NRL Evaluated Plasma Chemistry (NEPC)¶

`nepc.nepc`¶

This package provides the following functionality for NRL Evaluated Plasma Chemistry (NEPC) style databases:

create data files for building a NEPC database from common sources (e.g. LXCat)

build a NEPC style database on a MySQL server

establishing a connection to a local or remote database

access cross section data via the CS class

access pre-defined plasma chemistry models via the Model class

curate, visualize, and use cross section data

perform exploratory data analysis (EDA) of cross section data

print statistics about a database (e.g. number of rows in various tables)

Examples

Establish a connection to the database named nepc running on a production server:

>>> cnx, cursor = nepc.connect()

Establish a connection to the database named nepc running on the local machine:

>>> cnx, cursor = nepc.connect(local=True, test=True)

Access the pre-defined plasma chemistry model, fict, in the nepc_test database:

>>> fict = nepc.Model(cursor, "fict")

Print a summary of the fict model, including a stylized Pandas dataframe:

>>> fict.summary()

Additional examples of EDA using nepc are in tests/data/eda. Examples of methods for building data files for the nepc_test database, including parsing LXCat formatted data, are in tests/data/methods.

class nepc.nepc.CS(cursor, cs_id)¶

A cross section data set, including metadata and cross section data, from a NEPC MySQL database.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
cs_id (int) – i.d. of the cross section in cs and csdata tables

metadata¶

cs_idint: id of the cross section in cs and csdata tables
speciestr: name of specie from species table
processstr: name of process from processes table
units_efloat: units of electron energy list e in eV
units_sigmafloat: units of cross section list sigma in m^2
refstr: ref from cs table corresponding to entry in ‘[nepc]/models/ref.bib’
lhsAstr: name of lhsA state from states table
lhsBstr: name of lhsB state from states table
rhsAstr: name of rhsA state from states table
rhsBstr: name of rhsB state from states table
wavelengthfloat: wavelength of photon involved in process in nanometers (nm)
lhs_vint: vibrational energy level of lhs specie
rhs_vint: vibrational energy level of rhs specie
lhs_jint: rotational energy level of lhs specie
rhs_jint: rotational energy level of rhs specie
backgroundstr: background text describing origin of data and other important info
lpufloat: lower percent uncertainty
upufloat: upper percent uncertainty
lhsA_longstr: long_name of lhsA state from states table
lhsB_longstr: long_name of lhsB state from states table
rhsA_longstr: long_name of rhsA state from states table
rhsB_longstr: long_name of rhsB state from states table
e_on_lhsint: number of electrons on lhs
e_on_rhsint: number of electrons on rhs
hv_on_lhsint: photon on lhs? (0 or 1)
hv_on_rhsint: photon on rhs? (0 or 1)
v_on_lhsint: vibrational energy level on lhs? (0 or 1)
v_on_rhsint: vibrational energy level on rhs? (0 or 1)
j_on_lhsint: rotational energy level on lhs? (0 or 1)
j_on_rhsint: rotational energy level on rhs? (0 or 1)

Type: dict

data¶

elist of float: Electron energies in units of units_e eV (see CS.metadata).
sigmalist of float: Cross sections in units of units_sigma \(m^2\) (see CS.metadata).

Type: dict

__len__()¶: The number of data points in the cross section data set

plot(units_sigma=1e-20, plot_param_dict={'linewidth': 1}, xlim_param_dict={'auto': True}, ylim_param_dict={'auto': True}, ylog=False, xlog=False, show_legend=True, filename=None, width=10, height=10)¶

Plot a single cross section data set.

Parameters

units_sigma (float, optional) – desired units of the y-axis in \(m^2\)
plot_param_dict (dict, optional) – kwargs to pass to matplotlib.axes.Axes.plot()
xlim_param_dict (dict, optional) – kwargs to pass to matplotlib.axes.Axes.set_xlim()
ylim_param_dict (dict, optional) – kwargs to pass to matplotlib.axes.Axes.set_ylim()
ylog (bool, optional) – whether y-axis is log scale (default is False)
xlog (bool, optional) – whether x-axis is log scale (default is False)
show_legend (bool, optional) – whether to display the legend or not (default is True)
filename (str, optional) – filename for output, if provided (default is to not output a file)
width (float, optional) – width of plot
height (float, optional) – height of plot

Returns

Plot of the cross section data, CS.data, with formatting using information in the metadata, CS.metadata.

Return type

matplotlib.axes.Axes

class nepc.nepc.CustomCS(cursor=None, cs_id=None, metadata=None, data=None)¶

Extends CS to provide a custom cross section data set.

If building upon an existing CS, must provide cursor and cs_id as well as one or both of metadata and data.

