Work on the SasData object definition #156

lucas-wilkins · 2025-08-14T11:05:08Z

Reworked SasData classes

This introduces a new object, the Abscissa object, that describes how the axes data relates to ordinate data.

Useful for testing.

We add the following ignore statements to pycodestyle - E501: Too many pieces of legacy code extend past the line length - W503: This PEP is now considered and anti-pattern and many formatters explicitly (e.g. ruff, black) explicitly ignore it. Reference to anti-pattern: https://peps.python.org/pep-0008/#should-a-line-break-before-or-after-a-binary-operator

Serialise sasdata

codescene-delta-analysis

Code Health Improved (1 files improve in Code Health)

Gates Failed
New code is healthy (1 new file with code health below 9.00)
Enforce critical code health rules (1 file with Bumpy Road Ahead, Deep, Nested Complexity)

Gates Passed
1 Quality Gates Passed

See analysis details in CodeScene

Reason for failure

New code is healthy	Violations	Code Health Impact
abscissa.py	3 rules	10.00 → 8.64	Suppress

Enforce critical code health rules	Violations	Code Health Impact
abscissa.py	2 critical rules	10.00 → 8.64	Suppress

View Improvements

File	Code Health Impact	Categories Improved
transforms.py	9.39 → 10.00	Deep, Nested Complexity

Quality Gate Profile: The Bare Minimum
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codescene-delta-analysis

Gates Failed
New code is healthy (1 new file with code health below 9.00)
Enforce critical code health rules (1 file with Bumpy Road Ahead, Deep, Nested Complexity)

Gates Passed
1 Quality Gates Passed

See analysis details in CodeScene

Reason for failure

New code is healthy	Violations	Code Health Impact
abscissa.py	3 rules	10.00 → 8.64	Suppress

Enforce critical code health rules	Violations	Code Health Impact
abscissa.py	2 critical rules	10.00 → 8.64	Suppress

Quality Gate Profile: The Bare Minimum
Want more control? Customize Code Health rules or catch issues early with our IDE extension and CLI tool.

codescene-delta-analysis

Gates Failed
New code is healthy (1 new file with code health below 9.00)
Enforce critical code health rules (1 file with Bumpy Road Ahead, Deep, Nested Complexity)

Gates Passed
1 Quality Gates Passed

See analysis details in CodeScene

Reason for failure

New code is healthy	Violations	Code Health Impact
abscissa.py	3 rules	10.00 → 8.64	Suppress

Enforce critical code health rules	Violations	Code Health Impact
abscissa.py	2 critical rules	10.00 → 8.64	Suppress

Quality Gate Profile: The Bare Minimum
Want more control? Customize Code Health rules or catch issues early with our IDE extension and CLI tool.

codescene-delta-analysis · 2025-08-14T11:42:42Z

sasdata/abscissa.py

+    def determine(axis_data: list[Quantity[ArrayLike]], ordinate_data: Quantity[ArrayLike]) -> "Abscissa":
+        """ Get an Abscissa object that fits the combination of axes and data"""
+
+        # Different posibilites:
+        #   1: axes_data[i].shape == axes_data[j].shape == ordinate_data.shape
+        #    1a: axis_data[i] is 1D =>
+        #      1a-i:  len(axes_data) == 1 => Grid type or Scatter type depending on sortedness
+        #      1a-ii: len(axes_data) != 1 => Scatter type
+        #    1b: axis_data[i] dimensionality matches len(axis_data) => Meshgrid type
+        #    1c: other => Error
+        #   2: (len(axes_data[0]), len(axes_data[1])... ) == ordinate_data.shape => Grid type
+        #   3: None of the above => Error
+
+        ordinate_shape = np.array(ordinate_data.value).shape
+        axis_arrays = [np.array(axis.value) for axis in axis_data]
+
+        # 1:
+        if all([axis.shape == ordinate_shape for axis in axis_arrays]):
+            # 1a:
+            if all([len(axis.shape)== 1 for axis in axis_arrays]):
+                # 1a-i:
+                if len(axis_arrays) == 1:
+                    # Is it sorted
+                    if is_increasing(axis_arrays[0]):
+                        return GridAbscissa(axis_data)
+                    else:
+                        return ScatterAbscissa(axis_data)
+                # 1a-ii
+                else:
+                    return ScatterAbscissa(axis_data)
+            # 1b
+            elif all([len(axis.shape) == len(axis_arrays) for axis in axis_arrays]):
+
+                return MeshgridAbscissa(axis_data)
+
+            else:
+                raise InterpretationError(Abscissa._determine_error_message(axis_arrays, ordinate_shape))
+
+        elif all([len(axis.shape)== 1 for axis in axis_arrays]) and \
+                tuple([axis.shape[0] for axis in axis_arrays]) == ordinate_shape:
+
+            # Require that they are sorted
+            if all([is_increasing(axis) for axis in axis_arrays]):
+
+                return GridAbscissa(axis_data)
+
+            else:
+                raise InterpretationError("Grid axes are not sorted")
+
+        else:
+            raise InterpretationError(Abscissa._determine_error_message(axis_arrays, ordinate_shape))


