update fcs file creation example

whitews · Oct 24, 2014 · 00b729e · 00b729e
1 parent 049a7bb
commit 00b729e
Showing 1 changed file with 69 additions and 25 deletions.
diff --git a/examples/fabricate_fcs_file.py b/examples/fabricate_fcs_file.py
@@ -3,45 +3,88 @@
 
 
 if __name__ == '__main__':
+    # these clusters have lots of overlap
+    # cluster1 = np.random.multivariate_normal(
+    #     [60000.0, 6000.0, 600.0, 6.0],
+    #     [
+    #         [2000,  100,   10,   10],
+    #         [10,   5000,   10,   10],
+    #         [10,     10, 1000,   10],
+    #         [10,     10,   10,    1]
+    #     ],
+    #     (10000,)
+    # )
+    # cluster2 = np.random.multivariate_normal(
+    #     [-100.0, -5.0, 400.0, 4000.0],
+    #     [
+    #         [10,    100,   10,   10],
+    #         [10,      5,   10,   10],
+    #         [1000,   10,   50,   10],
+    #         [10,     10,   10, 5000]
+    #     ],
+    #     (10000,)
+    # )
+    # cluster3a = np.random.multivariate_normal(
+    #     [25000, 25000.0, 25000.0, 0],
+    #     [
+    #         [1000,    0,    0,    0],
+    #         [0,    1000,    0,    0],
+    #         [0,       0, 1000,    0],
+    #         [0,       0,    0, 1000]
+    #     ],
+    #     (10000,)
+    # )
+    # cluster3b = np.random.multivariate_normal(
+    #     [25000, 0, 25000.0, 25000.0],
+    #     [
+    #         [1000,    0,    0,    0],
+    #         [0,    1000,    0,    0],
+    #         [0,       0, 1000,    0],
+    #         [0,       0,    0, 1000]
+    #     ],
+    #     (10000,)
+    # )
+
+    # these clusters are clearly separated
     cluster1 = np.random.multivariate_normal(
-        [60000.0, 6000.0, 600.0, 6.0],
+        [6000.0, 6000.0, 0.0, 3000.0],
         [
-            [2000,  100,   10,   10],
-            [10,   5000,   10,   10],
-            [10,     10, 1000,   10],
-            [10,     10,   10,    1]
+            [600000,  600000,   0,   0],
+            [300000,   1,   0,   0],
+            [0,     0, 1,   10],
+            [0,     0,   10,    1000]
         ],
-        (10000,)
+        (2000,)
     )
     cluster2 = np.random.multivariate_normal(
-        [-100.0, -5.0, 400.0, 4000.0],
+        [-10.0, 0.0, 0.0, 0.0],
         [
-            [10,    100,   10,   10],
-            [10,      5,   10,   10],
-            [1000,   10,   50,   10],
-            [10,     10,   10, 5000]
+            [10000,    100,   0,   0],
+            [100,      10000,   0,   0],
+            [0,   0,   100000,   0],
+            [0,     0,   0, 1000]
         ],
-        (10000,)
+        (2000,)
     )
     cluster3a = np.random.multivariate_normal(
-        [25000, 25000.0, 25000.0, 0],
+        [7000.0, 2000.0, -6.0, 1500],
         [
-            [1000,    0,    0,    0],
-            [0,    1000,    0,    0],
-            [0,       0, 1000,    0],
-            [0,       0,    0, 1000]
+            [100000,    100,    0,    0],
+            [100,    100000,    100,    0],
+            [0,       100, 10000,    0],
+            [0,       0,    0, 10000]
         ],
-        (10000,)
+        (2000,)
     )
     cluster3b = np.random.multivariate_normal(
-        [25000, 0, 25000.0, 25000.0],
+        [2000.0, 7000.0, 1500.0, -6.0],
         [
-            [1000,    0,    0,    0],
-            [0,    1000,    0,    0],
-            [0,       0, 1000,    0],
-            [0,       0,    0, 1000]
+            [100000,    100,    0,    0],
+            [100,    100000,    100,    0],
+            [0,       100, 10000,    0],
+            [0,       0,    0, 10000]
         ],
-        (10000,)
+        (2000,)
     )
 
     data_set1 = np.vstack(
@@ -67,4 +110,5 @@
         'channel_D'
     ]
 
-    create_fcs(data_set1, channel_names, 'data_set1.fcs')
+    create_fcs(data_set1, channel_names, 'data_set1.fcs')
+    create_fcs(data_set2, channel_names, 'data_set2.fcs')