If building a CustomCS from scratch, must provide metadata and data.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
cs_id (int) – i.d. of the cross section in cs and csdata tables
metadata (dict) – one or more of the attributes of CS
data (dict) – same as attributes of CS

metadata¶

see Attributes of CS

Type: dict

data¶

elist[float]: electron energy
sigmalist[float]: cross section

Type: dict

class nepc.nepc.CustomModel(cursor=None, model_name=None, cs_id_list=[], cs_list=[], metadata=None)¶

Extends Model to provide a customized collection of cross sections.

The cross sections can be of class CS (from the NEPC database) or CustomCS (user created/modified). Options:

If building upon an existing NEPC model, must provide cursor and model_name. May also provide a filter to select cross sections that meet criteria.
If building from existing cross sections, must provide cursor and cs_id_list.
If building from a list of custom cross sections, must provide cs_list.

Must do at least one of a, b, or c, and can do any combination thereof.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
model_name (str) – The name of a NEPC model (see [nepc.wiki]/models
cs_id_list (list of int) – List of cs_id’s to pull from NEPC database.
cs_list (list of CustomCS) – List of user-defined cross sections of CustomCS type.
metadata (dict) – Dictionary of filter criteria to select specific CS’s from a Model.

cs¶

A list of cross section data and metadata of CS or CustomCS type.

Type: list of CS or CustomCS

class nepc.nepc.Model(cursor, model_name)¶

A pre-defined collection of cross sections from a NEPC database

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
model_name (str) – Name of a NEPC model (pre-defined collection of cross sections)

cs¶

cross section data in the NEPC format (CS)

Type: list[CS]

unique¶

set with Model.set_unique, all unique electron energies in all CS.data of the Model

Type: list[float]

__len__()¶: number of cross sections in the model

plot(units_sigma=1e-20, process='', plot_param_dict={'linewidth': 1}, xlim_param_dict={'auto': True}, ylim_param_dict={'auto': True}, ylog=False, xlog=False, show_legend=True, filename=None, max_plots=10, width=10, height=10)¶

Plot cross section data in the Model.

Parameters

process (str) – If provided, the process that should be plotted.
units_sigma (float) – Desired units of the y-axis in m^2.
plot_param_dict (dict) – kwargs to pass to ax.plot
xlim(ylim)_param_dict (dict) – dictionary of kwargs to pass to ax.set_x(y)lim
ylog (bool) – whether y-, x-axis is log scale
xlog (bool) – whether y-, x-axis is log scale
show_legend (bool) – whether to display the legend or not
filename (str) – filename for output, if provided (default is to not output a file)
max_cs (int) – maximum number of CS to put on graph

Returns

Plot of the cross section data, CS.data, with formatting using information in the metadata, CS.metadata within the model.

Return type

matplotlib.axes.Axes

set_unique()¶: sets Model.unique

subset(metadata=None)¶

Select the cross sections in the model matching the provided metadata

Parameters: metadata (dict) – see CS.metadata
Returns: cs_subset – cross section data in the NEPC format (CS)
Return type: list[CS]

summary(metadata=None, lower=None, upper=None, sort=[])¶

Summarize the NEPC model.

Prints the following information:

Number of cross sections in the model
Number of cross sections matching metadata, if provided

Returns a stylized Pandas dataframe with headers given by:

headers = [“cs_id”, “specie”, “lhsA”, “rhsA”, “process”,: “reaction”, “threshold”, “E_peak”, “E_upper”, “sigma_max”, “lpu”, “upu”]

Parameters

metadata (dict) – see CS.metadata
lower (int) – lower bound of model index to include in summary
upper (int) – upper bound of model index to include in summary
sort (list[str]) – headers by which the stylized Pandas table is sorted

Returns

cs_df – A stylized Pandas DataFrame containing the cs_id, process, range of electron energies (E_lower, E_upper), maximum sigma (sigma_max), and lpu/upu’s for each cross section in the model (or subset of the model if metadata is provided)

Return type

pandas.io.formats.style.Styler

nepc.nepc.connect(local=False, DBUG=False, test=False)¶

Establish a connection to a NEPC MySQL database

Parameters

local (bool, optional) – Access a database on localhost; otherwise use the production server (default False).
DBUG (bool, optional) – Print debug info (default False).
test (bool, optional) – If true, access the nepc_test database; otherwise, connect to the nepc database.

Returns

cnx (connection.MySQLConnection) – A connection to a NEPC MySQL database.
cursor (cursor.MySQLCursor) – A MySQLCursor object that can execute operations such as SQL statements. cursor interacts with the NEPC server using the cnx connection.

nepc.nepc.count_table_rows(cursor, table: str)¶

Return the number of rows in a MySQL table.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
table (str) – Name of a table in the NEPC database at cursor.

Returns

Number of rows in table.

