Move pysam import in cram.py into function where it's actually used

clodius/tiles/cooler.py

@@ -514,7 +514,7 @@ def make_mats(filepath):
 
         # get the genome size
         resolution = list(f["resolutions"].keys())[0]
-        genome_length = int(sum(f["resolutions"][resolution]["chroms"]["length"]))
+        genome_length = int(np.sum(f["resolutions"][resolution]["chroms"]["length"][:].astype(np.int64)))
 
         info["max_pos"] = [genome_length, genome_length]
         info["min_pos"] = [1, 1]

clodius/tiles/cram.py

@@ -1,10 +1,10 @@
-import pysam
-
 from clodius.tiles.bam import alignment_tileset_info
 from clodius.tiles.bam import alignment_tiles
 
 
 def tileset_info(filename, chromsizes):
+    import pysam
+
     samfile = pysam.AlignmentFile(filename, "rc")
 
     return alignment_tileset_info(samfile, chromsizes)
@@ -13,6 +13,8 @@ def tileset_info(filename, chromsizes):
 def tiles(
     filename, tile_ids, index_filename=None, chromsizes=None, max_tile_width=None
 ):
+    import pysam
+
     samfile = pysam.AlignmentFile(filename, "rc", index_filename=index_filename)
 
     return alignment_tiles(

clodius/tiles/vcf.py

@@ -7,7 +7,6 @@
 from clodius.utils import TILE_OPTIONS_CHAR
 
 
-
 def grouper(n, iterable):
     it = iter(iterable)
     while True:
@@ -51,7 +50,7 @@ def regions(filename, chromsizes, offset, limit):
         limit: The total number of entries to fetch
     """
     from pysam import VariantFile
- 
+
     vcf = VariantFile(filename)  # auto-detect input format
 
     fetcher = vcf.fetch()

notebooks/Aggregating an array.ipynb

@@ -4,7 +4,10 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -15,7 +18,10 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -59,7 +65,10 @@
    "cell_type": "code",
    "execution_count": 24,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -295,7 +304,10 @@
    "cell_type": "code",
    "execution_count": 186,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -329,7 +341,10 @@
    "cell_type": "code",
    "execution_count": 190,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -487,7 +502,10 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -627,7 +645,10 @@
    "cell_type": "code",
    "execution_count": 43,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -1051,7 +1072,10 @@
    "cell_type": "code",
    "execution_count": 279,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -1145,7 +1169,10 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "source": [
     "## Example with n x c data"
@@ -1331,7 +1358,10 @@
    "cell_type": "code",
    "execution_count": 127,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -1384,15 +1414,18 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -1406,9 +1439,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.10.15"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

notebooks/ENSEMBL annotations and RNAseq.ipynb

@@ -4,7 +4,10 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -39,7 +42,10 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -50,7 +56,10 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -229,7 +238,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": []
@@ -238,15 +250,18 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -260,9 +275,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.2"
+   "version": "3.10.15"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

notebooks/h37rv gene annotations.ipynb

@@ -4,7 +4,10 @@
    "cell_type": "code",
    "execution_count": 78,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -209,7 +212,10 @@
    "cell_type": "code",
    "execution_count": 76,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": [
@@ -220,15 +226,18 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -242,9 +251,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.2"
+   "version": "3.10.15"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }