Merge pull request #302 from dmgav/debug-pyqt

Compatibility with PyQT 5.15

.github/workflows/isort.yml

@@ -0,0 +1,21 @@
+name: Check Code Style - ISORT
+
+on: [push, pull_request]
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - uses: actions/setup-python@v2
+      - name: Install Dependencies
+        run: |
+          # These packages are installed in the base environment but may be older
+          # versions. Explicitly upgrade them because they often create
+          # installation problems if out of date.
+          python -m pip install --upgrade pip setuptools numpy
+
+          pip install isort
+      - name: Run ISort
+        run: |
+          isort . -c

.github/workflows/testing.yml

@@ -74,7 +74,7 @@ jobs:
 
     - name: Install Conda packages
       run: |
-        set -vxeuo pipefail
+        set -vxeo pipefail
 
         conda install -y \
           python=${{ matrix.python-version }} \
@@ -91,7 +91,7 @@ jobs:
     - name: Install Conda packages (Windows and OSX)
       if: runner.os != 'Linux'
       run: |
-        set -vxeuo pipefail
+        set -vxeo pipefail
 
         # There are issues in building wheels for pystackreg>0.2.2 on OSX, so install pystackreg from CF
         conda install -y pystackreg -c conda-forge

.isort.cfg

@@ -0,0 +1,5 @@
+[settings]
+line_length = 115
+multi_line_output = 3
+include_trailing_comma = True
+profile = black

docs/source/installation.rst

@@ -7,9 +7,6 @@ The easiest way to install PyXRF is to load it into a Conda environment from
 ``conda-forge`` Anaconda channel. Installation instructions are
 identical for all supported OS.
 
-PyXRF is currently not working properly with ``PyQt5`` v5.15, which is the latest available
-version. The instructions show how to install earlier version of ``PyQt5`` from PyPI.
-
 .. note::
 
   **Installation on Windows**: PyXRF can be installed from *conda-forge* only in the environments
@@ -36,15 +33,13 @@ version. The instructions show how to install earlier version of ``PyQt5`` from
 
     $ conda install mamba -n base -c conda-forge
 
-  Then use `mamba` instead of `conda` in all commands. Mamba may not respect pinned versions of
-  packages. Since PyXRF currently does not work with `pyqt` v5.15, explicitly specify the version
-  `"pyqt<5.15"` during installation, for example
+  Then use `mamba` instead of `conda` in all the following commands, for example
 
   .. code:: bash
 
     $ mamba create -n pyxrf-env python=3.9 pip -c conda-forge
     $ mamba activate pyxrf-env
-    $ mamba install pyxrf "pyqt<5.15" -c conda-forge
+    $ mamba install pyxrf -c conda-forge
 
   You may still use `conda` where it works well, e.g. to activate an existing environment.
 
@@ -119,14 +114,15 @@ version. The instructions show how to install earlier version of ``PyQt5`` from
 
    .. code:: bash
 
-       $ pip install pyxrf 'PyQt5<5.15'
+       $ pip install pyxrf PyQt5
+       $ pip install pyxrf 'PyQt5<5.15'  # Older version of PyQT
 
    or from source (editable installation):
 
    .. code:: bash
 
        $ cd <root-directory-of-the-repository>
-       $ pip install 'PyQt5<5.15'
+       $ pip install PyQt5
        $ pip install -e .
 
 Starting PyXRF

pyxrf/__init__.py

@@ -1,5 +1,6 @@
 import logging
 from logging import NullHandler
+
 from ._version import get_versions
 
 __version__ = get_versions()["version"]

pyxrf/api.py

@@ -2,9 +2,10 @@
 # Use 'pyxrf.api_dev' if you are importing PyXRF API into a custom script.
 
 
-from .api_dev import *  # noqa: F401, F403
 from pyxrf import __version__ as pyxrf_version
 
+from .api_dev import *  # noqa: F401, F403
+
 
 def pyxrf_api():
     r"""

pyxrf/api_dev.py

@@ -1,29 +1,27 @@
 # Use this file if you need to import PyXRF APIs into a custom script.
 # Use 'pyxrf.api' if you are interactively importing APIs into an IPython session.
 