Return type

int

nepc.nepc.cs_e(cursor, cs_id)¶

Get the electron energies for a cross section dataset in a NEPC database corresponding to a given cs_id.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
cs_id (int) – The cs_id for a cross section dataset in the NEPC database at cursor.

Returns

Electron energies for the cross section dataset corresponding to cs_id.

Return type

list of float

nepc.nepc.cs_e_sigma(cursor, cs_id)¶

Get electron energy and cross section data for a given cs_id in a NEPC database.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
cs_id (int) – The cs_id for a cross section dataset in the NEPC database at cursor.

Returns

list of float – Electron energies for the cross section dataset corresponding to cs_id.
list of float – Cross sections for the cross section dataset corresponding to cs_id.

nepc.nepc.cs_metadata(cursor, cs_id)¶

Get metadata for a given cs_id in a NEPC database.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
cs_id (int) – The cs_id for a cross section dataset in the NEPC database at cursor.

Returns

See CS.metadata. List items are in same order as CS.metadata.

Return type

list

nepc.nepc.cs_sigma(cursor, cs_id)¶

Get the cross sections for a cross section dataset in a NEPC database corresponding to a given cs_id.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
cs_id (int) – The cs_id for a cross section dataset in the NEPC database at cursor.

Returns

Cross sections for the cross section dataset corresponding to cs_id.

Return type

list of float

nepc.nepc.model_cs_id_list(cursor, model_name)¶

Get a list of cs_id’s for a model in a NEPC database.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
model_name (str) – Name of a model in the NEPC MySQL database

Returns

cs_id_list – cs_id’s corresponding to cross sections in the model

Return type

list of int

nepc.nepc.reaction_latex(cs)¶

Return the LaTeX for the process involved in a nepc cross section.

Parameters: cs (CS or CustomCS) – A nepc cross section.
Returns: The LaTeX for the process involved in a NEPC cross section.
Return type: str

nepc.nepc.table_as_df(cursor, table, columns='*')¶

Return a table in a MySQL database as a pandas DataFrame.

Parameters

cursor (cursor.MySQLCursor) – A MySQLCursor object. See return value cursor of connect().
table (str) – Name of a table in the NEPC database at cursor.
columns (list of str, optional) – Which columns to get. (Default is to get all columns.)

Returns

Table in the form of a pandas DataFrame

Return type

DataFrame

`nepc.util.util`¶

Utility methods for the nepc module.

nepc.util.util.get_size(obj, seen=None)¶: Recursively find the size of an object.

nepc.util.util.mkdir(outdir)¶

Try to make a directory and raise an exception if the directory already exists

Parameters: outdir (str) – The directory to be made.

nepc.util.util.rmdir(outdir)¶

Try to remove a tree and raise an exception if this isn’t possible.

Parameters: outdir (str) – The directory to be removed.

nepc.util.util.wc_fxn(file_to_count)¶: Return the number of lines in a file using the commandline utility wc.

`nepc.util.config`¶

Get environment variables used by nepc scripts.

nepc.util.config.nepc_cs_home()¶: Returns the path to the nepc_cs directory.

nepc.util.config.nepc_home()¶: Returns the path to the nepc directory.

nepc.util.config.production()¶: Returns the address of the production server.

nepc.util.config.user_home()¶: Returns the user’s home directory.

`nepc.util.parser`¶

Adapted from BOLOS (https://github.com/aluque/bolos). Adaptations:

replaced ‘next()’ with ‘__next__()’ for Python 3
broke out large comment to add separate dictionary entries for process, param, species, etc.

Notes

This module contains the code required to parse BOLSIG+-compatible files. To make the code re-usabe in other projects it is independent from the rest of the BOLOS code.

Most users would only use the method parse() in this module, which is documented below.

nepc.util.parser.get_next_ids(test=False)¶

Get the next ids from a file

Parameters

test (bool, optional) – If true, the command is run for the nepc_test database. Otherwise, it is run for the nepc database. (Default is the nepc database.)

Returns

int – Next cs_id to use
int – Next csdata_id to use

nepc.util.parser.get_states(test=False)¶: Get lists of name’s and long_name’s from states.tsv file.

nepc.util.parser.parse(filename, has_arg=True, debug=False)¶

Parses a BOLSIG+ cross-sections file.

Parameters

filename (str) – Name of a Bolsig+-compatible cross-sections file.
has_arg (bool, optional) – Whether threshold values are present in each block

Returns

processes – A list with all processes, in dictionary form, included in the file.

