def _ystrings(ynames, ylabel, yunit, legends):
"""Generate a y-axis label and set of legend entries.
"""
if ynames:
if ylabel is None: # Try to create a suitable axis label.
descriptions = self.get_description(ynames)
# If the descriptions are the same, label the y axis with
# the 1st one.
ylabel = descriptions[0]
if len(set(descriptions)) <> 1:
print("The y-axis variable descriptions are not all "
"the same. The first has been used. Please "
"provide the proper name via ylabel1 or ylabel2.")
if legends == []:
legends = ynames
if incl_prefix:
legends = [self.fbase + ': ' + leg for leg in legends]
if suffix:
legends = ([leg + ' (%s)' % suffix for leg in legends]
if use_paren else
[leg + suffix for leg in legends])
assert len(set(self.get_dimension(ynames))) == 1, \
"The variables on the y-axis do not have the same physical dimension."
if yunit is None:
# Use the unit of the 1st variable.
yunit = self.get_unit(ynames[0])
if ylabel <> "":
ylabel = label_number(ylabel, yunit)
return ylabel, yunit, legends
def _ystrings(ynames, ylabel, yunit, legends):
"""Generate a y-axis label and set of legend entries.
"""
if ynames:
if ylabel is None: # Try to create a suitable axis label.
descriptions = self.get_description(ynames)
# If the descriptions are the same, label the y axis with
# the 1st one.
ylabel = descriptions[0]
if len(set(descriptions)) <> 1:
print(
"The y-axis variable descriptions are not all "
"the same. The first has been used. Please "
"provide the proper name via ylabel1 or ylabel2.")
if legends == []:
legends = ynames
if incl_prefix:
legends = [self.fbase + ': ' + leg for leg in legends]
if suffix:
legends = ([leg + ' (%s)' % suffix
for leg in legends] if use_paren else
[leg + suffix for leg in legends])
assert len(set(self.get_dimension(ynames))) == 1, \
"The variables on the y-axis do not have the same physical dimension."
if yunit is None:
# Use the unit of the 1st variable.
yunit = self.get_unit(ynames[0])
if ylabel <> "":
ylabel = label_number(ylabel, yunit)
return ylabel, yunit, legends
def currdenfig(self, title=None, times=[0], z_index=0, leg_kwargs={},
**kwargs):
"""Plot current densities of the cell segments at times.
**Arguments:**
- *title*: Title for the figure
- *times*: List of times at which the data should be sampled
If multiple times are given, then subfigures will be generated.
- *z_index*: z-index at which the current densities are taken
- *leg_kwargs*: Dictionary of keyword arguments for
:meth:`matplotlib.pyplot.legend`
If *leg_kwargs* is *None*, then no legend will be shown.
- *\*\*kwargs*: Additional arguments for :meth:`barfig`
"""
# Process the arguments.
xlabel = kwargs.pop('xlabel', 'y-axis index (inlet to outlet)')
name_template = self.cell + ('iprimeprime_seg[%i, ' + '%i]'
% (z_index+1))
#description = self.get_description(name_template % 1)
#unit = self.get_unit(name_template % 1)
unit = self.get_unit(name_template % 1)
#ylabel = kwargs.pop('ylabel', label_number(description, unit))
ylabel = kwargs.pop('ylabel', label_number("Current density", unit))
# Create the plot.
ax = self.barfig(names=[name_template % (i_y+1) for i_y in range(1)],
times=times, xlabel=xlabel, ylabel=ylabel,
leg_kwargs=None, **kwargs)
for a, time in zip(ax, times):
a.axhline(self.get_values('cell.iprimeprime', time),
linestyle='--', color='k', label='Entire cell')
# Decorate.
if title is None:
if self.n_z == 1:
plt.title("Current Distribution of Cell Segments")
else:
plt.title("Current Distribution of Cell Segments\n"
"z-axis index %i (of %i)" % (z_index+1, self.n_z))
if leg_kwargs is not None:
loc = leg_kwargs.pop('loc', 'best')
if len(ax) == 1:
ax[0].legend(loc=loc, **leg_kwargs)
else:
plt.figlegend(ax[0].lines, **leg_kwargs)
def plot(self, ynames1=[], ylabel1=None, yunit1=None, legends1=[],
leg1_kwargs={'loc': 'best'}, ax1=None,
ynames2=[], ylabel2=None, yunit2=None, legends2=[],
leg2_kwargs={'loc': 'best'}, ax2=None,
xname='Time', xlabel=None, xunit=None,
title=None, label="xy", incl_prefix=False, suffix=None,
use_paren=True, **kwargs):
r"""Plot data as points and/or curves in 2D Cartesian coordinates.
A new figure is created if necessary.
**Arguments:**
- *ynames1*: Names of variables for the primary y axis
If any names are invalid, then they will be skipped.
- *ylabel1*: Label for the primary y axis
If *ylabel1* is *None* (default) and all of the variables have the
same Modelica_ description string, then the common description
will be used. Use '' for no label.
