Switch on doctests in the CI (cta-observatory#1731)

* Switch on doctests in the CI

* Fix doctests failures

ctapipe/core/container.py

@@ -204,14 +204,16 @@ class Container(metaclass=ContainerMeta):
     For hierarchical data structures, Field can use `Container`
     subclasses or a `Map` as the default value.
 
-    >>>    class MyContainer(Container):
-    >>>        x = Field(100,"The X value")
-    >>>        energy = Field(-1, "Energy measurement", unit=u.TeV)
-    >>>
-    >>>    cont = MyContainer()
-    >>>    print(cont.x)
-    >>>    # metadata will become header keywords in an output file:
-    >>>    cont.meta['KEY'] = value
+    >>> import astropy.units as u
+    >>> class MyContainer(Container):
+    ...     x = Field(100, "The X value")
+    ...     energy = Field(-1, "Energy measurement", unit=u.TeV)
+    ...
+    >>> cont = MyContainer()
+    >>> print(cont.x)
+    100
+    >>> # metadata will become header keywords in an output file:
+    >>> cont.meta["KEY"] = "value"
 
     `Fields <Field>`_ inside `Containers <Container>`_ can contain instances of other
     containers, to allow for a hierarchy of containers, and can also
@@ -220,8 +222,8 @@ class Container(metaclass=ContainerMeta):
     of this can be found in `ctapipe.containers`
 
     `Container` works by shadowing all class variables (which must be
-    instances of `Field`) with instance variables of the same name the
-    hold the value expected. If ``reset`` is called, all
+    instances of `Field`) with instance variables of the same name that
+    hold the actual data. If ``reset`` is called, all
     instance variables are reset to their default values as defined in
     the class.
 

ctapipe/core/logging.py

@@ -48,6 +48,7 @@ def recursive_update(d1, d2, copy=False):
     {'a': {'b': 'foo', 'c': 'foo'}}
     >>> # As opposed to
     >>> d1.update(d2)
+    >>> d1
     {'a': {'c': 'foo'}}
     """
     if not isinstance(d1, Mapping) or not isinstance(d2, Mapping):

ctapipe/image/toymodel.py

@@ -9,8 +9,11 @@
 
     >>> from ctapipe.instrument import CameraGeometry
     >>> geom = CameraGeometry.make_rectangular(20, 20)
-    >>> showermodel = Gaussian(x=0.25 * u.m, y=0.0 * u.m,
-    length=0.1 * u.m, width=0.02 * u.m, psi='40d')
+    >>> showermodel = Gaussian(
+    ...    x=0.25 * u.m, y=0.0 * u.m,
+    ...    length=0.1 * u.m, width=0.02 * u.m,
+    ...    psi='40d'
+    ... )
     >>> image, signal, noise = showermodel.generate_image(geom, intensity=1000)
     >>> print(image.shape)
     (400,)

ctapipe/io/eventseeker.py

@@ -25,21 +25,23 @@ class EventSeeker(Component):
     filled with the event information using the methods defined in the
     event_source for that file format.
 
-    To obtain a particular event in a hessio file:
+    To obtain a particular event in a simtel file:
 
     >>> from ctapipe.io import SimTelEventSource
-    >>> event_source = SimTelEventSource(input_url="/path/to/file")
+    >>> event_source = SimTelEventSource(input_url="dataset://gamma_test_large.simtel.gz")
     >>> seeker = EventSeeker(event_source=event_source)
     >>> event = seeker.get_event_index(2)
     >>> print(event.count)
+    2
 
-    To obtain a particular event in a hessio file from its event_id:
+    To obtain a particular event in a simtel file from its event_id:
 
     >>> from ctapipe.io import SimTelEventSource
-    >>> event_source = SimTelEventSource(input_url="/path/to/file")
+    >>> event_source = SimTelEventSource(input_url="dataset://gamma_test_large.simtel.gz", back_seekable=True)
     >>> seeker = EventSeeker(event_source=event_source)
-    >>> event = seeker.get_event_id(101)
+    >>> event = seeker.get_event_id(31007)
     >>> print(event.count)
+    1
 
     **NOTE**: Event_index refers to the number associated to the event
     assigned by ctapipe (``event.count``), based on the order the events are

ctapipe/io/eventsource.py

@@ -32,30 +32,33 @@ class EventSource(Component):
     appropriate subclass if a compatible source is found for the given
     ``input_url``.
 