Return type

list of dict

Notes

This function does not return process.Process instances so that the parser is independent of the rest of the code and can be re-used in other projects. If you want to convert a process in dictionary form d to a process.Process instance, use

>>> process = process.Process(**d)

nepc.util.parser.remove_crs(mystring)¶: Removes new lines

nepc.util.parser.text_array_to_float_array(text_array, omit_regexp='')¶

Convert an array of strings to an array of floats

Parameters

text_array (str array) –
array of strings to be converted (An) –

Returns

data (float array)
An array of floats containing float-converted data
from text_array

nepc.util.parser.write_cs_to_file(filename, data_array, cs_id, start_csdata_id, specie, process, units_e, units_sigma, ref='\\N', lhs_a='\\N', lhs_b='\\N', rhs_a='\\N', rhs_b='\\N', threshold='-1', wavelength='-1', lhs_v=- 1, rhs_v=- 1, lhs_j=- 1, rhs_j=- 1, background='\\N', lpu='-1', upu='-1')¶: Write both the cross-section data and metadata to a file :param Contains a combination of parameters from write_data_to_file and: :param write_metadata_to_file:

nepc.util.parser.write_data_to_file(data_array, filename, start_csdata_id)¶

Given an array of electron energies and corresponding cross sections, write the data to a file in the correct format for a NEPC database.

Parameters

data_array (numpy.ndarray) – A numpy array of values to be entered into the filenumpy array. Each row is of length 2 (e, sigma).
filename (str) – Name of the file where values of data_array should be written.
start_csdata_id (int) – The first csdata_id for the supplied data.

Returns

The next csdata_id to use.

Return type

int

nepc.util.parser.write_metadata_to_file(filename, cs_id, specie, process, units_e, units_sigma, ref='\\N', lhs_a='\\N', lhs_b='\\N', rhs_a='\\N', rhs_b='\\N', threshold='-1', wavelength='-1', lhs_v=- 1, rhs_v=- 1, lhs_j=- 1, rhs_j=- 1, background='\\N', lpu='-1', upu='-1')¶

Given metadata for a cross section data set, write the metadata to a file in the correct format for a NEPC database.

Parameters

filename (str) – Name of the file where values of data_array should be written.
cs_id (int) – cs_id corresponding to the cross section in the database.
specie (str) – The short name corresponding to the specie in the database.
process (str) – The short name corresponding to the electron scattering process in the database.
units_e (float) – The units, in eV, of the electron energies.
units_sigma (float) – The units, in \(m^2\), of the cross sections.
ref (str) – The short name for the reference corresponding to the dataset.
lhs_a (str) – The short name for the lhs_a state for the process.
lhs_b (str) – The short name for the lhs_b state.
rhs_a (str) – The short name for the rhs_a state.
rhs_b (str) – The short name for the rhs_b state.
threshold (float) – The threshold electron energy for the process.
wavelength (float) – The wavelength of the photon associated with the process, if applicable.
lhs_v (int) – The vibrational energy associated with the LHS state, if applicable.
rhs_v (int) – The vibrational energy associated with the RHS state, if applicable.
lhs_j (int) – The rotational energy associated with the LHS state, if applicable.
rhs_j (int) – The rotational energy associated with the RHS state, if applicable.
background (str) – Background information for the cross section data.
lpu (float) – Lower percent uncertainty of the cross section data.
upu (float) – Upper percent uncertainty of the cross section data.

Returns

The next cs_id to use.

Return type

int

nepc.util.parser.write_models_to_file(filename, models_array)¶

Write model data to a file.

Parameters

filename (str) – The name of the file where the model data should be stored.
models_array (list of str) – A list of models that should be added to filename.

nepc.util.parser.write_next_id_to_file(next_cs_id, next_csdata_id, test=False)¶

Write out the next id’s for the database to a file.

Parameters

next_cs_id (int) – The next cs_id to use
next_csdata_id (int) – The next csdata_id to use
test (bool, optional) – If true, the command is run for the nepc_test database. Otherwise, it is run for the nepc database. (Default is the nepc database.)

nepc.util.parser.write_pd_data_to_file(data_frame, filename, start_csdata_id)¶

Given a dataframe of csdata, write this to a file in the correct format :param data_frame: :type data_frame: pandas DataFrame :param A DataFrame containing cross section data to be entered into the file: :param filename: :type filename: file :param Name of the file where values of data_frame should be entered: :param start_cs_data_id: :type start_cs_data_id: int :param The id where the data should be placed:

Returns

csdata_id
The next csdata_id to use

NRL Evaluated Plasma Chemistry (NEPC)¶

`nepc.nepc`¶

`nepc.util.util`¶

`nepc.util.config`¶

`nepc.util.parser`¶

Other Topics¶

Indices and tables¶

Table of Contents

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NRL Evaluated Plasma Chemistry (NEPC)¶

nepc.nepc¶

nepc.util.util¶

nepc.util.config¶

nepc.util.parser¶

Other Topics¶

Indices and tables¶

`nepc.nepc`¶

`nepc.util.util`¶

`nepc.util.config`¶

`nepc.util.parser`¶