- *yunit1*: String indicating the unit for the primary y-axis (see note
for *xunit*)
If *yunit1* is *None*, the Modelica_ *displayUnit* of the first
entry of *ynames1* or the default unit (from *fcres.ini*) based on
that variable's dimension will be used (in decreasing priority).
.. Note:: Dimension checking is not currently performed, so it is
important to ensure that a proper unit is chosen.
- *legends1*: List of legend entries for variables assigned to the
primary y axis
If *legends1* is an empty list ([]), ynames1 will be used. If
*legends1* is *None* and all of the variables on the primary axis
have the same unit, then no legend will be shown.
- *leg1_kwargs*: Dictionary of keyword arguments for the primary legend
- *ax1*: Primary y axes
If *ax1* is not provided, then axes will be created in a new
figure.
- *ynames2*, *ylabel2*, *yunit2*, *legends2*, *leg2_kwargs*, and *ax2*:
Similar to *ynames1*, *ylabel1*, *yunit1*, *legends1*, *leg1_kwargs*,
and *ax1* but for the secondary y axis
- *xname*: Name of the x-axis data
- *xlabel*: Label for the x axis
If *xlabel* is *None* (default), the variable's Modelica_
description string will be applied. Use '' for no label.
- *xunit*: String indicating the unit for the x axis (see note
for *yunit1*)
If *xunit* is *None*, the Modelica_ variable's *displayUnit* or
the default unit (from *fcres.ini*) based on the variable's
dimension will be used (in decreasing priority).
- *title*: Title for the figure
If *title* is *None* (default), then the title will be the base
filename. Use '' for no title.
- *label*: Label for the figure (ignored if ax is provided)
This will be used as a base filename if the figure is saved.
- *incl_prefix*: If *True*, prefix the legend strings with the base
filename of the class.
- *suffix*: String that will be added at the end of the legend entries
- *use_paren*: Add parentheses around the suffix
- *\*\*kwargs*: Additional arguments for :meth:`base.plot` (and thus to
:meth:`matplotlib.pyplot.plot`)
If both y axes are used (primary and secondary), then the *dashes*
argument is ignored. The curves on the primary axis will be solid
and the curves on the secondary axis will be dotted.
**Returns:**
1. *ax1*: Primary y axes
2. *ax2*: Secondary y axes
**Example:**
.. testsetup::
>>> from fcres import closeall
>>> closeall()
.. code-block:: python
>>> from fcres import SimRes, saveall
>>> sim = SimRes('examples/SaturationPressure')
>>> sim.plot(xname="subregion.gas.H2O.T",
... ynames1=["subregion.gas.H2O.p", "p_sat"],
... legends1=["FCSys (from Gibbs equilibrium)",
... "Modelica.Media (correlated function)"],
... ylabel1='Saturation pressure',
... title="Water Saturation Pressure",
... label='examples/SaturationPressure') # doctest: +ELLIPSIS
(<matplotlib.axes._subplots.AxesSubplot object at 0x...>, None)
>>> saveall()
Saved examples/SaturationPressure.pdf
Saved examples/SaturationPressure.png
.. only:: html
.. image:: ../examples/SaturationPressure.png
:scale: 70 %
:alt: plot of water saturation pressure
.. only:: latex
.. figure:: ../examples/SaturationPressure.pdf
:scale: 70 %
Plot of water saturation pressure
"""
# Note: ynames1 is the first argument (besides self) so that plot()
# can be called with simply a variable name.
def _ystrings(ynames, ylabel, yunit, legends):
"""Generate a y-axis label and set of legend entries.
"""
if ynames:
if ylabel is None: # Try to create a suitable axis label.
descriptions = self.get_description(ynames)
# If the descriptions are the same, label the y axis with
# the 1st one.
ylabel = descriptions[0]
if len(set(descriptions)) <> 1:
print("The y-axis variable descriptions are not all "
"the same. The first has been used. Please "
"provide the proper name via ylabel1 or ylabel2.")
if legends == []:
legends = ynames
if incl_prefix:
legends = [self.fbase + ': ' + leg for leg in legends]
if suffix:
legends = ([leg + ' (%s)' % suffix for leg in legends]
if use_paren else
[leg + suffix for leg in legends])
assert len(set(self.get_dimension(ynames))) == 1, \
"The variables on the y-axis do not have the same physical dimension."
if yunit is None:
# Use the unit of the 1st variable.
yunit = self.get_unit(ynames[0])
if ylabel <> "":
ylabel = label_number(ylabel, yunit)
return ylabel, yunit, legends
# Process the inputs.
ynames1 = base.flatten_list(ynames1)
ynames2 = base.flatten_list(ynames2)
assert ynames1 or ynames2, "No signals were provided."
