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)
