update doc links to new Bloom lab webpage

README.rst

@@ -16,7 +16,7 @@ polyclonal
 
 Model mutational escape from polyclonal antibodies using deep mutational scanning data.
 
-``polyclonal`` is a Python package written by `the Bloom lab <https://research.fhcrc.org/bloom/en.html>`_.
+``polyclonal`` is a Python package written by `the Bloom lab <https://jbloomlab.org>`_.
 
 See `Yu et al (2022) <https://doi.org/10.1093/ve/veac110>`_ for an explanation of the approach implemented in ``polyclonal``.
 

docs/acknowledgments.rst

@@ -1,6 +1,6 @@
 Acknowledgements
 -----------------
-``polyclonal`` is written by `the Bloom lab <https://research.fhcrc.org/bloom/en.html>`_.
+``polyclonal`` is written by `the Bloom lab <https://jbloomlab.org>`_.
 
 The citation for ``polyclonal`` is `Yu et al (2022) <https://doi.org/10.1093/ve/veac110>`_.
 

docs/conf.py

@@ -67,7 +67,7 @@
 # General information about the project.
 project = "polyclonal"
 copyright = f"2019--{datetime.datetime.now().year}"  # noqa: A001
-author = "`the Bloom lab <https://research.fhcrc.org/bloom/en.html>`_"
+author = "`the Bloom lab <https://jbloomlab.org/>`_"
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the
@@ -192,7 +192,7 @@
         master_doc,
         "polyclonal.tex",
         "polyclonal Documentation",
-        "`the Bloom lab <https://research.fhcrc.org/bloom/en.html>`_",
+        "`the Bloom lab <https://jbloomlab.org>`_",
         "manual",
     ),
 ]

docs/index.rst

@@ -3,7 +3,7 @@
 
 ``polyclonal`` is a Python package for modeling mutational escape from polyclonal antibodies using deep mutational scanning data.
 
-It is written by `the Bloom lab <https://research.fhcrc.org/bloom/en.html>`_.
+It is written by `the Bloom lab <https://jbloomlab.org>`_.
 
 See `Yu et al (2022) <https://doi.org/10.1093/ve/veac110>`_ for an explanation of the approach implemented in ``polyclonal``.
 

polyclonal/polyclonal.py

@@ -451,7 +451,7 @@ class Polyclonal:
 
     >>> model_data.mutations
     ('M1C', 'G2A', 'A4K', 'A4L')
-    >>> dict(sorted(model_data.mutations_times_seen.items()))
+    >>> {key: int(val) for (key, val) in sorted(model_data.mutations_times_seen.items())}
     {'A4K': 4, 'A4L': 3, 'G2A': 6, 'M1C': 6}
 
     The activities are evenly spaced from 1 to 0, while the mutation escapes
@@ -1652,8 +1652,7 @@ def _scaled_pseudo_huber(delta, r, calc_grad=False):
         ...       lambda r: Polyclonal._scaled_pseudo_huber(2, r, False)[0],
         ...       lambda r: Polyclonal._scaled_pseudo_huber(2, r, True)[1],
         ...       [2])
-        >>> err < 1e-7
-        True
+        >>> assert err < 1e-7
 
         """
         if delta <= 0:
@@ -1672,7 +1671,7 @@ def _loss_dloss(self, params, delta):
         )
         assert pred_pvs.shape == self._pvs.shape
         assert dpred_pvs_dparams.shape == (len(params), len(self._pvs))
-        assert type(dpred_pvs_dparams) == scipy.sparse.csr_matrix
+        assert type(dpred_pvs_dparams) is scipy.sparse.csr_matrix
         residuals = pred_pvs - self._pvs
         loss, dloss_dr = self._scaled_pseudo_huber(delta, residuals, True)
         assert loss.shape == dloss_dr.shape == self._pvs.shape
@@ -1684,7 +1683,7 @@ def _loss_dloss(self, params, delta):
             dloss_dr = dloss_dr * self._weights
         dloss_dparams = dpred_pvs_dparams.dot(dloss_dr)
         assert dloss_dparams.shape == params.shape
-        assert type(dloss_dparams) == numpy.ndarray
+        assert type(dloss_dparams) is numpy.ndarray
         return (loss, dloss_dparams)
 
     def _reg_escape(self, params, weight, delta):
@@ -3104,7 +3103,7 @@ def _compute_pv(self, params, bmap, cs, calc_grad=False):
         dpvc_dbetaparams = dpevc_dbeta.reshape(
             bmap.binarylength * len(self.epitopes), n_vc
         )
-        assert type(dpvc_dbetaparams) == scipy.sparse.coo_matrix
+        assert type(dpvc_dbetaparams) is scipy.sparse.coo_matrix
         # combine to make dpvc_dparams, noting activities before betas
         # in params
         dpvc_dparams = scipy.sparse.vstack(
@@ -3115,7 +3114,7 @@ def _compute_pv(self, params, bmap, cs, calc_grad=False):
                 dpvc_dbetaparams.tocsr(),
             ]
         )
-        assert type(dpvc_dparams) == scipy.sparse.csr_matrix
+        assert type(dpvc_dparams) is scipy.sparse.csr_matrix
         assert dpvc_dparams.shape == (len(params), n_vc)
         return p_vc, dpvc_dparams
 

ruff.toml

@@ -1,11 +1,12 @@
-select = [
+lint.select = [
   "E",   # pycodestyle
   "F",   # pyflakes
   "UP",  # pyupgrade
   "D",   # pydocstyle
 ]
 line-length = 89
 extend-exclude = [
+    "tests",
     "build",
     "dist",
     "docs/_build",
@@ -14,7 +15,7 @@ extend-exclude = [
     "optimization_benchmarks",
     ".*",
 ]
-ignore = [
+lint.ignore = [
     "D203",
     "D205",
     "D212",