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[Doc] Consistently format Python module names using italics
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The exception to this is where the reference is specifically to the
package name, for instance when describing installation with pip or conda.
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@speth
speth committed Feb 16, 2022
1 parent a7c2f32 commit fcaccbd
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Showing 4 changed files with 37 additions and 37 deletions.
36 changes: 18 additions & 18 deletions interfaces/cython/cantera/composite.py
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Original file line number Diff line number Diff line change
Expand Up @@ -357,7 +357,7 @@ class SolutionArray:
array of states.
`SolutionArray` can represent both 1D and multi-dimensional arrays of states,
with shapes described in the same way as Numpy arrays. All of the states
with shapes described in the same way as *NumPy* arrays. All of the states
can be set in a single call::
>>> gas = ct.Solution('gri30.yaml')
Expand All @@ -367,13 +367,13 @@ class SolutionArray:
>>> X = 'CH4:1.0, O2:1.0, N2:3.76'
>>> states.TPX = T, P, X
Similar to Numpy arrays, input with fewer non-singleton dimensions than the
Similar to *NumPy* arrays, input with fewer non-singleton dimensions than the
`SolutionArray` is 'broadcast' to generate input of the appropriate shape. In
the above example, the single value for the mole fraction input is applied
to each input, while each row has a constant temperature and each column has
a constant pressure.
Computed properties are returned as Numpy arrays with the same shape as the
Computed properties are returned as *NumPy* arrays with the same shape as the
array of states, with additional dimensions appended as necessary for non-
scalar output (e.g. per-species or per-reaction properties)::
Expand All @@ -394,7 +394,7 @@ class SolutionArray:
>>> states.equilibrate('HP')
>>> states.T # -> adiabatic flame temperature at various equivalence ratios
`SolutionArray` objects can also be 'sliced' like Numpy arrays, which can be
`SolutionArray` objects can also be 'sliced' like *NumPy* arrays, which can be
used both for accessing and setting properties::
>>> states = ct.SolutionArray(gas, (6, 10))
Expand Down Expand Up @@ -449,8 +449,8 @@ class SolutionArray:
For HDF export and import, the (optional) keyword argument ``group`` allows
for saving and accessing of multiple solutions in a single container file.
Note that `write_hdf` and `read_hdf` require a working installation of h5py.
The package `h5py` can be installed using pip or conda.
Note that `write_hdf` and `read_hdf` require a working installation of *h5py*.
The package *h5py* can be installed using pip or conda.
:param phase: The `Solution` object used to compute the thermodynamic,
kinetic, and transport properties
Expand Down Expand Up @@ -1141,11 +1141,11 @@ def read_csv(self, filename, normalize=True):

def to_pandas(self, cols=None, *args, **kwargs):
"""
Returns the data specified by ``cols`` in a single pandas DataFrame.
Returns the data specified by ``cols`` in a single `pandas.DataFrame`.
Additional arguments are passed on to `collect_data`. This method works
only with 1D `SolutionArray` objects and requires a working pandas
installation. Use pip or conda to install `pandas` to enable this method.
only with 1D `SolutionArray` objects and requires a working *pandas*
installation. Use pip or conda to install ``pandas`` to enable this method.
"""

if isinstance(_pandas, ImportError):
Expand All @@ -1158,11 +1158,11 @@ def to_pandas(self, cols=None, *args, **kwargs):

