diff --git a/b_asic/resources.py b/b_asic/resources.py
index b33de2eb4c40aaebfd89fc8207eb5cf922866e98..f5ab1c76f8d611b111f3c57f61fee9c751caba0a 100644
--- a/b_asic/resources.py
+++ b/b_asic/resources.py
@@ -1006,6 +1006,9 @@ class ProcessCollection:
fig.savefig(f, format="svg") # type: ignore
return f.getvalue()
+ # SVG is valid HTML. This is useful for e.g. sphinx-gallery
+ _repr_html_ = _repr_svg_
+
def __repr__(self):
return (
f"ProcessCollection({self._collection}, {self._schedule_time},"
diff --git a/b_asic/schedule.py b/b_asic/schedule.py
index d35fcca72741f2489d28a1b8150cdc75863cc533..242a9525e23b19ffa6777bc7043ea185d634032b 100644
--- a/b_asic/schedule.py
+++ b/b_asic/schedule.py
@@ -1064,3 +1064,6 @@ class Schedule:
fig.savefig(buffer, format="svg")
return buffer.getvalue()
+
+ # SVG is valid HTML. This is useful for e.g. sphinx-gallery
+ _repr_html_ = _repr_svg_
diff --git a/b_asic/signal_flow_graph.py b/b_asic/signal_flow_graph.py
index 43c6d085a6ebf05ea6c12061319693442dc1f40e..e9e47845955c118aaecd843c8cfb2f799850ba05 100644
--- a/b_asic/signal_flow_graph.py
+++ b/b_asic/signal_flow_graph.py
@@ -1490,6 +1490,14 @@ class SFG(AbstractOperation):
def _repr_png_(self):
return self.sfg_digraph()._repr_mimebundle_(include=["image/png"])["image/png"]
+ def _repr_svg_(self):
+ return self.sfg_digraph()._repr_mimebundle_(include=["image/svg+xml"])[
+ "image/svg+xml"
+ ]
+
+ # SVG is valid HTML. This is useful for e.g. sphinx-gallery
+ _repr_html_ = _repr_svg_
+
def show(
self,
fmt: Optional[str] = None,
diff --git a/examples/connectmultiplesfgs.py b/examples/connectmultiplesfgs.py
index 2a0786010f3efa9b90592362a1320f8eb6c1bbf1..4ab897b43ab189b941002282720cd69f52a54568 100644
--- a/examples/connectmultiplesfgs.py
+++ b/examples/connectmultiplesfgs.py
@@ -1,5 +1,3 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
"""
========================
Connecting multiple SFGs
@@ -14,46 +12,40 @@ SFGs but the operations of these. To do this, one will have to use the
method :func:`~b_asic.signal_flow_graph.SFG.connect_external_signals_to_components`.
This example illustrates how it can be done.
+"""
-.. jupyter-execute::
-
- from b_asic.sfg_generators import wdf_allpass
- from b_asic.signal_flow_graph import SFG
- from b_asic.special_operations import Input, Output
-
- # Generate allpass branches for fifth-ordet LWDF filter
- allpass1 = wdf_allpass([0.2, 0.5])
- allpass2 = wdf_allpass([-0.5, 0.2, 0.5])
-
- in_lwdf = Input()
- allpass1 << in_lwdf
- allpass2 << in_lwdf
- out_lwdf = Output((allpass1 + allpass2) * 0.5)
-
- # Create SFG of LWDF with two internal SFGs
- sfg_with_sfgs = SFG(
- [in_lwdf], [out_lwdf], name="LWDF with separate internals SFGs for allpass branches"
- )
-
-The resulting SFG looks like:
+from b_asic.sfg_generators import wdf_allpass
+from b_asic.signal_flow_graph import SFG
+from b_asic.special_operations import Input, Output
-.. jupyter-execute::
+# Generate allpass branches for fifth-ordet LWDF filter
+allpass1 = wdf_allpass([0.2, 0.5])
+allpass2 = wdf_allpass([-0.5, 0.2, 0.5])
- sfg_with_sfgs
+in_lwdf = Input()
+allpass1 << in_lwdf
+allpass2 << in_lwdf
+out_lwdf = Output((allpass1 + allpass2) * 0.5)
+# Create SFG of LWDF with two internal SFGs
+sfg_with_sfgs = SFG(
+ [in_lwdf], [out_lwdf], name="LWDF with separate internals SFGs for allpass branches"
+)
-Now, to create a LWDF where the SFGs are flattened. Note that the original SFGs
-``allpass1`` and ``allpass2`` currently cannot be printed etc after this operation.
+# %%
+# The resulting SFG looks like:
-.. jupyter-execute::
+sfg_with_sfgs
- allpass1.connect_external_signals_to_components()
- allpass2.connect_external_signals_to_components()
- flattened_sfg = SFG([in_lwdf], [out_lwdf], name="Flattened LWDF")
+# %%
+# Now, to create a LWDF where the SFGs are flattened. Note that the original SFGs
+# ``allpass1`` and ``allpass2`` currently cannot be printed etc after this operation.