❌ New issue: Complex Method
Abscissa.determine has a cyclomatic complexity of 24, threshold = 9

_Suppress

codescene-delta-analysis · 2025-08-14T11:42:43Z

sasdata/abscissa.py

+    def determine(axis_data: list[Quantity[ArrayLike]], ordinate_data: Quantity[ArrayLike]) -> "Abscissa":
+        """ Get an Abscissa object that fits the combination of axes and data"""
+
+        # Different posibilites:
+        #   1: axes_data[i].shape == axes_data[j].shape == ordinate_data.shape
+        #    1a: axis_data[i] is 1D =>
+        #      1a-i:  len(axes_data) == 1 => Grid type or Scatter type depending on sortedness
+        #      1a-ii: len(axes_data) != 1 => Scatter type
+        #    1b: axis_data[i] dimensionality matches len(axis_data) => Meshgrid type
+        #    1c: other => Error
+        #   2: (len(axes_data[0]), len(axes_data[1])... ) == ordinate_data.shape => Grid type
+        #   3: None of the above => Error
+
+        ordinate_shape = np.array(ordinate_data.value).shape
+        axis_arrays = [np.array(axis.value) for axis in axis_data]
+
+        # 1:
+        if all([axis.shape == ordinate_shape for axis in axis_arrays]):
+            # 1a:
+            if all([len(axis.shape)== 1 for axis in axis_arrays]):
+                # 1a-i:
+                if len(axis_arrays) == 1:
+                    # Is it sorted
+                    if is_increasing(axis_arrays[0]):
+                        return GridAbscissa(axis_data)
+                    else:
+                        return ScatterAbscissa(axis_data)
+                # 1a-ii
+                else:
+                    return ScatterAbscissa(axis_data)
+            # 1b
+            elif all([len(axis.shape) == len(axis_arrays) for axis in axis_arrays]):
+
+                return MeshgridAbscissa(axis_data)
+
+            else:
+                raise InterpretationError(Abscissa._determine_error_message(axis_arrays, ordinate_shape))
+
+        elif all([len(axis.shape)== 1 for axis in axis_arrays]) and \
+                tuple([axis.shape[0] for axis in axis_arrays]) == ordinate_shape:
+
+            # Require that they are sorted
+            if all([is_increasing(axis) for axis in axis_arrays]):
+
+                return GridAbscissa(axis_data)
+
+            else:
+                raise InterpretationError("Grid axes are not sorted")
+
+        else:
+            raise InterpretationError(Abscissa._determine_error_message(axis_arrays, ordinate_shape))


❌ New issue: Bumpy Road Ahead
Abscissa.determine has 2 blocks with nested conditional logic. Any nesting of 2 or deeper is considered. Threshold is one single, nested block per function

