update to work with new binarymap (scipy sparse arrays rather than …

…matrices) (#185)

* use `binarymap` v0.7 (`scipy.sparse` arrays rather than matrices)

* remove pin on `urllib3`

CHANGELOG.rst

@@ -6,6 +6,11 @@ All notable changes to this project will be documented in this file.
 
 The format is based on `Keep a Changelog <https://keepachangelog.com>`_.
 
+6.12
+----
+- Switch to using ``scipy.sparse`` arrays rather than matrices to keep up with `this <https://github.com/jbloomlab/binarymap/issues/6>`_ `change <https://github.com/jbloomlab/binarymap/pull/7>`_ to ``binarymap`` (now require ``binarymap`` >= 0.7).
+- Remove pin on ``urllib3``
+
 6.11
 ----
 - In ``lineplot_and_heatmap``, add ``mean_abs`` and ``sum_abs`` as possible site statistics, reflecting the mean and sum of the absolute values of the mutation values.

polyclonal/__init__.py

@@ -29,9 +29,9 @@
 
 """
 
-__author__ = "`the Bloom lab <https://research.fhcrc.org/bloom/en.html>`_"
+__author__ = "`the Bloom lab <https://jbloomlab.org>`_"
 __email__ = "[email protected]"
-__version__ = "6.11"
+__version__ = "6.12"
 __url__ = "https://github.com/jbloomlab/polyclonal"
 
 from polyclonal.alphabets import AAS

polyclonal/polyclonal.py

@@ -1671,7 +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) is scipy.sparse.csr_matrix
+        assert type(dpred_pvs_dparams) is scipy.sparse.csr_array
         residuals = pred_pvs - self._pvs
         loss, dloss_dr = self._scaled_pseudo_huber(delta, residuals, True)
         assert loss.shape == dloss_dr.shape == self._pvs.shape
@@ -2972,7 +2972,7 @@ def _compute_1d_pvs(self, params, one_binarymap, binarymaps, cs, calc_grad=False
         Differs from :meth:`Polyclonal._compute_pv` in that it works if just
         one or multiple BinaryMap objects.
 
-        If `calc_grad` is `True`, also returns `scipy.sparse.csr_matrix`
+        If `calc_grad` is `True`, also returns `scipy.sparse.csr_array`
         of gradient as described in :meth:`Polyclonal._compute_pv`.
 
         """
@@ -3029,7 +3029,7 @@ def _compute_pv(self, params, bmap, cs, calc_grad=False):
             ``p_vc`` is 1D array ordered by concentration and then variant
             variant. So elements are `ivariant + iconcentration * nvariants`,
             and length is nconcentrations * nvariants. If ``calc_grad=True``,
-            then ``dpvc_dparams`` is `scipy.sparse.csr_matrix` of shape
+            then ``dpvc_dparams`` is `scipy.sparse.csr_array` of shape
             (len(params), nconcentrations * nvariants). Note that
             len(params) is nepitopes * (1 + binarylength).
 
@@ -3103,18 +3103,18 @@ 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) is scipy.sparse.coo_matrix
+        assert type(dpvc_dbetaparams) is scipy.sparse.coo_array
         # combine to make dpvc_dparams, noting activities before betas
         # in params
         dpvc_dparams = scipy.sparse.vstack(
             [
-                scipy.sparse.csr_matrix(dpvc_da),
-                scipy.sparse.csr_matrix(dpvc_dn),
-                scipy.sparse.csr_matrix(dpvc_dt),
+                scipy.sparse.csr_array(dpvc_da),
+                scipy.sparse.csr_array(dpvc_dn),
+                scipy.sparse.csr_array(dpvc_dt),
                 dpvc_dbetaparams.tocsr(),
             ]
         )
-        assert type(dpvc_dparams) is scipy.sparse.csr_matrix
+        assert type(dpvc_dparams) is scipy.sparse.csr_array
         assert dpvc_dparams.shape == (len(params), n_vc)
         return p_vc, dpvc_dparams
 

setup.py

@@ -44,7 +44,7 @@
     license="GPLv3",
     install_requires=[
         "altair>=5.0.0",
-        "binarymap>=0.6",
+        "binarymap>=0.7",
         "biopython>=1.79",
         "frozendict>=2.0.7",
         "matplotlib>=3.1",
@@ -54,7 +54,6 @@
         "pyarrow",
         "requests",
         "scipy>=1.7.1",
-        "urllib3==1.26.15",  # https://github.com/googleapis/python-bigquery/issues/1565
     ],
     platforms="Linux and Mac OS X.",
     packages=["polyclonal"],

tests/test_gradients.ipynb

@@ -234,7 +234,7 @@
     "            calc_grad=False,\n",
     "        )\n",
     "        numerical_grad = (p_vc_eps - p_vc) / eps\n",
-    "        analytical_grad = dpvc_dparams[iparam].toarray()\n",
+    "        analytical_grad = dpvc_dparams[[iparam], :].toarray()\n",
     "        diff = numpy.sqrt(((numerical_grad - analytical_grad) ** 2).sum())\n",
     "        mag = numpy.sqrt((analytical_grad**2).sum())\n",
     "        if (diff > 1e-7) or (diff / mag > 1e-3):\n",