-Resulting in:
+allpass1.connect_external_signals_to_components()
+allpass2.connect_external_signals_to_components()
+flattened_sfg = SFG([in_lwdf], [out_lwdf], name="Flattened LWDF")
-.. jupyter-execute::
+# %%
+# Resulting in:
- flattened_sfg
-"""
+flattened_sfg
diff --git a/examples/firstorderiirfilter.py b/examples/firstorderiirfilter.py
index 16baebebe0353cb4205e4ce3afb1b209f9cebe00..9f02c0910d71d85af677006e00c7543a2ae4c115 100644
--- a/examples/firstorderiirfilter.py
+++ b/examples/firstorderiirfilter.py
@@ -7,11 +7,12 @@ In this example, a direct form first-order IIR filter is designed.
First, we need to import the operations that will be used in the example:
"""
-from b_asic.core_operations import Addition, ConstantMultiplication
+from b_asic.core_operations import ConstantMultiplication
from b_asic.special_operations import Delay, Input, Output
# %%
-# Then, we continue by defining the input and delay element, which we can optionally name.
+# Then, we continue by defining the input and delay element, which we can optionally
+# name.
input = Input(name="My input")
delay = Delay(name="The only delay")
@@ -27,15 +28,17 @@ a1 = ConstantMultiplication(0.5, delay)
first_addition = a1 + input
# %%
-# Or by creating them, but connecting the input later. Each operation has a function :func:`~b_asic.operation.Operation.input`
-# that is used to access a specific input (or output, by using :func:`~b_asic.operation.Operation.output`).
+# Or by creating them, but connecting the input later. Each operation has a function
+# :func:`~b_asic.operation.Operation.input`that is used to access a specific input
+# (or output, by using :func:`~b_asic.operation.Operation.output`).
b1 = ConstantMultiplication(0.7)
b1.input(0).connect(delay)
# %%
-# The latter is useful when there is not a single order to create the signal flow graph, e.g., for recursive algorithms.
-# In this example, we could not connect the output of the delay as that was not yet available.
+# The latter is useful when there is not a single order to create the signal flow
+# graph, e.g., for recursive algorithms. In this example, we could not connect the
+# output of the delay as that was not yet available.
#
# There is also a shorthand form to connect signals using the ``<<`` operator:
@@ -47,47 +50,27 @@ delay << first_addition
output = Output(b1 + first_addition)
# %%
-# Now, we should create a signal flow graph, but first it must be imported (normally, this should go at the top of the file).
+# Now, we should create a signal flow graph, but first it must be imported (normally,
+# this should go at the top of the file).
-from b_asic.signal_flow_graph import SFG
+from b_asic.signal_flow_graph import SFG # noqa: E402
# %%
-# The signal flow graph is defined by its inputs and outputs, so these must be provided. As, in general, there can be
-# multiple inputs and outputs, there should be provided as a list or a tuple.
+# The signal flow graph is defined by its inputs and outputs, so these must be
+# provided. As, in general, there can be multiple inputs and outputs, there should
+# be provided as a list or a tuple.
firstorderiir = SFG([input], [output])
# %%
-# If this is executed in an enriched terminal, such as a Jupyter Notebook, Jupyter QtConsole, or Spyder, just typing
-# the variable name will return a graphical representation of the signal flow graph.
+# If this is executed in an enriched terminal, such as a Jupyter Notebook, Jupyter
+# QtConsole, or Spyder, just typing the variable name will return a graphical
+# representation of the signal flow graph.
firstorderiir
# %%
-# This will look something like
-#
-# .. graphviz::
-#
-# digraph {
-# rankdir=LR
-# in1 [shape=cds]
-# in1 -> add1
-# out1 [shape=cds]
-# add2 -> out1
-# add1 [shape=ellipse]
-# cmul1 -> add1
-# cmul1 [shape=ellipse]
-# add1 -> t1
-# t1 [shape=square]
-# add1 -> add2
-# add2 [shape=ellipse]
-# cmul2 -> add2
-# cmul2 [shape=ellipse]
-# t1 -> cmul2
-# t1 -> cmul1
-# }
-#
-# For now, we can print the precendence relations of the SFG
+# For now, we can print the precedence relations of the SFG
firstorderiir.print_precedence_graph()
# %%
@@ -145,21 +128,23 @@ firstorderiir.print_precedence_graph()
# add2 [label=add2 shape=ellipse]
# }
#
-# As seen, each operation has an id, in addition to the optional name. This can be used to access the operation.
-# For example,
+# As seen, each operation has an id, in addition to the optional name.
+# This can be used to access the operation. For example,
firstorderiir.find_by_id('cmul1')
# %%
-# Note that this operation differs from ``a1`` defined above as the operations are copied and recreated once inserted
-# into a signal flow graph.
+# Note that this operation differs from ``a1`` defined above as the operations are
+# copied and recreated once inserted into a signal flow graph.
#
-# The signal flow graph can also be simulated. For this, we must import :class:`.Simulation`.
+# The signal flow graph can also be simulated. For this, we must import
+# :class:`.Simulation`.
