def test_non_negative(**kwargs) -> None:
"""Raise a ValueError if at least one value of the objects given as keywords is
negative.
If all values are non negative, nothing happens:
>>> from hydpy.auxs.validtools import test_non_negative
>>> test_non_negative(arr1=numpy.array([1.0, 2.0]),
... arr2=numpy.array([3.0, 4.0]),
... arr3=numpy.array([5.0, 6.0]))
If at least one value is negative, the following error is raised:
>>> test_non_negative(arr1=numpy.array([1.0, 2.0]),
... arr2=numpy.array([-3.0, 4.0]),
... arr3=numpy.array([5.0, 6.0]))
Traceback (most recent call last):
...
ValueError: For the following objects, at least one value is negative: arr2.
For flexibility in the functions application, it is allowed to pass no array at all:
>>> test_non_negative()
"""
names = list(kwargs.keys())
negs = [numpy.nanmin(array) < 0.0 for array in kwargs.values()]
if any(negs):
string = objecttools.enumeration(
name for name, neg in sorted(zip(names, negs)) if neg)
raise ValueError(
f"For the following objects, at least one value is negative: {string}."
)
def test_equal_shape(**kwargs) -> None:
"""Raise a ValueError if the shapes of the objects given as keywords are not equal.
If all shapes are equal, nothing happens:
>>> from hydpy.auxs.validtools import test_equal_shape
>>> test_equal_shape(arr1=numpy.array([1.0, 2.0]),
... arr2=numpy.array([3.0, 4.0]),
... arr3=numpy.array([5.0, 6.0]))
If at least one shape differs, the following error is raised:
>>> test_equal_shape(arr1=numpy.array([1.0, 2.0]),
... arr2=numpy.array([3.0]),
... arr3=numpy.array([5.0, 6.0]))
Traceback (most recent call last):
...
ValueError: The shapes of the following objects are not equal: \
arr1 (2,), arr2 (1,), and arr3 (2,).
For flexibility in the functions application, it is allowed to pass only one array
or no arrays at all:
>>> test_equal_shape(arr1=numpy.array([1.0, 2.0]))
>>> test_equal_shape()
"""
names = list(kwargs.keys())
shapes = numpy.array(
[numpy.array(array).shape for array in kwargs.values()])
if any(shapes[:-1] != shapes[1:]):
string = objecttools.enumeration(
f"{name} {tuple(shape)}"
for (name, shape) in sorted(zip(names, shapes)))
raise ValueError(
f"The shapes of the following objects are not equal: {string}.")
def __set__(self, obj, value):
value = str(value)
if value in obj._supportedmodes:
self.value = value
else:
raise ValueError(
'The given sequence file type `%s` is not implemented. '
'Please choose one of the following file types: %s.' %
(value, objecttools.enumeration(obj._supportedmodes)))
def __init__(self, logfile: IO, logstyle: str, infotype: str):
self.logfile = logfile
try:
stdtype2string = self.style2infotype2string[logstyle]
except KeyError:
styles = objecttools.enumeration(
sorted(self.style2infotype2string.keys()))
raise ValueError(
f'The given log file style {logstyle} is not available. '
f'Please choose one of the following: {styles}.')
self._string = stdtype2string[infotype]
def __init__(
self,
logfile: TextIO,
logstyle: str,
infotype: Literal["info", "warning", "exception"],
) -> None:
self.logfile = logfile
self._infotype = infotype
try:
stdtype2string = self.style2infotype2string[logstyle]
except KeyError:
styles = objecttools.enumeration(
sorted(self.style2infotype2string.keys()))
raise ValueError(
f"The given log file style {logstyle} is not available. "
f"Please choose one of the following: {styles}.") from None
self._string = stdtype2string[infotype]
def execute_scriptfunction() -> Optional[int]:
"""Execute a HydPy script function.
Function |execute_scriptfunction| is indirectly applied and explained in the
documentation on module |hyd|.
"""
logstyle = "plain"
logfilepath = prepare_logfile("stdout")
try:
args_given = []
kwargs_given = {}
for arg in sys.argv[1:]:
if len(arg) < 3:
args_given.append(arg)
else:
result = parse_argument(arg)
if isinstance(result, str):
args_given.append(arg)
else:
kwargs_given[result[0]] = result[1]
logfilepath = prepare_logfile(kwargs_given.pop("logfile", "stdout"))
logstyle = kwargs_given.pop("logstyle", "plain")
try:
funcname = str(args_given.pop(0))
except IndexError:
raise ValueError(
"The first positional argument defining the function to be called is "
"missing.") from None
try:
func = hydpy.pub.scriptfunctions[funcname]
except KeyError:
available_funcs = objecttools.enumeration(
sorted(hydpy.pub.scriptfunctions.keys()))
raise ValueError(
f"There is no `{funcname}` function callable by `hyd.py`. Choose one "
f"of the following instead: {available_funcs}.") from None
argspec = inspect.getfullargspec(func)
args_possible = argspec.args
if argspec.defaults:
args_required = args_possible[:-len(argspec.defaults)]
else:
args_required = args_possible
nmb_args_possible = len(args_possible)
nmb_args_required = len(args_required)
nmb_args_given = len(args_given)
if nmb_args_given < nmb_args_required or nmb_args_given > nmb_args_possible:
enum_args_given = ""
if nmb_args_given:
enum_args_given = f" ({objecttools.enumeration(args_given)})"
if nmb_args_given < nmb_args_required:
args = args_required
nmb_args = nmb_args_required
condition = "requires"
else:
args = args_possible
nmb_args = nmb_args_possible
condition = "allows"
enum_args = ""
if nmb_args:
enum_args = f" ({objecttools.enumeration(args)})"
raise ValueError(
f"Function `{funcname}` {condition} `{nmb_args:d}` "
f"positional arguments{enum_args}, but "
f"`{nmb_args_given:d}` are given{enum_args_given}.")
with _activate_logfile(logfilepath, logstyle, "info", "warning"):
return func(*args_given, **kwargs_given)
except BaseException as exc:
if logstyle not in LogFileInterface.style2infotype2string:
logstyle = "plain"
with _activate_logfile(logfilepath, logstyle, "exception",
"exception"):
args = sys.argv[1:]
nmb = len(args)
if nmb > 1:
argphrase = f"with arguments `{', '.join(args)}`"
elif nmb == 1:
argphrase = f"with argument `{args[0]}`"
else:
argphrase = "without arguments"
print(
f"Invoking hyd.py {argphrase} resulted in the following error:\n"
f"{str(exc)}\n\nSee the following stack traceback for debugging:\n",
file=sys.stderr,
)
traceback.print_tb(sys.exc_info()[2])
return 1
def plot(self,
filename,
width=None,
height=None,
selected=None,
activated=None):
"""Save a bokeh html file plotting the current test results.
(Optional) arguments:
* filename: Name of the file. If necessary, the file ending
`html` is added automatically. The file is stored in the
`html` folder of subpackage `docs`.
* width: Width of the plot in screen units. Defaults to 600.
* height: Height of the plot in screen units. Defaults to 300.
* selected: List of the sequences to be plotted.
* activated: List of the sequences to be shown initially.