if title is None:
title = self.fbase
# Create primary and secondary axes if necessary.
if not ax1:
fig = base.figure(label)
ax1 = fig.add_subplot(111)
if ynames2 and not ax2:
ax2 = ax1.twinx()
# Generate the x-axis label.
if xlabel is None:
xlabel = 'Time' if xname == 'Time' else self.get_description(xname)
# With Dymola 7.4, the description of the time variable will be
# "Time in", which isn't good.
if xunit is None:
xunit = self.get_unit(xname)
if xlabel<> "":
xlabel = label_number(xlabel, xunit)
# Generate the y-axis labels and sets of legend entries.
ylabel1, yunit1, legends1 = _ystrings(ynames1, ylabel1, yunit1, legends1)
ylabel2, yunit2, legends2 = _ystrings(ynames2, ylabel2, yunit2, legends2)
# Read the data.
if xname == 'Time':
t_scale = lambda t: t*self._unitvalue('s')/self._unitvalue(xunit)
y_1 = self.get_values(ynames1, f=self.to_unit(yunit1))
y_2 = self.get_values(ynames2, f=self.to_unit(yunit2))
else:
x = self.get_values(xname, f=self.to_unit(xunit))
times = self.get_times(xname)
y_1 = self.get_values_at_times(ynames1, times, f=self.to_unit(yunit1))
y_2 = self.get_values_at_times(ynames2, times, f=self.to_unit(yunit2))
# Plot the data.
if ynames1:
if ynames2:
# Use solid lines for primary axis and dotted lines for
# secondary.
kwargs['dashes'] = [(None, None)]
base.plot(y_1, self.get_times(ynames1, f=t_scale) if xname == 'Time'
else x, ax1, label=legends1, **kwargs)
kwargs['dashes'] = [(3, 3)]
base.plot(y_2, self.get_times(ynames2, f=t_scale) if xname == 'Time'
else x, ax2, label=legends2, **kwargs)
else:
base.plot(y_1, self.get_times(ynames1, f=t_scale) if xname == 'Time'
else x, ax1, label=legends1, **kwargs)
elif ynames2:
base.plot(y_2, self.get_times(ynames2, f=t_scale) if xname == 'Time'
else x, ax2, label=legends2, **kwargs)
# Decorate the figure.
ax1.set_title(title)
ax1.set_xlabel(xlabel)
if ylabel1:
ax1.set_ylabel(ylabel1)
if ylabel2:
ax2.set_ylabel(ylabel2)
if legends1:
if legends2:
# Put the primary legend in the upper left and secondary in
# upper right.
leg1_kwargs['loc'] = 2
leg2_kwargs['loc'] = 1
ax1.legend(**leg1_kwargs)
ax2.legend(**leg2_kwargs)
else:
ax1.legend(**leg1_kwargs)
elif legends2:
ax2.legend(**leg2_kwargs)
return ax1, ax2
def currdenfig(self,
title=None,
times=[0],
z_index=0,
leg_kwargs={},
**kwargs):
"""Plot current densities of the cell segments at times.
**Arguments:**
- *title*: Title for the figure
- *times*: List of times at which the data should be sampled
If multiple times are given, then subfigures will be generated.
- *z_index*: z-index at which the current densities are taken
- *leg_kwargs*: Dictionary of keyword arguments for
:meth:`matplotlib.pyplot.legend`
If *leg_kwargs* is *None*, then no legend will be shown.
- *\*\*kwargs*: Additional arguments for :meth:`barfig`
"""
# Process the arguments.
xlabel = kwargs.pop('xlabel', 'y-axis index (inlet to outlet)')
name_template = self.cell + ('iprimeprime_seg[%i, ' + '%i]' %
(z_index + 1))
#description = self.get_description(name_template % 1)
#unit = self.get_unit(name_template % 1)
unit = self.get_unit(name_template % 1)
#ylabel = kwargs.pop('ylabel', label_number(description, unit))
ylabel = kwargs.pop('ylabel', label_number("Current density", unit))
# Create the plot.
ax = self.barfig(names=[name_template % (i_y + 1) for i_y in range(1)],
times=times,
xlabel=xlabel,
ylabel=ylabel,
leg_kwargs=None,
**kwargs)
for a, time in zip(ax, times):
a.axhline(self.get_values('cell.iprimeprime', time),
linestyle='--',
color='k',
label='Entire cell')
# Decorate.
if title is None:
if self.n_z == 1:
plt.title("Current Distribution of Cell Segments")
else:
plt.title("Current Distribution of Cell Segments\n"
"z-axis index %i (of %i)" % (z_index + 1, self.n_z))
if leg_kwargs is not None:
loc = leg_kwargs.pop('loc', 'best')
if len(ax) == 1:
ax[0].legend(loc=loc, **leg_kwargs)
else:
plt.figlegend(ax[0].lines, **leg_kwargs)
def colorfig(self,
suffix,
times=[0],
n_rows=1,
title="",
subtitles=[],
label="color",
slice_axis='z',
slice_index=0,
xlabel="",
xticklabels=[],
xticks=[],
ylabel="",
yticklabels=[],
yticks=[],
clabel="",
cbar_orientation='vertical',
margin_left=rcParams['figure.subplot.left'],
margin_right=1 - rcParams['figure.subplot.right'],
margin_bottom=rcParams['figure.subplot.bottom'],
margin_top=1 - rcParams['figure.subplot.top'],
margin_cbar=0.2,
wspace=0.1,
hspace=0.25,
cbar_space=0.1,
cbar_width=0.05,
**kwargs):
"""Create a figure with 2D scalar data at given time(s) on a color axis
in 2D Cartesian coordinates.