-from .model.fileio import stitch_fitted_results  # noqa: F401
-from .model.fileio import spec_to_hdf  # noqa: F401
-from .model.fileio import create_movie  # noqa: F401
+import logging
+
+from .core.map_processing import dask_client_create  # noqa: F401
+from .gui_support.gpc_class import autofind_emission_lines  # noqa: F401, E402
+from .model.command_tools import fit_pixel_data_and_save, pyxrf_batch  # noqa: F401
 from .model.fileio import combine_data_to_recon  # noqa: F401
-from .model.fileio import h5file_for_recon  # noqa: F401
+from .model.fileio import create_movie  # noqa: F401
 from .model.fileio import export_to_view  # noqa: F401
+from .model.fileio import h5file_for_recon  # noqa: F401
 from .model.fileio import make_hdf_stitched  # noqa: F401
-
-from .model.load_data_from_db import make_hdf, export1d  # noqa: F401
-from .model.command_tools import fit_pixel_data_and_save, pyxrf_batch  # noqa: F401
-from .xanes_maps.xanes_maps_api import build_xanes_map  # noqa: F401
-from .simulation.sim_xrf_scan_data import gen_hdf5_qa_dataset, gen_hdf5_qa_dataset_preset_1  # noqa: F401
-from .core.map_processing import dask_client_create  # noqa: F401
-
-from .model.load_data_from_db import save_data_to_hdf5  # noqa: F401, E402
 from .model.fileio import read_data_from_hdf5  # noqa: F401, E402
-
-from .gui_support.gpc_class import autofind_emission_lines  # noqa: F401, E402
+from .model.fileio import spec_to_hdf  # noqa: F401
+from .model.fileio import stitch_fitted_results  # noqa: F401
+from .model.load_data_from_db import save_data_to_hdf5  # noqa: F401, E402
+from .model.load_data_from_db import export1d, make_hdf  # noqa: F401
+from .simulation.sim_xrf_scan_data import gen_hdf5_qa_dataset, gen_hdf5_qa_dataset_preset_1  # noqa: F401
+from .xanes_maps.xanes_maps_api import build_xanes_map  # noqa: F401
 
 # Note:  the statement '# noqa: F401' is telling flake8 to ignore violation F401 at the given line
 #     Violation F401 - the package is imported but unused
 
-import logging
 
 logger = logging.getLogger("pyxrf")
 

pyxrf/core/map_processing.py

@@ -1,19 +1,20 @@
-import numpy as np
+import getpass
+import logging
 import math
 import os
-import h5py
-import dask
-import dask.array as da
-import tempfile
 import platform
-import getpass
+import tempfile
 import time as ttime
-from numba import jit
+
+import dask
+import dask.array as da
+import h5py
+import numpy as np
 from dask.distributed import Client, wait
+from numba import jit
 from progress.bar import Bar
-from .fitting import fit_spectrum
 
-import logging
+from .fitting import fit_spectrum
 
 logger = logging.getLogger(__name__)
 

pyxrf/core/quant_analysis.py

@@ -1,19 +1,21 @@
+import copy
+import json
+import logging
+import math
 import os
-import yaml
+import time as ttime
+
 import jsonschema
 import numpy as np
-import math
-import json
-import copy
-import time as ttime
+import yaml
+
+from .utils import convert_time_to_nexus_string, normalize_data_by_scaler
 from .xrf_utils import (
-    split_compound_mass,
-    generate_eline_list,
-    compute_atomic_scaling_factor,
     check_if_eline_supported,
+    compute_atomic_scaling_factor,
+    generate_eline_list,
+    split_compound_mass,
 )
-from .utils import normalize_data_by_scaler, convert_time_to_nexus_string
-import logging
 
 logger = logging.getLogger(__name__)
 

pyxrf/core/tests/test_fitting.py

@@ -1,8 +1,8 @@
-import pytest
 import numpy as np
 import numpy.testing as npt
+import pytest
 
-from pyxrf.core.fitting import rfactor_compute, _fitting_nnls, _fitting_admm, fit_spectrum
+from pyxrf.core.fitting import _fitting_admm, _fitting_nnls, fit_spectrum, rfactor_compute
 
 # ------------------------------------------------------------------------------
 #  useful functions for generating of datasets for testing of fitting algorithms

pyxrf/core/tests/test_map_processing.py

@@ -1,37 +1,35 @@
-import pytest
-import numpy as np
-import dask.array as da
-import numpy.testing as npt
-import h5py
+import logging
 import os
 import uuid
-from pyxrf.core.fitting import fit_spectrum
 
+import dask.array as da
+import h5py
+import numpy as np
+import numpy.testing as npt
+import pytest
 from skbeam.core.fitting.background import snip_method
 