-from b_asic.simulation import Simulation
+from b_asic.simulation import Simulation # noqa: E402
# %%
-# The :class:`.Simulation` class require that we provide inputs. These can either be arrays of values or we can use functions
-# that provides the values when provided a time index.
+# The :class:`.Simulation` class require that we provide inputs. These can either be
+# arrays of values or we can use functions that provides the values when provided a
+# time index.
#
# Let us create a simulation that simulates a short impulse response:
@@ -171,18 +156,18 @@ sim = Simulation(firstorderiir, [[1, 0, 0, 0, 0]])
sim.run()
# %%
-# The returned value is the output after the final iteration. However, we may often be interested in the results from
-# the whole simulation.
-# The results from the simulation, which is a dictionary of all the nodes in the signal flow graph,
-# can be obtained as
+# The returned value is the output after the final iteration. However, we may often be
+# interested in the results from the whole simulation.
+# The results from the simulation, which is a dictionary of all the nodes in the signal
+# flow graph, can be obtained as
sim.results
# %%
-# Hence, we can obtain the results that we are interested in and, for example, plot the output and the value after the
-# first addition:
+# Hence, we can obtain the results that we are interested in and, for example, plot the
+# output and the value after the first addition:
-import matplotlib.pyplot as plt
+import matplotlib.pyplot as plt # noqa: E402
plt.plot(sim.results['0'], label="Output")
plt.plot(sim.results['add1'], label="After first addition")
@@ -193,24 +178,27 @@ plt.show()
# %%
# To compute and plot the frequency response, it is possible to use mplsignal
-from mplsignal.freq_plots import freqz_fir
+from mplsignal.freq_plots import freqz_fir # noqa: E402
freqz_fir(sim.results["0"])
plt.show()
# %%
-# As seen, the output has not converged to zero, leading to that the frequency-response may not be correct, so we want
-# to simulate for a longer time.
-# Instead of just adding zeros to the input array, we can use a function that generates the impulse response instead.
-# There are a number of those defined in B-ASIC for convenience, and the one for an impulse response is called :class:`.Impulse`.
+# As seen, the output has not converged to zero, leading to that the frequency-response
+# may not be correct, so we want to simulate for a longer time.
+# Instead of just adding zeros to the input array, we can use a function that generates
+# the impulse response instead.
+# There are a number of those defined in B-ASIC for convenience, and the one for an
+# impulse response is called :class:`.Impulse`.
-from b_asic.signal_generator import Impulse
+from b_asic.signal_generator import Impulse # noqa: E402
sim = Simulation(firstorderiir, [Impulse()])
# %%
-# Now, as the functions will not have an end, we must run the simulation for a given number of cycles, say 30.
+# Now, as the functions will not have an end, we must run the simulation for a given
+# number of cycles, say 30.
# This is done using :func:`~b_asic.simulation.Simulation.run_for` instead:
sim.run_for(30)
diff --git a/examples/folding_example_with_architecture.py b/examples/folding_example_with_architecture.py
index 6f226f917b132177e8b934551140ef23c41356a5..8eea8e4d3bf8b47a10f02a60d9161df620232d49 100644
--- a/examples/folding_example_with_architecture.py
+++ b/examples/folding_example_with_architecture.py
@@ -35,6 +35,10 @@ out1 = Output(add1 + add3, "OUT")
sfg = SFG(inputs=[in1], outputs=[out1], name="Bi-quad folding example")
+# %%
+# The SFG looks like:
+sfg
+
# %%
# Set latencies and execution times
sfg.set_latency_of_type(ConstantMultiplication.type_name(), 2)
diff --git a/examples/introduction.py b/examples/introduction.py
index 8e1747997460a180d55765d7870881522b4d4030..2cf182b3db8eb3df174bd52557810eb627b3b102 100644
--- a/examples/introduction.py
+++ b/examples/introduction.py
@@ -15,3 +15,7 @@ a = Addition(i, c)
d.input(0).connect(a)
sfg = SFG([i], [o])
+
+# %%
+# The SFG looks like:
+sfg
diff --git a/examples/schedulingexample.py b/examples/schedulingexample.py
index 889e99bcfe290df0b5716f5c1f4a24fe34e98a44..44e3f9468a1b8440bb2d4704ff6a267b2a62fa52 100644
--- a/examples/schedulingexample.py
+++ b/examples/schedulingexample.py
@@ -28,3 +28,6 @@ node3 = node2 + node5
node4 << node3
sfg = SFG([node1], [out], name="Scheduling example")
+# %%
+# THe SFG looks like
+sfg
diff --git a/examples/threepointwinograddft.py b/examples/threepointwinograddft.py
index 17ec5c42248e4635677dcca13381a6c0d47ec1de..68b8afbd3997c4b05476fbedea19e8ca9b0ac6c5 100644
--- a/examples/threepointwinograddft.py
+++ b/examples/threepointwinograddft.py
@@ -37,6 +37,10 @@ sfg = SFG(
name="3-point Winograd DFT",
)
+# %%
+# The SFG looks like
+sfg
+
# %%
# Set latencies and execution times
sfg.set_latency_of_type(ConstantMultiplication.type_name(), 2)