**Arguments:**
- *suffix*: Name of the variable to be plotted (relative to the names
of the subregions)
- *times*: List of times at which the data should be sampled
If multiple times are given, then subfigures will be generated.
- *n_rows*: Number of rows of (sub)plots
- *title*: Title for the figure
- *subtitles*: List of subtitles (i.e., titles for each subplot)
If not provided, "t = xx s" will be used, where xx is the time of
each entry. "(initial)" or "(final)" are appended if appropriate.
- *label*: Label for the figure
This will be used as a base filename if the figure is saved.
- *slice_axis*: Axis normal to the screen or page ('x', 'y', or 'z')
- *slice_index*: Position along slice_axis
- *xlabel*: Label for the x-axes (only shown for the subplots on the
bottom row)
- *xticklabels*: Labels for the x-axis ticks (only shown for the
subplots on the bottom row)
- *xticks*: Positions of the x-axis ticks
- *ylabel*: Label for the y axis (only shown for the subplots on the
left column)
- *yticklabels*: Labels for the y-axis ticks (only shown for the
subplots on the left column)
- *yticks*: Positions of the y-axis ticks
- *clabel*: Label for the color- or c-bar axis
- *cbar_orientation*: Orientation of the colorbar ("vertical" or
"horizontal")
- *margin_left*: Left margin
- *margin_right*: Right margin (ignored if ``cbar_orientation ==
'vertical'``)
- *margin_bottom*: Bottom margin (ignored if ``cbar_orientation ==
'horizontal'``)
- *margin_top*: Top margin
- *margin_cbar*: Margin reserved for the colorbar (right margin if
``cbar_orientation == 'vertical'`` and bottom margin if
``cbar_orientation == 'horizontal'``)
- *wspace*: The amount of width reserved for blank space between
subplots
- *hspace*: The amount of height reserved for white space between
subplots
- *cbar_space*: Space between the subplot rectangles and the colorbar
- *cbar_width*: Width of the colorbar if vertical (or height if
horizontal)
- *\*\*kwargs*: Additional arguments for :meth:`modelicares.base.color`
"""
# The procedure for coordinating the images with a single colorbar was
# copied and modified from
# http://matplotlib.sourceforge.net/examples/pylab_examples/multi_image.html,
# accessed 11/8/10.
# 5/26/11: TODO: This method needs to be updated. Use quiverfig() as a
# reference.
from res import color
# Get the data.
n_plots = len(times)
if slice_axis == 'x':
names = presuffix(self.subregions[slice_index], suffix=suffix)
elif slice_axis == 'y':
names = presuffix(self.subregions[:][slice_index], suffix=suffix)
else:
names = presuffix(self.subregions[:][:][slice_index],
suffix=suffix)
c = self.get_values_at_times(names, times)
# Cast the data into a list of matrices (one at each sample time).
if slice_axis == 'x':
c = [
np.array([[
c[i_y + self.n_y * i_z][i]
for i_y in range(self.n_y - 1, -1, -1)
] for i_z in range(self.n_z)]) for i in range(n_plots)
]
elif slice_axis == 'y':
c = [
np.array([[
c[i_z + self.n_z * i_x][i]
for i_z in range(self.n_z - 1, -1, -1)
] for i_x in range(self.n_x)]) for i in range(n_plots)
]
else:
c = [
np.array([[
c[i_y + self.n_y * i_x][i]
for i_z in range(self.n_y - 1, -1, -1)
] for i_x in range(self.n_x)]) for i in range(n_plots)
]
[start_time, stop_time] = self.get_times('Time', [0, -1])
# Generate xlabel, xticks, and xticklabels.
if not xlabel:
if slice_axis == 'x':
xlabel = 'z-axis index'
elif slice_axis == 'y':
xlabel = 'x-axis index'
elif slice_axis == 'z':
xlabel = 'y-axis index'
if not xticklabels:
if slice_axis == 'x':
xticklabels = [str(i + 1) for i in range(self.n_z)]
elif slice_axis == 'y':
xticklabels = [str(i + 1) for i in range(self.n_x)]
else:
xticklabels = [str(i + 1) for i in range(self.n_x)]
if not xticks:
if slice_axis == 'x':
xticks = range(self.n_z)
elif slice_axis == 'y':
xticks = range(self.n_x)
else:
xticks = range(self.n_x)
