{"action":"created","comment":{"url":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/comments/96438069","pull_request_review_id":17018726,"id":96438069,"diff_hunk":"@@ -22,9 +22,154 @@\n # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\n # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n from cerebralcortex.kernel.datatypes.window import Window\n+from cerebralcortex.kernel.datatypes.datastream import DataStream\n+import numpy as np\n+\n+# def window(datastream, windowDataStream):\n+#\n+#     rdd = datastream.rdd\n+#     windowRDD = windowDataStream.rdd\n+#\n+#     #Take the defined windows of windowRDD and build this structure: (windowRDD_element (Window), [rdd.DataPoints])\n+#     #convert to key_value pair\n+#     windrdd = windowRDD.map(lambda x: (x[0],list(x[1:3])))\n+#\n+#     #Convert windrdd to a broadcast variable, that can be one-time cached in the worker nodes\n+#     winRDD_broadcast = sc.broadcast(windrdd.collect())\n+#\n+#     #Initialize RDD\n+#     windfinalRDD = sc.parallelize([])\n+#\n+#     #For each winRDD_broadcast value, compute the window_datapointRDD\n+#     for i in range(len(winRDD_broadcast.value)):\n+#         window_datapointRDD = dprdd.filter(lambda t: (t[0]>=winRDD_broadcast.value[i][1][0] and t[0]<=winRDD_broadcast.value[i][1][1]))\n+#         windfRDD = window_datapointRDD.map(lambda x: (winRDD_broadcast.value[i][0],[x])).reduceByKey(lambda x,y:x+y)\n+#         windfinalRDD = sc.union([windfinalRDD,windfRDD])\n+#\n+#     (windfinalRDD.collect())\n+#     return DataStream()\n+\n+def epochAlign(timestamp, offset, after=False):\n+\n+    newTimestamp = Math.floor(timestamp / offset)*offset\n+\n+    if after:\n+        newTimestamp += offset\n+\n+    return newTimestamp\n+\n+#Sliding window function\n+def window_sliding(datastream,window_size,window_offset):\n+    timestamps = [d[0] for d in datastream[:len(datastream)]]\n+    datapoints = [d[1] for d in datastream[:len(datastream)]]\n+    starttime = np.min(timestamps)\n+    endtime = np.max(timestamps)\n+    windowed_datastream = []\n+    for ts in np.arange(starttime,endtime,window_offset):\n+        temp_windows = [i for i,v in enumerate(timestamps) if timestamps[i]>=ts and timestamps[i]<ts+window_size]\n+        temp_windows = [datapoints[t] for t in temp_windows]\n+        windowed_datastream.append(temp_windows)\n+    return windowed_datastream\n+\n+# def window_sliding(datastream, window_size, window_offset):\n+#\n+#     rdd = datastream.get_datapoints()\n+#     cc = datastream.get_cerebralcortex().sc\n+#     timestampRDD = rdd.map(lambda x: x.get_timestamp_epoch())\n+#     # initial_ts = epochAlign(timestampRDD.min(), window_offset, after=False)\n+#     # end_ts = epochAlign(timestampRDD.max(), window_offset, after=True)\n+#\n+#     initial_ts = timestampRDD.min()\n+#     end_ts = timestampRDD.max()\n+#\n+#     winRDD = cc.parallelize([])\n+#     for index, ts in list(enumerate(range(initial_ts, end_ts, window_offset))):\n+#         # winR = cc.parallelize([(index, Window(starttime=ts, endtime=ts+window_size))])\n+#         winR = cc.parallelize([(index, ts, ts+window_size)])\n+#         winRDD = cc.union([winRDD, winR])\n+#\n+#     # print (winRDD)\n+#     # windowRDD = windowDataStream.rdd\n+#\n+#     #Take the defined windows of windowRDD and build this structure: (windowRDD_element (Window), [rdd.DataPoints])\n+#     #convert to key_value pair\n+#     # windrdd = winRDD.map(lambda x: (x[0], x[1].get_time_tuple()))\n+#     windrdd = winRDD.map(lambda x:(x[0],list(x[1:3])))\n+#     # print (windrdd.take(2))\n+#     #Convert windrdd to a broadcast variable, that can be one-time cached in the worker nodes\n+#     winRDD_broadcast = cc.broadcast(windrdd.collect())\n+#\n+#     #Initialize RDD\n+#     windfinalRDD = cc.parallelize([])\n+#\n+#     #For each winRDD_broadcast value, compute the window_datapointRDD\n+#     for i in range(len(winRDD_broadcast.value)):\n+#         window_datapointRDD = rdd.filter(lambda t: (t[0]>=winRDD_broadcast.value[i][1][0] and t[0]<=winRDD_broadcast.value[i][1][1]))\n+#         windfRDD = window_datapointRDD.map(lambda x: (winRDD_broadcast.value[i][0],[x])).reduceByKey(lambda x,y:x+y)\n+#         windfinalRDD = cc.union([windfinalRDD,windfRDD])\n+#\n+#     return windfinalRDD\n+#     # datastream.add_window(windfinalRDD, {'windowType': 'sliding', 'windowSize': window_size, 'windowOffset': window_offset})\n+#\n+#\n+#     # return DataStream.from_datastream(datastream, )\n+\n+# -----------------------------\n+\n+# def window_sliding(datastream):\n+#     window_size = 1200000\n+#     window_offset = 60000\n+#     rdd = datastream.get_datapoints()\n+#     cc = datastream.get_cerebralcortex().sc\n+#     timestampRDD = rdd.map(lambda x: x.get_timestamp_epoch())\n+#     # initial_ts = epochAlign(timestampRDD.min(), window_offset, after=False)\n+#     # end_ts = epochAlign(timestampRDD.max(), window_offset, after=True)\n+#\n+#     initial_ts = timestampRDD.min()\n+#     end_ts = timestampRDD.max()\n+#\n+#     winRDD = cc.parallelize([])\n+#     for index, ts in list(enumerate(range(initial_ts, end_ts, window_offset))):\n+#         winR = cc.parallelize([(index, Window(starttime=ts, endtime=ts+window_size).get_time_tuple)])\n+#         # winR = cc.parallelize([(index, ts, ts+window_size)])\n+#         winRDD = cc.union([winRDD, winR])\n+#\n+#\n+#     # windowRDD = windowDataStream.rdd\n+#\n+#     #Take the defined windows of windowRDD and build this structure: (windowRDD_element (Window), [rdd.DataPoints])\n+#     #convert to key_value pair\n+#     windrdd = winRDD.map(lambda x: (x[0], x[1].get_time_tuple()))\n+#     print (windrdd.take(2))\n+#     #Convert windrdd to a broadcast variable, that can be one-time cached in the worker nodes\n+#     winRDD_broadcast = cc.broadcast(windrdd.collect())\n+#\n+#     #Initialize RDD\n+#     windfinalRDD = cc.parallelize([])\n+#\n+#     #For each winRDD_broadcast value, compute the window_datapointRDD\n+#     for i in range(len(winRDD_broadcast.value)):\n+#         window_datapointRDD = rdd.filter(lambda t: (t[0]>=winRDD_broadcast.value[i][1][0] and t[0]<=winRDD_broadcast.value[i][1][1]))\n+#         windfRDD = window_datapointRDD.map(lambda x: (winRDD_broadcast.value[i][0],[x])).reduceByKey(lambda x,y:x+y)\n+#         windfinalRDD = cc.union([windfinalRDD,windfRDD])\n+#\n+#     return windfinalRDD\n+#     # datastream.add_window(windfinalRDD, {'windowType': 'sliding', 'windowSize': window_size, 'windowOffset': window_offset})\n+#\n+#\n+#     # return DataStream.from_datastream(datastream, )\n+\n+# -----------------------------\n+\n+\n+\n+\n+\n+\n+\n \n \n-def window(datastream, windowsize):\n+def windowTime(datastream, windowsize):","path":"cerebralcortex/kernel/window.py","position":152,"original_position":152,"commit_id":"0eb4432d2e5d26c87a0bbb2f5772d7273973642b","original_commit_id":"0eb4432d2e5d26c87a0bbb2f5772d7273973642b","user":{"login":"twhnat","id":4039067,"avatar_url":"https://avatars.githubusercontent.com/u/4039067?v=3","gravatar_id":"","url":"https://api.github.com/users/twhnat","html_url":"https://github.com/twhnat","followers_url":"https://api.github.com/users/twhnat/followers","following_url":"https://api.github.com/users/twhnat/following{/other_user}","gists_url":"https://api.github.com/users/twhnat/gists{/gist_id}","starred_url":"https://api.github.com/users/twhnat/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/twhnat/subscriptions","organizations_url":"https://api.github.com/users/twhnat/orgs","repos_url":"https://api.github.com/users/twhnat/repos","events_url":"https://api.github.com/users/twhnat/events{/privacy}","received_events_url":"https://api.github.com/users/twhnat/received_events","type":"User","site_admin":false},"body":"Function needs documentation, types, and returns specified.","created_at":"2017-01-17T15:40:23Z","updated_at":"2017-01-17T15:44:08Z","html_url":"https://github.com/MD2Korg/CerebralCortex/pull/2#discussion_r96438069","pull_request_url":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/2","_links":{"self":{"href":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/comments/96438069"},"html":{"href":"https://github.com/MD2Korg/CerebralCortex/pull/2#discussion_r96438069"},"pull_request":{"href":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/2"}}},"pull_request":{"url":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/2","id":101822849,"html_url":"https://github.com/MD2Korg/CerebralCortex/pull/2","diff_url":"https://github.com/MD2Korg/CerebralCortex/pull/2.diff","patch_url":"https://github.com/MD2Korg/CerebralCortex/pull/2.patch","issue_url":"https://api.github.com/repos/MD2Korg/CerebralCortex/issues/2","number":2,"state":"open","locked":false,"title":"Functionality windowing","user":{"login":"Soujanya27","id":9871859,"avatar_url":"https://avatars.githubusercontent.com/u/9871859?v=3","gravatar_id":"","url":"https://api.github.com/users/Soujanya27","html_url":"https://github.com/Soujanya27","followers_url":"https://api.github.com/users/Soujanya27/followers","following_url":"https://api.github.com/users/Soujanya27/following{/other_user}","gists_url":"https://api.github.com/users/Soujanya27/gists{/gist_id}","starred_url":"https://api.github.com/users/Soujanya27/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Soujanya27/subscriptions","organizations_url":"https://api.github.com/users/Soujanya27/orgs","repos_url":"https://api.github.com/users/Soujanya27/repos","events_url":"https://api.github.com/users/Soujanya27/events{/privacy}","received_events_url":"https://api.github.com/users/Soujanya27/received_events","type":"User","site_admin":false},"body":"Added the first version of sliding windowing function with a test main.py file. It would be great if you