+from pyxrf.core.fitting import fit_spectrum
 from pyxrf.core.map_processing import (
-    dask_client_create,
+    RawHDF5Dataset,
     TerminalProgressBar,
-    wait_and_display_progress,
-    _compute_optimal_chunk_size,
-    _chunk_numpy_array,
     _array_numpy_to_dask,
-    RawHDF5Dataset,
-    prepare_xrf_map,
+    _chunk_numpy_array,
+    _compute_optimal_chunk_size,
+    _compute_roi,
+    _fit_xrf_block,
     _prepare_xrf_mask,
+    compute_selected_rois,
     compute_total_spectrum,
     compute_total_spectrum_and_count,
-    _fit_xrf_block,
+    dask_client_create,
     fit_xrf_map,
-    _compute_roi,
-    compute_selected_rois,
+    prepare_xrf_map,
     snip_method_numba,
+    wait_and_display_progress,
 )
-
 from pyxrf.core.tests.test_fitting import DataForFittingTest
 
-import logging
-
 logger = logging.getLogger(__name__)
 
 

pyxrf/core/tests/test_quant_analysis.py

@@ -1,30 +1,32 @@
+import copy
 import os
-import pytest
+import re
+import time as ttime
+
 import jsonschema
-import copy
 import numpy as np
 import numpy.testing as npt
-import time as ttime
-import re
-from pyxrf.core.utils import convert_time_from_nexus_string
-from pyxrf.core.xrf_utils import validate_element_str, generate_eline_list, split_compound_mass
+import pytest
+
 from pyxrf.core.quant_analysis import (
-    save_xrf_standard_yaml_file,
-    load_xrf_standard_yaml_file,
+    ParamQuantEstimation,
+    ParamQuantitativeAnalysis,
+    _xrf_quant_fluor_schema,
     _xrf_standard_schema,
-    load_included_xrf_standard_yaml_file,
     compute_standard_element_densities,
-    _xrf_quant_fluor_schema,
-    save_xrf_quant_fluor_json_file,
-    load_xrf_quant_fluor_json_file,
-    get_quant_fluor_data_dict,
     fill_quant_fluor_data_dict,
+    get_quant_fluor_data_dict,
+    load_included_xrf_standard_yaml_file,
+    load_xrf_quant_fluor_json_file,
+    load_xrf_standard_yaml_file,
     prune_quant_fluor_data_dict,
+    save_xrf_quant_fluor_json_file,
+    save_xrf_standard_yaml_file,
     set_quant_fluor_data_dict_optional,
     set_quant_fluor_data_dict_time,
-    ParamQuantEstimation,
-    ParamQuantitativeAnalysis,
 )
+from pyxrf.core.utils import convert_time_from_nexus_string
+from pyxrf.core.xrf_utils import generate_eline_list, split_compound_mass, validate_element_str
 
 # Short example of XRF standard data
 _standard_data_sample = [

pyxrf/core/tests/test_xrf_utils.py

@@ -1,20 +1,22 @@
-import pytest
 import re
+
 import numpy as np
 import numpy.testing as npt
+import pytest
+
 from pyxrf.core.xrf_utils import (
-    get_element_atomic_number,
-    validate_element_str,
-    parse_compound_formula,
-    split_compound_mass,
-    get_supported_eline_list,
-    check_if_eline_supported,
     check_if_eline_is_activated,
-    generate_eline_list,
+    check_if_eline_supported,
+    compute_atomic_scaling_factor,
+    compute_atomic_weight,
     compute_cs,
     compute_cs_ratio,
-    compute_atomic_weight,
-    compute_atomic_scaling_factor,
+    generate_eline_list,
+    get_element_atomic_number,
+    get_supported_eline_list,
+    parse_compound_formula,
+    split_compound_mass,
+    validate_element_str,
 )
 
 

pyxrf/core/tests/test_yaml_param_files.py

@@ -1,7 +1,8 @@
+import os
+
 import jsonschema
 import numpy as np
 import pytest
-import os
 
 from pyxrf.core.yaml_param_files import (
     _parse_docstring_parameters,

pyxrf/core/utils.py

@@ -1,8 +1,8 @@
-import numpy as np
-import scipy
+import logging
 import time as ttime
 
-import logging
+import numpy as np
+import scipy
 
 logger = logging.getLogger(__name__)
 

pyxrf/core/xrf_utils.py

@@ -1,7 +1,7 @@
 import re
-import xraylib
 from distutils.version import LooseVersion
 
+import xraylib
 from skbeam.core.constants import XrfElement as Element
 from skbeam.core.fitting.xrf_model import K_LINE, L_LINE, M_LINE