"""
if width is None:
width = self.plotting_options.width
if height is None:
height = self.plotting_options.height
if not filename.endswith('.html'):
filename += '.html'
if selected is None:
selected = self.plotting_options.selected
if selected is None:
selected = self.parseqs
if activated is None:
activated = self.plotting_options.activated
if activated is None:
activated = self.parseqs
activated = tuple(nm_.name if hasattr(nm_, 'name') else nm_.lower()
for nm_ in activated)
path = os.path.join(docs.__path__[0], 'html', filename)
plotting.output_file(path)
plot = plotting.figure(x_axis_type="datetime",
tools=['pan', 'ywheel_zoom'],
toolbar_location=None)
plot.toolbar.active_drag = plot.tools[0]
plot.toolbar.active_scroll = plot.tools[1]
plot.plot_width = width
plot.plot_height = height
legend_entries = []
viridis = palettes.viridis
headers = [header for header in self.raw_header_strings[1:] if header]
zipped = zip(selected, viridis(len(selected)), headers)
for (seq, col, header) in zipped:
series = seq.series.copy()
if not seq.NDIM:
listofseries = [series]
listofsuffixes = ['']
else:
nmb = seq.shape[0]
listofseries = [series[:, idx] for idx in range(nmb)]
if nmb == 1:
listofsuffixes = ['']
else:
listofsuffixes = ['-%d' % idx for idx in range(nmb)]
for subseries, suffix in zip(listofseries, listofsuffixes):
line = plot.line(self._datetimes,
subseries,
alpha=0.8,
muted_alpha=0.0,
line_width=2,
color=col)
line.muted = seq.name not in activated
if header.strip() == seq.name:
title = objecttools.classname(seq)
else:
title = header.capitalize()
title += suffix
legend_entries.append((title, [line]))
legend = models.Legend(items=legend_entries, click_policy='mute')
legend.border_line_color = None
plot.add_layout(legend, 'right')
units = self.extract_units(selected)
ylabel = objecttools.enumeration(units).replace('and', 'or')
plot.yaxis.axis_label = ylabel
plot.yaxis.axis_label_text_font_style = 'normal'
plotting.save(plot)
self._src = filename
self._width = width
self._height = height
def connect(self):
"""Connect the |InletSequence| and |OutletSequence| objects of
the actual model to the |NodeSequence| objects handled by an
arbitrary number of inlet and outlet nodes.
To application models derived from |conv_model.Model|, you first
need to define an |Element| connected with an arbitrary number of
inlet and outlet nodes:
>>> from hydpy import Element
>>> conv = Element("conv",
... inlets=["in1", "in2"],
... outlets=["out1", "out2", "out3"])
Second, you must define the inlet and outlet nodes' coordinates via
parameter |InputCoordinates| and |OutputCoordinates|, respectively.
In both cases, use the names of the |Node| objects as keyword arguments
to pass the corresponding coordinates:
>>> from hydpy.models.conv_v001 import *
>>> parameterstep()
>>> inputcoordinates(
... in1=(0.0, 3.0),
... in2=(2.0, -1.0))
>>> outputcoordinates(
... out1=(0.0, 3.0),
... out2=(3.0, -2.0),
... out3=(1.0, 2.0))
>>> maxnmbinputs()
>>> parameters.update()
|conv| passes the current values of the inlet nodes correctly to
the outlet nodes (note that node `in1` works with simulated values
while node `in2` works with observed values, as we set its
|Node.deploymode| to `obs`):
>>> conv.model = model
>>> conv.inlets.in1.sequences.sim = 1.0
>>> conv.inlets.in2.deploymode = "obs"
>>> conv.inlets.in2.sequences.obs = 2.0
>>> model.simulate(0)
>>> conv.outlets.out1.sequences.sim
sim(1.0)
>>> conv.outlets.out2.sequences.sim
sim(2.0)
>>> conv.outlets.out3.sequences.sim
sim(1.0)
When you forget a node (or misspell its name), you get the
following error message:
>>> outputcoordinates(
... out1=(0.0, 3.0),
... out2=(3.0, -2.0))
>>> maxnmbinputs()
>>> parameters.update()
>>> conv.model = model
Traceback (most recent call last):
...
RuntimeError: While trying to connect model `conv_v001` of element \
`conv`, the following error occurred: The node handled by control parameter \
outputcoordinates (out1 and out2) are not the same as the outlet nodes \
handled by element conv (out1, out2, and out3).
"""
try:
for coordinates, sequence, nodes in (
(
self.parameters.control.inputcoordinates,
self.sequences.inlets.inputs,
self.element.inlets,
),
(
self.parameters.control.outputcoordinates,
self.sequences.outlets.outputs,
self.element.outlets,
),
):
if nodes == devicetools.Nodes(coordinates.nodes):
sequence.shape = len(coordinates)
for idx, node in enumerate(coordinates.nodes):
sequence.set_pointer(
node.get_double(sequence.subseqs.name), idx)
else:
parameternodes = objecttools.enumeration(coordinates.nodes)
elementnodes = objecttools.enumeration(nodes)
raise RuntimeError(
f"The node handled by control parameter "
f"{coordinates.name} ({parameternodes}) are not the "
f"same as the {sequence.subseqs.name[:-1]} nodes "
f"handled by element {self.element.name} "
f"({elementnodes}).")
except BaseException:
objecttools.augment_excmessage(
f"While trying to connect model "
f"{objecttools.elementphrase(self)}")
def execute_scriptfunction() -> Optional[int]:
"""Execute a HydPy script function.