# Generate ylabel, yticks, and yticklabels.
if not ylabel:
if slice_axis == 'x':
ylabel = 'y-axis index'
elif slice_axis == 'y':
ylabel = 'z-axis index'
else:
ylabel = 'x-axis index'
if not yticklabels:
if slice_axis == 'x':
yticklabels = [str(i + 1) for i in range(self.n_y)]
elif slice_axis == 'y':
yticklabels = [str(i + 1) for i in range(self.n_z)]
else:
yticklabels = [str(i + 1) for i in range(self.n_y)]
if not yticks:
if slice_axis == 'x':
yticks = range(self.n_y)
elif slice_axis == 'y':
yticks = range(self.n_z)
else:
yticks = range(self.n_y)
# Generate clabel.
if not clabel:
clabels = self.get_description(names)
# If all of the descriptions are the same, use the first one.
if len(set(clabels)) == 1:
clabel = clabels[0]
else:
clabel = "Value"
#units = self.get_unit(names)
units = self.get_unit(names)
if len(set(units)) == 1:
clabel += label_number("", units[0])
else:
raise UserWarning(
"The variables have inconsistent units. The "
"colorbar unit will not match the units of all of the "
"variables.")
# Set up the subplots.
if not subtitles:
#unit = unit2tex(self.get_unit('Time'))
unit = unit2tex(self.get_unit('Time'))
subtitles = [
"t = " + label_quantity(times[i], unit) for i in n_plots
]
for i, time in enumerate(times):
if time == start_time:
subtitle += " (initial)"
elif time == stop_time:
subtitle += " (final)"
ax, cax = setup_subplots(n_plots=n_plots,
n_rows=n_rows,
title=title,
subtitles=subtitles,
label=label,
xlabel=xlabel,
xticklabels=xticklabels,
xticks=xticks,
ylabel=ylabel,
yticklabels=yticklabels,
yticks=yticks,
ctype=cbar_orientation,
clabel=clabel,
margin_left=margin_left,
margin_right=margin_right,
margin_bottom=margin_bottom,
margin_top=margin_top,
margin_cbar=margin_cbar,
wspace=wspace,
hspace=hspace,
cbar_space=cbar_space,
cbar_width=cbar_width)
# Create the plots.
profiles = []
c_min = np.inf
c_max = -np.inf
for i, time in enumerate(times):
profiles.append(color(ax[i], c[i], **kwargs))
# Find the minimum and maximum of the color-axis data.
c_min = min(c_min, np.amin(c[i]))
c_max = max(c_max, np.amax(c[i]))
# Set the first image as the master, with all the others observing it
# for changes in norm.
class ImageFollower:
"""Update image in response to changes in clim on another image.
"""
def __init__(self, follower):
self.follower = follower
def __call__(self, leader):
self.follower.set_clim(leader.get_clim())
norm = Normalize(c_min=c_min, c_max=c_max)
for i, profile in enumerate(profiles):
profile.set_norm(norm)
if i > 0:
profiles[0].callbacksSM.connect('changed',
ImageFollower(profile))
# Add the colorbar. (It is also based on the master image.)
cbar = fig.colorbar(images[0], cax, orientation=cbar_orientation)
# Scale the colorbar.
if c_min == c_max:
yticks = [c_min]
for i in range(len(cbar.ax.get_yticks()) - 1):
yticks.append(None)
cbar.set_ticks(yticks)
def colorfig(self, suffix, times=[0], n_rows=1, title="", subtitles=[],
label="color", slice_axis='z', slice_index=0,
xlabel="", xticklabels=[], xticks=[],
ylabel="", yticklabels=[], yticks=[],
clabel="", cbar_orientation='vertical',
margin_left=rcParams['figure.subplot.left'],
margin_right=1-rcParams['figure.subplot.right'],
margin_bottom=rcParams['figure.subplot.bottom'],
margin_top=1-rcParams['figure.subplot.top'],
margin_cbar=0.2,
wspace=0.1, hspace=0.25,
cbar_space=0.1, cbar_width=0.05,
**kwargs):
"""Create a figure with 2D scalar data at given time(s) on a color axis
in 2D Cartesian coordinates.
**Arguments:**
- *suffix*: Name of the variable to be plotted (relative to the names
of the subregions)
- *times*: List of times at which the data should be sampled
If multiple times are given, then subfigures will be generated.
- *n_rows*: Number of rows of (sub)plots
- *title*: Title for the figure
- *subtitles*: List of subtitles (i.e., titles for each subplot)
If not provided, "t = xx s" will be used, where xx is the time of
each entry. "(initial)" or "(final)" are appended if appropriate.
- *label*: Label for the figure
This will be used as a base filename if the figure is saved.