-    >>> dataset = get_dataset_path('gamma_test_large.simtel.gz')
-    >>> event_source = EventSource(input_url=dataset)
-    <ctapipe.io.simteleventsource.SimTelEventSource at ...>
+    >>> EventSource(input_url="dataset://gamma_test_large.simtel.gz")
+    <ctapipe.io.simteleventsource.SimTelEventSource ...>
 
     An ``EventSource`` can also be created through the configuration system,
     by passing ``config`` or ``parent`` as appropriate.
     E.g. if using ``EventSource`` inside of a ``Tool``, you would do:
-    >>> self.event_source = EventSource(parent=self)
+    >>> self.source = EventSource(parent=self) # doctest: +SKIP
 
     To loop through the events in a file:
-    >>> event_source = EventSource(input_url="/path/to/file")
-    >>> for event in event_source:
-    >>>    print(event.count)
+    >>> source = EventSource(input_url="dataset://gamma_test_large.simtel.gz", max_events=2)
+    >>> for event in source:
+    ...     print(event.count)
+    0
+    1
 
-    **NOTE**: Every time a new loop is started through the event_source,
+    **NOTE**: Every time a new loop is started through the source,
     it tries to restart from the first event, which might not be supported
     by the event source.
 
     It is encouraged to use ``EventSource`` in a context manager to ensure
-    the correct cleanups are performed when you are finished with the event_source:
+    the correct cleanups are performed when you are finished with the source:
 
-    >>> with EventSource(input_url="/path/to/file") as event_source:
-    >>>    for event in event_source:
-    >>>       print(event.count)
+    >>> with EventSource(input_url="dataset://gamma_test_large.simtel.gz", max_events=2) as source:
+    ...    for event in source:
+    ...        print(event.count)
+    0
+    1
 
     **NOTE**: For effiency reasons, most sources only use a single ``ArrayEvent`` instance
     and update it with new data on iteration, which might lead to surprising

ctapipe/utils/fitshistogram.py

@@ -38,7 +38,7 @@ class Histogram:
     --------
 
     >>> hist = Histogram(nbins=(10,10), ranges=[[-1,1], [-1,1]])
-    >>> data = np.random.normal(shape=(2*100)) # make 100 random 2D events
+    >>> data = np.random.normal(size=(100, 2)) # make 100 random 2D events
     >>> hist.fill(data)
 
 
@@ -180,12 +180,6 @@ def to_fits(self):
         """
         Convert the `Histogram` into an `astropy.io.fits.ImageHDU`,
         suitable for writing to a file.
-
-        Examples
-        --------
-
-        >>> myhist.to_fits().writeto("outputfile.fits.gz", overwrite=True)
-
         """
         ohdu = fits.ImageHDU(data=self.data.transpose())
         ohdu.name = self.name

docs/ctapipe_api/instrument/camerageometry_example.py

@@ -11,5 +11,3 @@
 plt.subplot(1, 2, 2)
 plt.scatter(geom.pix_x, geom.pix_y)
 plt.title("Pixel Positions")
-
-plt.show()

examples/stereo_reconstruction.py

@@ -3,9 +3,10 @@
 
 from ctapipe.io import EventSource
 from ctapipe.calib import CameraCalibrator
-from ctapipe.image.cleaning import tailcuts_clean, number_of_islands
+from ctapipe.image.cleaning import tailcuts_clean
+from ctapipe.image.morphology import number_of_islands
 from ctapipe.image import leakage, hillas_parameters
-from ctapipe.image.timing_parameters import timing_parameters
+from ctapipe.image.timing import timing_parameters
 from ctapipe.reco import HillasReconstructor
 from ctapipe.utils.datasets import get_dataset_path