_Suppress

codescene-delta-analysis · 2025-08-14T11:42:43Z

sasdata/abscissa.py

+    def determine(axis_data: list[Quantity[ArrayLike]], ordinate_data: Quantity[ArrayLike]) -> "Abscissa":
+        """ Get an Abscissa object that fits the combination of axes and data"""
+
+        # Different posibilites:
+        #   1: axes_data[i].shape == axes_data[j].shape == ordinate_data.shape
+        #    1a: axis_data[i] is 1D =>
+        #      1a-i:  len(axes_data) == 1 => Grid type or Scatter type depending on sortedness
+        #      1a-ii: len(axes_data) != 1 => Scatter type
+        #    1b: axis_data[i] dimensionality matches len(axis_data) => Meshgrid type
+        #    1c: other => Error
+        #   2: (len(axes_data[0]), len(axes_data[1])... ) == ordinate_data.shape => Grid type
+        #   3: None of the above => Error
+
+        ordinate_shape = np.array(ordinate_data.value).shape
+        axis_arrays = [np.array(axis.value) for axis in axis_data]
+
+        # 1:
+        if all([axis.shape == ordinate_shape for axis in axis_arrays]):
+            # 1a:
+            if all([len(axis.shape)== 1 for axis in axis_arrays]):
+                # 1a-i:
+                if len(axis_arrays) == 1:
+                    # Is it sorted
+                    if is_increasing(axis_arrays[0]):
+                        return GridAbscissa(axis_data)
+                    else:
+                        return ScatterAbscissa(axis_data)
+                # 1a-ii
+                else:
+                    return ScatterAbscissa(axis_data)
+            # 1b
+            elif all([len(axis.shape) == len(axis_arrays) for axis in axis_arrays]):
+
+                return MeshgridAbscissa(axis_data)
+
+            else:
+                raise InterpretationError(Abscissa._determine_error_message(axis_arrays, ordinate_shape))
+
+        elif all([len(axis.shape)== 1 for axis in axis_arrays]) and \
+                tuple([axis.shape[0] for axis in axis_arrays]) == ordinate_shape:
+
+            # Require that they are sorted
+            if all([is_increasing(axis) for axis in axis_arrays]):
+
+                return GridAbscissa(axis_data)
+
+            else:
+                raise InterpretationError("Grid axes are not sorted")
+
+        else:
+            raise InterpretationError(Abscissa._determine_error_message(axis_arrays, ordinate_shape))


❌ New issue: Deep, Nested Complexity
Abscissa.determine has a nested complexity depth of 4, threshold = 4

_Suppress

jamescrake-merani and others added 30 commits August 11, 2025 16:10

Remove python interpreter header.

b8fb654

Remove this comment as I don't think its true.

74b896c

Skeleton implementation for ordinate and abscissae

10455fe

These are the wrong way round.

8366cd8

Match statements are causing problems; use if.

198c0a3

Implement abscissae for 2D data.

042eb29

Wrote a test for 1d data.

94fcc04

Use the value property.

2589732

2D test.

7769f90

Bring guess into sasdata.

f569126

Bring default logic from SasView here.

6b9f873

Make the default value a param.

29213a6

Function for making the guesses.

6b732f8

Useful for testing.

Forgot return statement.

a426c19

Column unit can be none.

4b3fb72

If there are extra columns than expected, ignore.

4fb53e4

Wrote a test for the ASCII reader.

b855026

Need to get the full filename.

847b966

Don't use filename to get filename :P

d55c377

Property that doesn't include ignore columns.

d0baf0a

It seems I'm a bit sleepy today.

b742d2c

Use the new property.

6cfd4e3

Find can accept more locations in the future.

330a725

Missing import.

e66ff5c

Second test.

f09c7fe

Uncertainties should have the same units.

b2077bb

Add slow cubic interpolation

053d494

Fix first for loop

dd2ad3c

Remove second for loop from conversion_matrix calculation

0729c39

Parameterize tests over interpolation orders

85120f7

rprospero and others added 17 commits August 12, 2025 12:14

Start adding sample details

e66117d

Export process metadata

948759b

Export Instrument and Raw metadata

0037490

Support exporting Quantities

df12d24

Remove unneeded default calls

775170e

Start writing decoder

6ffbaa8

Correctly export sample temperature

bf15104

Fix notes nodes type

c37facd

Decode metadata from json

431e6e8

Use proper bytes for numpy serialisation

ad82625

Fix historical unit errors

0a6b213

Parse MetaNode

e19f214

Use .json extension for JSON files

76ace63

Fix formatting

2d9364b

[pre-commit.ci lite] apply automatic fixes for ruff linting errors

75bd590

Merge pull request #152 from SasView/serialise-sasdata

dcb3fb3

Serialise sasdata

codescene-delta-analysis bot reviewed Aug 14, 2025

View reviewed changes

lucas-wilkins added 3 commits August 14, 2025 12:39

Abscissa basics

7d1cbd6

Abscissa WIP

7af5c33

Fixed check

78bcc6d

lucas-wilkins force-pushed the 148-refactor_24-sasdata-derived-objects branch from 31d7c10 to 78bcc6d Compare August 14, 2025 11:41

[pre-commit.ci lite] apply automatic fixes for ruff linting errors

078cb36

codescene-delta-analysis bot reviewed Aug 14, 2025

View reviewed changes

DrPaulSharp force-pushed the refactor_24 branch from 6e3ba34 to c010919 Compare October 15, 2025 09:49

DrPaulSharp force-pushed the refactor_24 branch 2 times, most recently from d4683bd to 3df6e01 Compare November 7, 2025 17:52

DrPaulSharp force-pushed the refactor_24 branch 2 times, most recently from b32dbfe to 6f3b4af Compare December 9, 2025 12:24

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Work on the SasData object definition #156

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