- *slice_axis*: Axis normal to the screen or page ('x', 'y', or 'z')
- *slice_index*: Position along slice_axis
- *xlabel*: Label for the x-axes (only shown for the subplots on the
bottom row)
- *xticklabels*: Labels for the x-axis ticks (only shown for the
subplots on the bottom row)
- *xticks*: Positions of the x-axis ticks
- *ylabel*: Label for the y axis (only shown for the subplots on the
left column)
- *yticklabels*: Labels for the y-axis ticks (only shown for the
subplots on the left column)
- *yticks*: Positions of the y-axis ticks
- *clabel*: Label for the color- or c-bar axis
- *cbar_orientation*: Orientation of the colorbar ("vertical" or
"horizontal")
- *margin_left*: Left margin
- *margin_right*: Right margin (ignored if ``cbar_orientation ==
'vertical'``)
- *margin_bottom*: Bottom margin (ignored if ``cbar_orientation ==
'horizontal'``)
- *margin_top*: Top margin
- *margin_cbar*: Margin reserved for the colorbar (right margin if
``cbar_orientation == 'vertical'`` and bottom margin if
``cbar_orientation == 'horizontal'``)
- *wspace*: The amount of width reserved for blank space between
subplots
- *hspace*: The amount of height reserved for white space between
subplots
- *cbar_space*: Space between the subplot rectangles and the colorbar
- *cbar_width*: Width of the colorbar if vertical (or height if
horizontal)
- *\*\*kwargs*: Additional arguments for :meth:`modelicares.base.color`
"""
# The procedure for coordinating the images with a single colorbar was
# copied and modified from
# http://matplotlib.sourceforge.net/examples/pylab_examples/multi_image.html,
# accessed 11/8/10.
# 5/26/11: TODO: This method needs to be updated. Use quiverfig() as a
# reference.
from res import color
# Get the data.
n_plots = len(times)
if slice_axis == 'x':
names = presuffix(self.subregions[slice_index], suffix=suffix)
elif slice_axis == 'y':
names = presuffix(self.subregions[:][slice_index], suffix=suffix)
else:
names = presuffix(self.subregions[:][:][slice_index],
suffix=suffix)
c = self.get_values_at_times(names, times)
# Cast the data into a list of matrices (one at each sample time).
if slice_axis == 'x':
c = [np.array([[c[i_y + self.n_y*i_z][i]
for i_y in range(self.n_y-1,-1,-1)]
for i_z in range(self.n_z)]) for i in range(n_plots)]
elif slice_axis == 'y':
c = [np.array([[c[i_z + self.n_z*i_x][i]
for i_z in range(self.n_z-1,-1,-1)]
for i_x in range(self.n_x)]) for i in range(n_plots)]
else:
c = [np.array([[c[i_y + self.n_y*i_x][i]
for i_z in range(self.n_y-1,-1,-1)]
for i_x in range(self.n_x)]) for i in range(n_plots)]
[start_time, stop_time] = self.get_times('Time', [0,-1])
# Generate xlabel, xticks, and xticklabels.
if not xlabel:
if slice_axis == 'x':
xlabel = 'z-axis index'
elif slice_axis == 'y':
xlabel = 'x-axis index'
elif slice_axis == 'z':
xlabel = 'y-axis index'
if not xticklabels:
if slice_axis == 'x':
xticklabels = [str(i+1) for i in range(self.n_z)]
elif slice_axis == 'y':
xticklabels = [str(i+1) for i in range(self.n_x)]
else:
xticklabels = [str(i+1) for i in range(self.n_x)]
if not xticks:
if slice_axis == 'x':
xticks = range(self.n_z)
elif slice_axis == 'y':
xticks = range(self.n_x)
else:
xticks = range(self.n_x)
# Generate ylabel, yticks, and yticklabels.
if not ylabel:
if slice_axis == 'x':
ylabel = 'y-axis index'
elif slice_axis == 'y':
ylabel = 'z-axis index'
else:
ylabel = 'x-axis index'
if not yticklabels:
if slice_axis == 'x':
yticklabels = [str(i+1) for i in range(self.n_y)]
elif slice_axis == 'y':
yticklabels = [str(i+1) for i in range(self.n_z)]
else:
yticklabels = [str(i+1) for i in range(self.n_y)]
if not yticks:
if slice_axis == 'x':
yticks = range(self.n_y)
elif slice_axis == 'y':
yticks = range(self.n_z)
else:
yticks = range(self.n_y)
# Generate clabel.
if not clabel:
clabels = self.get_description(names)
# If all of the descriptions are the same, use the first one.
if len(set(clabels)) == 1:
clabel = clabels[0]
else:
clabel = "Value"
#units = self.get_unit(names)
units = self.get_unit(names)
if len(set(units)) == 1:
clabel += label_number("", units[0])
else:
raise UserWarning("The variables have inconsistent units. The "
"colorbar unit will not match the units of all of the "
"variables.")
