables, in string format, to plot. **kwargs : optional Additional key word arguments can be passed to change the numpy.histogram (e.g. density=True, bins=11, ...) Returns ------- grid_plot : bokeh row A row with the histogram plots. Examples -------- >>> import ross.stochastic as srs >>> elm = srs.st_disk_example() >>> elm.plot_random_var(["Id"]) # doctest: +ELLIPSIS Row... """ label = dict( m="Mass", Id="Diametral moment of inertia", Ip="Polar moment of inertia", ) if not all(var in self.is_random for var in var_list): raise ValueError( "Not random variable in var_list. Select variables from {}". format(self.is_random)) return plot_histogram(self.attribute_dict, label, var_list, **kwargs)