from sympy.external import import_module
from spb.backends.base_backend import Plot
from spb.backends.matplotlib import MB
def _nrows_ncols(nr, nc, nplots):
"""Define the correct number of rows and/or columns based on the number
of plots to be shown.
"""
np = import_module('numpy')
if (nc <= 0) and (nr <= 0):
nc = 1
nr = nplots
elif nr <= 0:
nr = int(np.ceil(nplots / nc))
elif nc <= 0:
nc = int(np.ceil(nplots / nr))
elif nr * nc < nplots:
nr += 1
return _nrows_ncols(nr, nc, nplots)
return nr, nc
def _create_mpl_figure(mapping):
matplotlib = import_module(
'matplotlib',
import_kwargs={'fromlist': ['pyplot', 'gridspec']},
min_module_version='1.1.0',
catch=(RuntimeError,))
plt = matplotlib.pyplot
fig = plt.figure()
for spec, p in mapping.items():
kw = {"projection": "3d"} if (len(p.series) > 0 and
p.series[0].is_3D) else {}
cur_ax = fig.add_subplot(spec, **kw)
# cpa: current plot attributes
cpa = p._copy_kwargs()
cpa["backend"] = MB
cpa["fig"] = fig
cpa["ax"] = cur_ax
p = Plot(*p.series, **cpa)
p.process_series()
return fig
def _create_panel_figure(mapping, panel_kw):
pn = import_module(
'panel',
min_module_version='0.12.0')
pn.extension("plotly")
fig = pn.GridSpec(**panel_kw)
for spec, p in mapping.items():
rs = spec.rowspan
cs = spec.colspan
fig[slice(rs.start, rs.stop), slice(cs.start, cs.stop)] = p.fig
return fig
[docs]def plotgrid(*args, **kwargs):
"""Combine multiple plots into a grid-like layout.
This function has two modes of operation, depending on the input arguments.
Make sure to read the examples to fully understand them.
Parameters
==========
args : sequence (optional)
A sequence of aldready created plots. This, in combination with
`nr` and `nc` represents the first mode of operation, where a basic
grid with (nc * nr) subplots will be created.
nr, nc : int (optional)
Number of rows and columns.
By default, `nc = 1` and `nr = -1`: this will create as many rows
as necessary, and a single column.
By setting `nr = 1` and `nc = -1`, it will create a single row and
as many columns as necessary.
gs : dict (optional)
A dictionary mapping Matplotlib's `GridSpec` objects to the plots.
The keys represent the cells of the layout. Each cell will host the
associated plot.
This represents the second mode of operation, as it allows to create
more complicated layouts.
panel_kw : dict (optional)
A dictionary of keyword arguments to be passed to panel's `GridSpec`
for further customization. Default to
`dict(sizing_mode="stretch_width")`. Refer to [#fn1]_ for more
information.
show : boolean (optional)
It applies only to Matplotlib figures. Default to True.
Returns
=======
fig : `plt.Figure` or `pn.GridSpec`
If all input plots are instances of `MatplotlibBackend`, than a
Matplotlib `Figure` will be returned. Otherwise an instance of
Holoviz Panel's `GridSpec` will be returned.
Examples
========
First mode of operation with instances of `MatplotlibBackend`:
.. code-block:: python
from sympy import symbols, sin, cos, tan, exp, sqrt, Matrix, gamma
from spb.backends.matplotlib import MB
from spb import *
x, y, z = symbols("x, y, z")
p1 = plot(sin(x), backend=MB, show=False)
p2 = plot(tan(x), backend=MB, detect_poles=True, show=False)
p3 = plot(exp(-x), backend=MB, show=False)
fig = plotgrid(p1, p2, p3)
First mode of operation with different backends. Try this on a Jupyter
Notebook. Note:
1. the output of `plotgrid` is not captured into a variable. It is
captured and rendered by Jupyter Notebook.
2. Matplotlib has been integrated as a picture, thus it loses its
interactivity.
.. code-block:: python
p1 = plot(sin(x), backend=MB, show=False)
p2 = plot(tan(x), backend=MB, detect_poles=True, show=False)
p3 = plot(exp(-x), backend=MB, show=False)
plotgrid(p1, p2, p3, nr=1, nc=3,
panel_kw=dict(sizing_mode="stretch_width", height=250))
Second mode of operation, using Matplotlib GridSpec:
.. code-block:: python
from matplotlib.gridspec import GridSpec
p1 = plot(sin(x), cos(x), show=False, backend=MB)
p2 = plot_contour(cos(x**2 + y**2), (x, -3, 3), (y, -3, 3), show=False, backend=BB)
p3 = plot_complex(sqrt(x), show=False, backend=PB)
p4 = plot_vector(Matrix([-y, x]), (x, -5, 5), (y, -5, 5), show=False, backend=MB)
p5 = plot_complex(gamma(z), (z, -3-3*I, 3+3*I), show=False, backend=MB)
gs = GridSpec(3, 3)
mapping = {
gs[0, :1]: p1,
gs[1, :1]: p2,
gs[2:, :1]: p3,
gs[2:, 1:]: p4,
gs[0:2, 1:]: p5,
}
plotgrid(gs=mapping)
References
==========
.. [#fn1] https://panel.holoviz.org/reference/layouts/GridSpec.html
"""
matplotlib = import_module(
'matplotlib',
import_kwargs={'fromlist': ['pyplot', 'gridspec']},
min_module_version='1.1.0',
catch=(RuntimeError,))
plt = matplotlib.pyplot
GridSpec = matplotlib.gridspec.GridSpec
show = kwargs.get("show", True)
gs = kwargs.get("gs", None)
panel_kw = kwargs.get("panel_kw", dict(sizing_mode="stretch_width"))
if (gs is None) and (len(args) == 0):
fig = plt.figure()
elif (gs is None):
### First mode of operation
# default layout: 1 columns, as many rows as needed
nr = kwargs.get("nr", -1)
nc = kwargs.get("nc", 1)
nr, nc = _nrows_ncols(nr, nc, len(args))
gs = GridSpec(nr, nc)
mapping = {}
c = 0
for i in range(nr):
for j in range(nc):
if c < len(args):
mapping[gs[i, j]] = args[c]
c += 1
if all(isinstance(a, MB) for a in args):
fig = _create_mpl_figure(mapping)
else:
fig = _create_panel_figure(mapping, panel_kw)
else:
### Second mode of operation
if not isinstance(gs, dict):
raise TypeError("`gs` must be a dictionary.")
SubplotSpec = matplotlib.gridspec.SubplotSpec
if not isinstance(list(gs.keys())[0], SubplotSpec):
raise ValueError(
"Keys of `gs` must be of elements of type "
"matplotlib.gridspec.SubplotSpec. Use "
"matplotlib.gridspec.GridSpec to create them.")
if all(isinstance(a, MB) for a in gs.values()):
fig = _create_mpl_figure(gs)
else:
fig = _create_panel_figure(gs, panel_kw)
if isinstance(fig, plt.Figure):
fig.tight_layout()
if show:
plt.show()
return fig