def from_pandas(self, df, normalize=True):
"""
Restores `SolutionArray` data from a pandas DataFrame ``df``.
Restores `SolutionArray` data from a `pandas.DataFrame` ``df``.
This method is intendend for loading of data that were previously
exported by `to_pandas`. The method requires a working pandas
installation. The package 'pandas' can be installed using pip or conda.
exported by `to_pandas`. The method requires a working *pandas*
installation. The package ``pandas`` can be installed using pip or conda.
The ``normalize`` argument is passed on to `restore_data` to normalize
mole or mass fractions. By default, ``normalize`` is ``True``.
Expand Down Expand Up @@ -1219,29 +1219,29 @@ def write_hdf(self, filename, *args, cols=None, group=None, subgroup=None,
Dictionary of user-defined attributes added at the group level
(typically used in conjunction with a subgroup argument).
:param mode:
Mode h5py uses to open the output file {'a' to read/write if file
Mode *h5py* uses to open the output file {'a' to read/write if file
exists, create otherwise (default); 'w' to create file, truncate if
exists; 'r+' to read/write, file must exist}.
:param append:
If False, the content of a pre-existing group is deleted before
writing the `SolutionArray` in the first position. If True, the
current `SolutionArray` objects is appended to the group.
:param compression:
Pre-defined h5py compression filters {None, 'gzip', 'lzf', 'szip'}
Pre-defined *h5py* compression filters {None, 'gzip', 'lzf', 'szip'}
used for data compression.
:param compression_opts:
Options for the h5py compression filter; for 'gzip', this
Options for the *h5py* compression filter; for 'gzip', this
corresponds to the compression level {None, 0-9}.
:return:
Group identifier used for storing HDF data.
Arguments ``compression`` and ``compression_opts`` are mapped to parameters
for `h5py.create_dataset`; in both cases, the choices of ``None`` results
in default values set by h5py.
in default values set by *h5py*.
Additional arguments (that is, ``*args`` and ``**kwargs``) are passed on to
`collect_data`; see `collect_data` for further information. This method
requires a working installation of h5py (`h5py` can be installed using
requires a working installation of *h5py* (``h5py`` can be installed using
pip or conda).
"""
if isinstance(_h5py, ImportError):
Expand Down Expand Up @@ -1326,7 +1326,7 @@ def read_hdf(self, filename, group=None, subgroup=None, force=False, normalize=T
the `SolutionArray` information.
The method imports data using `restore_data` and requires a working
installation of h5py (`h5py` can be installed using pip or conda).
installation of *h5py* (``h5py`` can be installed using pip or conda).
"""
if isinstance(_h5py, ImportError):
raise _h5py
Expand Down
10 changes: 5 additions & 5 deletions interfaces/cython/cantera/ctml2yaml.py
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Original file line number Diff line number Diff line change
Expand Up @@ -172,11 +172,11 @@ def float2string(data: float) -> str:
:param data: The floating point data to be formatted.
Uses NumPy's ``format_float_positional()`` and ``format_float_scientific()`` if they
are is available, requires NumPy >= 1.14. In that case, values with magnitude
between 0.01 and 10000 are formatted using ``format_float_positional ()`` and other
values are formatted using ``format_float_scientific()``. If those NumPy functions
are not available, returns the ``repr`` of the input.
Uses *NumPy*'s ``format_float_positional()`` and ``format_float_scientific()`` if
they are is available, requires ``numpy >= 1.14``. In that case, values with
magnitude between 0.01 and 10000 are formatted using ``format_float_positional ()``
and other values are formatted using ``format_float_scientific()``. If those *NumPy*
functions are not available, returns the ``repr`` of the input.
"""
if not HAS_FMT_FLT_POS:
return repr(data)
Expand Down
26 changes: 13 additions & 13 deletions interfaces/cython/cantera/onedim.py
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Original file line number Diff line number Diff line change
Expand Up @@ -104,11 +104,11 @@ def set_initial_guess(self, *args, data=None, group=None, **kwargs):
:param data:
Restart data, which are typically based on an earlier simulation
result. Restart data may be specified using a `SolutionArray`,
pandas' DataFrame, or previously saved CSV or HDF container files.
`pandas.DataFrame`, or previously saved CSV or HDF container files.
Note that restart data do not overwrite boundary conditions.
DataFrame input requires a working installation of pandas, whereas
HDF input requires an installation of h5py. These packages can be
installed using pip or conda (`pandas` and `h5py`, respectively).
DataFrame input requires a working installation of *pandas*, whereas
HDF input requires an installation of *h5py*. These packages can be
installed using pip or conda (``pandas`` and ``h5py``, respectively).
:param key:
Group identifier within a HDF container file (only used in
combination with HDF restart data).
Expand Down Expand Up @@ -463,8 +463,8 @@ def to_pandas(self, species='X', normalize=True):
Boolean flag to indicate whether the mole/mass fractions should
be normalized (default is ``True``)
This method uses `to_solution_array` and requires a working pandas
installation. Use pip or conda to install `pandas` to enable this
This method uses `to_solution_array` and requires a working *pandas*
installation. Use pip or conda to install ``pandas`` to enable this
method.
"""
cols = ('extra', 'T', 'D', species)
Expand All @@ -485,7 +485,7 @@ def from_pandas(self, df, restore_boundaries=True, settings=None):
This method is intendend for loading of data that were previously
exported by `to_pandas`. The method uses `from_solution_array` and
requires a working pandas installation. The package 'pandas' can be
requires a working *pandas* installation. The package ``pandas`` can be
installed using pip or conda.
"""
arr = SolutionArray(self.gas, extra=self.other_components())
Expand Down Expand Up @@ -543,16 +543,16 @@ def write_hdf(self, filename, *args, group=None, species='X', mode='a',
Attribute to use obtaining species profiles, e.g. ``X`` for
mole fractions or ``Y`` for mass fractions.
:param mode:
Mode h5py uses to open the output file {'a' to read/write if file
Mode *h5py* uses to open the output file {'a' to read/write if file
exists, create otherwise (default); 'w' to create file, truncate if
exists; 'r+' to read/write, file must exist}.
:param description:
Custom comment describing the dataset to be stored.
:param compression:
Pre-defined h5py compression filters {None, 'gzip', 'lzf', 'szip'}
Pre-defined *h5py* compression filters {None, 'gzip', 'lzf', 'szip'}
used for data compression.
:param compression_opts:
Options for the h5py compression filter; for 'gzip', this
Options for the *h5py* compression filter; for 'gzip', this
corresponds to the compression level {None, 0-9}.
:param quiet:
Suppress message confirming successful file output.
Expand All @@ -563,7 +563,7 @@ def write_hdf(self, filename, *args, group=None, species='X', mode='a',
Additional arguments (that is, ``*args`` and ``**kwargs``) are passed on to
`SolutionArray.collect_data`. The method exports data using
`SolutionArray.write_hdf` via `to_solution_array` and requires a working
installation of h5py (`h5py` can be installed using pip or conda).
installation of *h5py* (``h5py`` can be installed using pip or conda).
"""
cols = ('extra', 'T', 'D', species)
meta = self.settings
Expand Down Expand Up @@ -603,8 +603,8 @@ def read_hdf(self, filename, group=None, restore_boundaries=True, normalize=True
be normalized (default is ``True``)
The method imports data using `SolutionArray.read_hdf` via
`from_solution_array` and requires a working installation of h5py
(`h5py` can be installed using pip or conda).
`from_solution_array` and requires a working installation of *h5py*
(``h5py`` can be installed using pip or conda).
"""
if restore_boundaries:
domains = range(3)
Expand Down
2 changes: 1 addition & 1 deletion interfaces/cython/cantera/utils.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@ def appdelete():
def use_sparse(sparse=True):
"""
Enable sparse output using `scipy.sparse`. Sparse output requires a working
`scipy` installation. Use pip or conda to install `scipy` to enable this method.
*SciPy* installation. Use pip or conda to install ``scipy`` to enable this method.
"""
global _USE_SPARSE
if sparse and isinstance(_scipy_sparse, ImportError):
Expand Down

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