# Set up the subplots.
if not subtitles:
#unit = unit2tex(self.get_unit('Time'))
unit = unit2tex(self.get_unit('Time'))
subtitles = ["t = " + label_quantity(times[i], unit)
for i in n_plots]
for i, time in enumerate(times):
if time == start_time:
subtitle += " (initial)"
elif time == stop_time:
subtitle += " (final)"
ax, cax = setup_subplots(n_plots=n_plots, n_rows=n_rows,
title=title, subtitles=subtitles, label=label,
xlabel=xlabel, xticklabels=xticklabels, xticks=xticks,
ylabel=ylabel, yticklabels=yticklabels, yticks=yticks,
ctype=cbar_orientation, clabel=clabel,
margin_left=margin_left, margin_right=margin_right,
margin_bottom=margin_bottom, margin_top=margin_top,
margin_cbar=margin_cbar, wspace=wspace, hspace=hspace,
cbar_space=cbar_space, cbar_width=cbar_width)
# Create the plots.
profiles = []
c_min = np.inf
c_max = -np.inf
for i, time in enumerate(times):
profiles.append(color(ax[i], c[i], **kwargs))
# Find the minimum and maximum of the color-axis data.
c_min = min(c_min, np.amin(c[i]))
c_max = max(c_max, np.amax(c[i]))
# Set the first image as the master, with all the others observing it
# for changes in norm.
class ImageFollower:
"""Update image in response to changes in clim on another image.
"""
def __init__(self, follower):
self.follower = follower
def __call__(self, leader):
self.follower.set_clim(leader.get_clim())
norm = Normalize(c_min=c_min, c_max=c_max)
for i, profile in enumerate(profiles):
profile.set_norm(norm)
if i > 0:
profiles[0].callbacksSM.connect('changed',
ImageFollower(profile))
# Add the colorbar. (It is also based on the master image.)
cbar = fig.colorbar(images[0], cax, orientation=cbar_orientation)
# Scale the colorbar.
if c_min == c_max:
yticks = [c_min]
for i in range(len(cbar.ax.get_yticks()) - 1):
yticks.append(None)
cbar.set_ticks(yticks)
def plot(self,
ynames1=[],
ylabel1=None,
yunit1=None,
legends1=[],
leg1_kwargs={'loc': 'best'},
ax1=None,
ynames2=[],
ylabel2=None,
yunit2=None,
legends2=[],
leg2_kwargs={'loc': 'best'},
ax2=None,
xname='Time',
xlabel=None,
xunit=None,
title=None,
label="xy",
incl_prefix=False,
suffix=None,
use_paren=True,
**kwargs):
r"""Plot data as points and/or curves in 2D Cartesian coordinates.
A new figure is created if necessary.
**Arguments:**
- *ynames1*: Names of variables for the primary y axis
If any names are invalid, then they will be skipped.
- *ylabel1*: Label for the primary y axis
If *ylabel1* is *None* (default) and all of the variables have the
same Modelica_ description string, then the common description
will be used. Use '' for no label.
- *yunit1*: String indicating the unit for the primary y-axis (see note
for *xunit*)
If *yunit1* is *None*, the Modelica_ *displayUnit* of the first
entry of *ynames1* or the default unit (from *fcres.ini*) based on
that variable's dimension will be used (in decreasing priority).
.. Note:: Dimension checking is not currently performed, so it is
important to ensure that a proper unit is chosen.
- *legends1*: List of legend entries for variables assigned to the
primary y axis
If *legends1* is an empty list ([]), ynames1 will be used. If
*legends1* is *None* and all of the variables on the primary axis
have the same unit, then no legend will be shown.
- *leg1_kwargs*: Dictionary of keyword arguments for the primary legend
- *ax1*: Primary y axes
If *ax1* is not provided, then axes will be created in a new
figure.
- *ynames2*, *ylabel2*, *yunit2*, *legends2*, *leg2_kwargs*, and *ax2*:
Similar to *ynames1*, *ylabel1*, *yunit1*, *legends1*, *leg1_kwargs*,
and *ax1* but for the secondary y axis
- *xname*: Name of the x-axis data
- *xlabel*: Label for the x axis
If *xlabel* is *None* (default), the variable's Modelica_
description string will be applied. Use '' for no label.
- *xunit*: String indicating the unit for the x axis (see note
for *yunit1*)
If *xunit* is *None*, the Modelica_ variable's *displayUnit* or
the default unit (from *fcres.ini*) based on the variable's
dimension will be used (in decreasing priority).
- *title*: Title for the figure
If *title* is *None* (default), then the title will be the base
filename. Use '' for no title.
- *label*: Label for the figure (ignored if ax is provided)
This will be used as a base filename if the figure is saved.
- *incl_prefix*: If *True*, prefix the legend strings with the base
filename of the class.
- *suffix*: String that will be added at the end of the legend entries
- *use_paren*: Add parentheses around the suffix
- *\*\*kwargs*: Additional arguments for :meth:`base.plot` (and thus to
:meth:`matplotlib.pyplot.plot`)
If both y axes are used (primary and secondary), then the *dashes*
argument is ignored. The curves on the primary axis will be solid
and the curves on the secondary axis will be dotted.