Function |execute_scriptfunction| is indirectly applied and
explained in the documentation on module |hyd|.
"""
try:
args_given = []
kwargs_given = {}
for arg in sys.argv[1:]:
if len(arg) < 3:
args_given.append(arg)
else:
try:
key, value = parse_argument(arg)
kwargs_given[key] = value
except ValueError:
args_given.append(arg)
logfilepath = prepare_logfile(kwargs_given.pop('logfile', 'stdout'))
logstyle = kwargs_given.pop('logstyle', 'plain')
try:
funcname = str(args_given.pop(0))
except IndexError:
raise ValueError(
'The first positional argument defining the function '
'to be called is missing.')
try:
func = hydpy.pub.scriptfunctions[funcname]
except KeyError:
available_funcs = objecttools.enumeration(
sorted(hydpy.pub.scriptfunctions.keys()))
raise ValueError(
f'There is no `{funcname}` function callable by `hyd.py`. '
f'Choose one of the following instead: {available_funcs}.')
argspec = inspect.getfullargspec(func)
args_possible = argspec.args
if argspec.defaults:
args_required = args_possible[:-len(argspec.defaults)]
else:
args_required = args_possible
nmb_args_possible = len(args_possible)
nmb_args_required = len(args_required)
nmb_args_given = len(args_given)
if (nmb_args_given < nmb_args_required
or nmb_args_given > nmb_args_possible):
enum_args_given = ''
if nmb_args_given:
enum_args_given = (f' ({objecttools.enumeration(args_given)})')
if nmb_args_given < nmb_args_required:
args = args_required
nmb_args = nmb_args_required
condition = 'requires'
else:
args = args_possible
nmb_args = nmb_args_possible
condition = 'allows'
enum_args = ''
if nmb_args:
enum_args = f' ({objecttools.enumeration(args)})'
raise ValueError(
f'Function `{funcname}` {condition} `{nmb_args:d}` '
f'positional arguments{enum_args}, but '
f'`{nmb_args_given:d}` are given{enum_args_given}.')
with _activate_logfile(logfilepath, logstyle, 'info', 'warning'):
return func(*args_given, **kwargs_given)
except BaseException as exc:
if logstyle not in LogFileInterface.style2infotype2string:
logstyle = 'plain'
with _activate_logfile(logfilepath, logstyle, 'exception',
'exception'):
args = sys.argv[1:]
nmb = len(args)
if nmb > 1:
argphrase = f'with arguments `{", ".join(args)}`'
elif nmb == 1:
argphrase = f'with argument `{args[0]}`'
else:
argphrase = 'without arguments'
print(
f'Invoking hyd.py {argphrase} resulted in the following '
f'error:\n{str(exc)}\n\n'
f'See the following stack traceback for debugging:\n',
file=sys.stderr)
traceback.print_tb(sys.exc_info()[2])
return 1
def search_elementnames(self,
*substrings: str,
name: str = 'elementnames') -> 'Selection':
"""Return a new selection containing all elements of the current
selection with a name containing at least one of the given substrings.
>>> from hydpy.examples import prepare_full_example_2
>>> hp, pub, _ = prepare_full_example_2()
Pass the (sub)strings as positional arguments and, optionally, the
name of the newly created |Selection| object as a keyword argument:
>>> test = pub.selections.complete.copy('test')
>>> from hydpy import prepare_model
>>> test.search_elementnames('dill', 'lahn_1')
Selection("elementnames",
nodes=(),
elements=("land_dill", "land_lahn_1", "stream_dill_lahn_2",
"stream_lahn_1_lahn_2"))
Wrong string specifications result in errors like the following:
>>> test.search_elementnames(['dill', 'lahn_1'])
Traceback (most recent call last):
...
