Merge pull request #436 from lldelisle/fix_numpy1.24

Fix numpy 1.24

docs/content/installation.rst

@@ -13,7 +13,7 @@ Requirements
 Python dependencies:
 
 * Python >= 3.7
-* numpy >= 1.16
+* numpy >= 1.20
 * intervaltree >= 2.1.0
 * pyBigWig >= 0.3.16
 * hicmatrix >= 15

docs/content/releases/3.8.rst

@@ -18,7 +18,8 @@ Bugfix:
 - Works with gffutils version 0.11.0 where ValueError became gffutils.exceptions.EmptyInputError for empty gtf.
 - The installation instructions have been updated
 - Fixed a small bug in links track with "use_middle" enabled, where midpoints could have different ordering than start points (Thanks to @Jeff1995 ).
-- Fix a bug when plotting gtf in the middle of a large intron
+- Fix a bug when plotting gtf in the middle of a large intron.
+- Support Numpy 1.24, drop support below 1.20
 
 Relax version control on matplotlib:
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

environment.yml

@@ -6,7 +6,7 @@ channels:
    - bioconda
    - conda-forge
 dependencies:
-    - numpy >=1.16
+    - numpy >=1.20
     - matplotlib >=3.1.1,<=3.6.2
     - intervaltree >=2.1.0
     - pybigwig >=0.3.16

pygenometracks/tracks/BedGraphTrack.py

@@ -317,9 +317,9 @@ def plot(self, ax, chrom_region, start_region, end_region):
             x_values = np.asarray([(t[0] + t[1]) / 2
                                    for i, t in enumerate(pos_list)
                                    if not np.isnan(score_list[i])],
-                                  dtype=np.float)
+                                  dtype=float)
             score_list = np.asarray([x for x in score_list if not np.isnan(x)],
-                                    dtype=np.float)
+                                    dtype=float)
         elif self.properties['summary_method'] is not None:
             score_list, x_values = self.get_values_as_bigwig(score_list,
                                                              pos_list,
@@ -366,9 +366,9 @@ def plot(self, ax, chrom_region, start_region, end_region):
                 x_values2 = np.asarray([(t[0] + t[1]) / 2
                                         for i, t in enumerate(pos_list2)
                                         if not np.isnan(score_list2[i])],
-                                       dtype=np.float)
+                                       dtype=float)
                 score_list2 = np.asarray([x for x in score_list2 if not np.isnan(x)],
-                                         dtype=np.float)
+                                         dtype=float)
                 if not all([x1 == x2 for x1, x2 in zip(x_values, x_values2)]):
                     # The x are not compatible we need to extrapolate:
                     new_x = sorted(np.unique(np.concatenate((x_values, x_values2), axis=0)))
@@ -481,7 +481,7 @@ def get_values_as_bdg(self, score_list, pos_list):
         # convert [1, 2, 3 ...] in [1, 1, 2, 2, 3, 3 ...]
         score_list = np.repeat(score_list, 2)
         # convert [(0, 10), (10, 20), (20, 30)] into [0, 10, 10, 20, 20, 30]
-        x_values = np.asarray(sum(pos_list, tuple()), dtype=np.float)
+        x_values = np.asarray(sum(pos_list, tuple()), dtype=float)
 
         if self.properties['nans_to_zeros']:
             score_list[np.isnan(score_list)] = 0

requirements.txt

@@ -1,4 +1,4 @@
-numpy >=1.16
+numpy >=1.20
 matplotlib >=3.1.1,<=3.6.2
 intervaltree >=2.1.0
 pybigwig >=0.3.16

requirements_CI.txt

@@ -1,4 +1,4 @@
-numpy >=1.16
+numpy >=1.20
 matplotlib ==3.6.2 # For the tests locally
 intervaltree >=2.1.0
 pybigwig >=0.3.16

setup.py

@@ -90,7 +90,7 @@ def checkProgramIsInstalled(self, program, args, where_to_download,
             sys.stderr.write(f"Error: {e}")
 
 
-install_requires_py = ["numpy >=1.16",
+install_requires_py = ["numpy >=1.20",
                        "matplotlib >=3.1.1,<=3.6.2",
                        "intervaltree >=2.1.0",
                        "pyBigWig >=0.3.16",