Add spectrum output to text file, closes #190 (#192)

* Add initial to_text_file and from_text_file methods

* Enable reading of header data

* Add spectrum1dcollection tests

* Add tests for spectrum1d

* Update from_text_file docstring

* Add Codecov to Github actions

* Force use of {} after Column i: y_data[j]

* Remove from_text_file method

* Simplify header writing

* Small comment correction

* Remove unused import

* Add note that text files cannot be re-read

* Small comment correction

* Update changelog

.github/workflows/run_tests.yml

@@ -38,6 +38,10 @@ jobs:
         with:
           project-token: ${{ secrets.CODACY_PROJECT_TOKEN }}
           coverage-reports: tests_and_analysis/test/reports/coverage.xml
+      - uses: codecov/codecov-action@v2
+        if: startsWith(matrix.os, 'ubuntu')
+        with:
+          files: tests_and_analysis/test/reports/coverage.xml
 
   publish-test-results:
     needs: test

CHANGELOG.rst

@@ -1,6 +1,11 @@
 `Unreleased <https://github.com/pace-neutrons/Euphonic/compare/v0.6.2...HEAD>`_
 ----------
 
+- New Features:
+
+  - New ``Spectrum1D.to_text_file`` and ``Spectrum1DCollection.to_text_file``
+    methods to write to column text files
+
 `v0.6.2 <https://github.com/pace-neutrons/Euphonic/compare/v0.6.1...v0.6.2>`_
 ------
 

euphonic/spectra.py

@@ -3,6 +3,7 @@
 import copy
 import itertools
 import math
+import json
 from numbers import Integral
 from typing import (Any, Dict, List, Optional, overload,
                     Sequence, Tuple, TypeVar, Union, Type, Iterable)
@@ -15,7 +16,7 @@
                          _obj_to_dict, _process_dict)
 from euphonic.readers.castep import read_phonon_dos_data
 from euphonic.util import _get_unique_elems_and_idx
-from euphonic import ureg, Quantity
+from euphonic import ureg, Quantity, __version__
 
 
 class Spectrum(ABC):
@@ -374,6 +375,25 @@ def to_dict(self) -> Dict[str, Any]:
         return _obj_to_dict(self, ['x_data', 'y_data', 'x_tick_labels',
                                    'metadata'])
 
+    def to_text_file(self, filename: str,
+                     fmt: Optional[Union[str, Sequence[str]]] = None) -> None:
+        """
+        Write to a text file. The header contains metadata and unit
+        information, the first column contains x_data and the second
+        column contains y_data. Note that text files written in this
+        format cannot be read back in by Euphonic.
+
+        Parameters
+        ----------
+        filename
+            Name of the text file to write to
+        fmt
+            A format specifier or sequence of specifiers (one for each
+            column), to be passed to numpy.savetxt
+        """
+        spec = Spectrum1DCollection.from_spectra([self])
+        spec.to_text_file(filename, fmt)
+
     @classmethod
     def from_dict(cls: Type[T], d: Dict[str, Any]) -> T:
         """
@@ -733,6 +753,39 @@ def to_dict(self) -> Dict[str, Any]:
         return _obj_to_dict(self, ['x_data', 'y_data', 'x_tick_labels',
                                    'metadata'])
 
+    def to_text_file(self, filename: str,
+                     fmt: Optional[Union[str, Sequence[str]]] = None) -> None:
+        """
+        Write to a text file. The header contains metadata and unit
+        information, the first column is x_data and each subsequent
+        column is a y_data spectrum. Note that text files written in
+        this format cannot be read back in by Euphonic.
+
+        Parameters
+        ----------
+        filename
+            Name of the text file to write to
+        fmt
+            A format specifier or sequence of specifiers (one for each
+            column), to be passed to numpy.savetxt
+        """
+        common_metadata = copy.deepcopy(self.metadata)
+        line_data = common_metadata.pop('line_data',
+                                        [{} for i in self.y_data])
+        header = [f'Generated by Euphonic {__version__}',
+                  f'x_data in ({self.x_data.units})',
+                  f'y_data in ({self.y_data.units})',
+                  f'Common metadata: {json.dumps(common_metadata)}',
+                  f'Column 1: x_data']
+        for i, line in enumerate(line_data):
+            header += [f'Column {i + 2}: y_data[{i}] {json.dumps(line)}']
+        out_data = np.hstack((self.get_bin_centres().magnitude[:, np.newaxis],
+                              self.y_data.transpose().magnitude))
+        kwargs = {'header': '\n'.join(header)}
+        if fmt is not None:
+            kwargs['fmt'] = fmt
+        np.savetxt(filename, out_data, **kwargs)
+
     @classmethod
     def from_dict(cls: Type[T], d) -> T:
         """