**Returns:**
1. *ax1*: Primary y axes
2. *ax2*: Secondary y axes
**Example:**
.. testsetup::
>>> from fcres import closeall
>>> closeall()
.. code-block:: python
>>> from fcres import SimRes, saveall
>>> sim = SimRes('examples/SaturationPressure')
>>> sim.plot(xname="subregion.gas.H2O.T",
... ynames1=["subregion.gas.H2O.p", "p_sat"],
... legends1=["FCSys (from Gibbs equilibrium)",
... "Modelica.Media (correlated function)"],
... ylabel1='Saturation pressure',
... title="Water Saturation Pressure",
... label='examples/SaturationPressure') # doctest: +ELLIPSIS
(<matplotlib.axes._subplots.AxesSubplot object at 0x...>, None)
>>> saveall()
Saved examples/SaturationPressure.pdf
Saved examples/SaturationPressure.png
.. only:: html
.. image:: ../examples/SaturationPressure.png
:scale: 70 %
:alt: plot of water saturation pressure
.. only:: latex
.. figure:: ../examples/SaturationPressure.pdf
:scale: 70 %
Plot of water saturation pressure
"""
# Note: ynames1 is the first argument (besides self) so that plot()
# can be called with simply a variable name.
def _ystrings(ynames, ylabel, yunit, legends):
"""Generate a y-axis label and set of legend entries.
"""
if ynames:
if ylabel is None: # Try to create a suitable axis label.
descriptions = self.get_description(ynames)
# If the descriptions are the same, label the y axis with
# the 1st one.
ylabel = descriptions[0]
if len(set(descriptions)) <> 1:
print(
"The y-axis variable descriptions are not all "
"the same. The first has been used. Please "
"provide the proper name via ylabel1 or ylabel2.")
if legends == []:
legends = ynames
if incl_prefix:
legends = [self.fbase + ': ' + leg for leg in legends]
if suffix:
legends = ([leg + ' (%s)' % suffix
for leg in legends] if use_paren else
[leg + suffix for leg in legends])
assert len(set(self.get_dimension(ynames))) == 1, \
"The variables on the y-axis do not have the same physical dimension."
if yunit is None:
# Use the unit of the 1st variable.
yunit = self.get_unit(ynames[0])
if ylabel <> "":
ylabel = label_number(ylabel, yunit)
return ylabel, yunit, legends
# Process the inputs.
ynames1 = base.flatten_list(ynames1)
ynames2 = base.flatten_list(ynames2)
assert ynames1 or ynames2, "No signals were provided."
if title is None:
title = self.fbase
# Create primary and secondary axes if necessary.
if not ax1:
fig = base.figure(label)
ax1 = fig.add_subplot(111)
if ynames2 and not ax2:
ax2 = ax1.twinx()
# Generate the x-axis label.
if xlabel is None:
xlabel = 'Time' if xname == 'Time' else self.get_description(xname)
# With Dymola 7.4, the description of the time variable will be
# "Time in", which isn't good.
if xunit is None:
xunit = self.get_unit(xname)
if xlabel <> "":
xlabel = label_number(xlabel, xunit)
# Generate the y-axis labels and sets of legend entries.
ylabel1, yunit1, legends1 = _ystrings(ynames1, ylabel1, yunit1,
legends1)
ylabel2, yunit2, legends2 = _ystrings(ynames2, ylabel2, yunit2,
legends2)
# Read the data.
if xname == 'Time':
t_scale = lambda t: t * self._unitvalue('s') / self._unitvalue(
xunit)
y_1 = self.get_values(ynames1, f=self.to_unit(yunit1))
y_2 = self.get_values(ynames2, f=self.to_unit(yunit2))
else:
x = self.get_values(xname, f=self.to_unit(xunit))
times = self.get_times(xname)
y_1 = self.get_values_at_times(ynames1,
times,
f=self.to_unit(yunit1))
y_2 = self.get_values_at_times(ynames2,
times,
f=self.to_unit(yunit2))
# Plot the data.
if ynames1:
if ynames2:
# Use solid lines for primary axis and dotted lines for
# secondary.
kwargs['dashes'] = [(None, None)]
base.plot(y_1,
self.get_times(ynames1, f=t_scale)
if xname == 'Time' else x,
ax1,
label=legends1,
**kwargs)
kwargs['dashes'] = [(3, 3)]
base.plot(y_2,
self.get_times(ynames2, f=t_scale)
if xname == 'Time' else x,
ax2,
label=legends2,
**kwargs)
else:
base.plot(y_1,
self.get_times(ynames1, f=t_scale)
if xname == 'Time' else x,
ax1,
label=legends1,
**kwargs)
elif ynames2:
base.plot(
y_2,
self.get_times(ynames2, f=t_scale) if xname == 'Time' else x,
ax2,
label=legends2,
**kwargs)
# Decorate the figure.
ax1.set_title(title)
ax1.set_xlabel(xlabel)
if ylabel1:
ax1.set_ylabel(ylabel1)
if ylabel2:
ax2.set_ylabel(ylabel2)
if legends1:
if legends2:
# Put the primary legend in the upper left and secondary in
# upper right.
leg1_kwargs['loc'] = 2
leg2_kwargs['loc'] = 1
ax1.legend(**leg1_kwargs)
ax2.legend(**leg2_kwargs)
else:
ax1.legend(**leg1_kwargs)
elif legends2:
ax2.legend(**leg2_kwargs)
return ax1, ax2