TypeError: While trying to determine the elements of selection \
`test` with names containing at least one of the given substrings \
`['dill', 'lahn_1']`, the following error occurred: 'in <string>' \
requires string as left operand, not list
Method |Selection.select_elementnames| restricts the current selection
to the one determined with the method |Selection.search_elementnames|:
>>> test.select_elementnames('dill', 'lahn_1')
Selection("test",
nodes=("dill", "lahn_1", "lahn_2", "lahn_3"),
elements=("land_dill", "land_lahn_1", "stream_dill_lahn_2",
"stream_lahn_1_lahn_2"))
On the contrary, the method |Selection.deselect_elementnames|
restricts the current selection to all devices not determined
by the method |Selection.search_elementnames|:
>>> pub.selections.complete.deselect_elementnames('dill', 'lahn_1')
Selection("complete",
nodes=("dill", "lahn_1", "lahn_2", "lahn_3"),
elements=("land_lahn_2", "land_lahn_3",
"stream_lahn_2_lahn_3"))
"""
try:
selection = Selection(name)
for element in self.elements:
for substring in substrings:
if substring in element.name:
selection.elements += element
break
return selection
except BaseException:
values = objecttools.enumeration(substrings)
objecttools.augment_excmessage(
f'While trying to determine the elements of selection '
f'`{self.name}` with names containing at least one '
f'of the given substrings `{values}`')
def search_modeltypes(self,
*models: ModelTypesArg,
name: str = 'modeltypes') -> 'Selection':
"""Return a |Selection| object containing only the elements
currently handling models of the given types.
>>> from hydpy.examples import prepare_full_example_2
>>> hp, pub, _ = prepare_full_example_2()
You can pass both |Model| objects and names and, as a keyword
argument, the name of the newly created |Selection| object:
>>> test = pub.selections.complete.copy('test')
>>> from hydpy import prepare_model
>>> hland_v1 = prepare_model('hland_v1')
>>> test.search_modeltypes(hland_v1)
Selection("modeltypes",
nodes=(),
elements=("land_dill", "land_lahn_1", "land_lahn_2",
"land_lahn_3"))
>>> test.search_modeltypes(
... hland_v1, 'hstream_v1', 'lland_v1', name='MODELTYPES')
Selection("MODELTYPES",
nodes=(),
elements=("land_dill", "land_lahn_1", "land_lahn_2",
"land_lahn_3", "stream_dill_lahn_2",
"stream_lahn_1_lahn_2", "stream_lahn_2_lahn_3"))
Wrong model specifications result in errors like the following:
>>> test.search_modeltypes('wrong')
Traceback (most recent call last):
...
ModuleNotFoundError: While trying to determine the elements of \
selection `test` handling the model defined by the argument(s) `wrong` \
of type(s) `str`, the following error occurred: \
No module named 'hydpy.models.wrong'
Method |Selection.select_modeltypes| restricts the current selection to
the one determined with the method the |Selection.search_modeltypes|:
>>> test.select_modeltypes(hland_v1)
Selection("test",
nodes=(),
elements=("land_dill", "land_lahn_1", "land_lahn_2",
"land_lahn_3"))
On the contrary, the method |Selection.deselect_upstream| restricts
the current selection to all devices not determined by method the
|Selection.search_upstream|:
>>> pub.selections.complete.deselect_modeltypes(hland_v1)
Selection("complete",
nodes=(),
elements=("stream_dill_lahn_2", "stream_lahn_1_lahn_2",
"stream_lahn_2_lahn_3"))
"""
try:
typelist = []
for model in models:
if not isinstance(model, modeltools.Model):
model = importtools.prepare_model(model)
typelist.append(type(model))
typetuple = tuple(typelist)
selection = Selection(name)
for element in self.elements:
if isinstance(element.model, typetuple):
selection.elements += element
return selection
except BaseException:
values = objecttools.enumeration(models)
classes = objecttools.enumeration(
objecttools.classname(model) for model in models)
objecttools.augment_excmessage(
f'While trying to determine the elements of selection '
f'`{self.name}` handling the model defined by the '
f'argument(s) `{values}` of type(s) `{classes}`')