could please review and suggest further improvements.","created_at":"2017-01-17T09:14:06Z","updated_at":"2017-01-17T15:44:08Z","closed_at":null,"merged_at":null,"merge_commit_sha":"af80ac393b0e35bec0c278d816edf53fe2928dea","assignee":null,"assignees":[],"milestone":null,"commits_url":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/2/commits","review_comments_url":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/2/comments","review_comment_url":"https://api.github.com/repos/MD2Korg/CerebralCortex/pulls/comments{/number}","comments_url":"https://api.github.com/repos/MD2Korg/CerebralCortex/issues/2/comments","statuses_url":"https://api.github.com/repos/MD2Korg/CerebralCortex/statuses/0eb4432d2e5d26c87a0bbb2f5772d7273973642b","head":{"label":"Soujanya27:functionality_windowing","ref":"functionality_windowing","sha":"0eb4432d2e5d26c87a0bbb2f5772d7273973642b","user":{"login":"Soujanya27","id":9871859,"avatar_url":"https://avatars.githubusercontent.com/u/9871859?v=3","gravatar_id":"","url":"https://api.github.com/users/Soujanya27","html_url":"https://github.com/Soujanya27","followers_url":"https://api.github.com/users/Soujanya27/followers","following_url":"https://api.github.com/users/Soujanya27/following{/other_user}","gists_url":"https://api.github.com/users/Soujanya27/gists{/gist_id}","starred_url":"https://api.github.com/users/Soujanya27/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Soujanya27/subscriptions","organizations_url":"https://api.github.com/users/Soujanya27/orgs","repos_url":"https://api.github.com/users/Soujanya27/repos","events_url":"https://api.github.com/users/Soujanya27/events{/privacy}","received_events_url":"https://api.github.com/users/Soujanya27/received_events","type":"User","site_admin":false},"repo":{"id":77116286,"name":"CerebralCortex","full_name":"Soujanya27/CerebralCortex","owner":{"login":"Soujanya27","id":9871859,"avatar_url":"https://avatars.githubusercontent.com/u/9871859?v=3","gravatar_id":"","url":"https://api.github.com/users/Soujanya27","html_url":"https://github.com/Soujanya27","followers_url":"https://api.github.com/users/Soujanya27/followers","following_url":"https://api.github.com/users/Soujanya27/following{/other_user}","gists_url":"https://api.github.com/users/Soujanya27/gists{/gist_id}","starred_url":"https://api.github.com/users/Soujanya27/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Soujanya27/subscriptions","organizations_url":"https://api.github.com/users/Soujanya27/orgs","repos_url":"https://api.github.com/users/Soujanya27/repos","events_url":"https://api.github.com/users/Soujanya27/events{/privacy}","received_events_url":"https://api.github.com/users/Soujanya27/received_events","type":"User","site_admin":false},"private":false,"html_url":"https://github.com/Soujanya27/CerebralCortex","description":null,"fork":true,"url":"https://api.github.com/repos/Soujanya27/CerebralCortex","forks_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/forks","keys_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/keys{/key_id}","collaborators_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/collaborators{/collaborator}","teams_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/teams","hooks_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/hooks","issue_events_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/issues/events{/number}","events_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/events","assignees_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/assignees{/user}","branches_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/branches{/branch}","tags_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/tags","blobs_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/git/blobs{/sha}","git_tags_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/git/tags{/sha}","git_refs_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/git/refs{/sha}","trees_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/git/trees{/sha}","statuses_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/statuses/{sha}","languages_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/languages","stargazers_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/stargazers","contributors_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/contributors","subscribers_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/subscribers","subscription_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/subscription","commits_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/commits{/sha}","git_commits_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/git/commits{/sha}","comments_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/comments{/number}","issue_comment_url":"https://api.github.com/repos/Soujanya27/CerebralCortex/issues/comments{/number}","contents_url"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