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seanlawseanlaw
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Reduced execution time in streaming tutorial
1 parent 616f092 commit f8e128e

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‎docs/Tutorial_Matrix_Profiles_For_Streaming_Data.ipynb‎

Lines changed: 48 additions & 48 deletions
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@@ -262,7 +262,7 @@
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"\n",
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"### The Performance\n",
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"\n",
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"We've basically claimed that incrementally updating our matrix profile with `stumpy.stumpi` is much faster (in total computational time) than performing a full pairwise distance calculation with `stumpy.stump` as each new data point arrives. Let's actually compare the timings by taking a full time series that is 10,000 data points in length and we initialize both approaches with the first 2% of the time series (i.e., the first 200 points) and append a single new data point at each iteration before re-computing the matrix profile:"
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"We've basically claimed that incrementally updating our matrix profile with `stumpy.stumpi` is much faster (in total computational time) than performing a full pairwise distance calculation with `stumpy.stump` as each new data point arrives. Let's actually compare the timings by taking a full time series that is 1,000 data points in length and we initialize both approaches with the first 2% of the time series (i.e., the first 20 points) and append a single new data point at each iteration before re-computing the matrix profile:"
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]
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},
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{
@@ -274,28 +274,28 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"stumpy.stump: 314.9s\n",
278-
"stumpy.stumpi: 16.7s\n"
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"stumpy.stump: 4.5s\n",
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"stumpy.stumpi: 0.4s\n"
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]
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}
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],
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"source": [
283-
"T_full = np.random.rand(10_000)\n",
284-
"T_stream = T_full[:200].copy()\n",
285-
"m = 100\n",
283+
"T_full = np.random.rand(1_000)\n",
284+
"T_stream = T_full[:20].copy()\n",
285+
"m = 10\n",
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"\n",
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"# `stumpy.stump` timing\n",
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"start = time.time()\n",
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"mp = stumpy.stump(T_stream, m)\n",
290-
"for i in range(200, len(T_full)):\n",
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"for i in range(20, len(T_full)):\n",
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" T_stream = np.append(T_stream, T_full[i])\n",
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" mp = stumpy.stump(T_stream, m)\n",
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"stump_time = time.time() - start\n",
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"\n",
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"# `stumpy.stumpi` timing\n",
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"stream = stumpy.stumpi(T_stream, m, egress=False) # Don't egress/remove the oldest data point when streaming\n",
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"start = time.time()\n",
298-
"for i in range(200, len(T_full)):\n",
298+
"for i in range(20, len(T_full)):\n",
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" t = T_full[i]\n",
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" stream.update(t)\n",
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"stumpi_time = time.time() - start\n",
@@ -338,7 +338,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"stumpy.stumpi: 13.5s\n"
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"stumpy.stumpi: 0.3s\n"
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]
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}
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],
@@ -765,42 +765,42 @@
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"</style>\n",
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"\n",
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"<div class=\"animation\">\n",
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" <div class=\"anim-controls\">\n",
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" <i class=\"fa fa-plus\"></i></button>\n",
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" </div>\n",
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" class=\"anim-state\">\n",
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" checked>\n",
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" <input type=\"radio\" name=\"state\" value=\"loop\" id=\"_anim_radio2_1e93c6dd911e4fc0a2f799828d5ca19d\"\n",
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" >\n",
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" >\n",
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" </form>\n",
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" </div>\n",
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"</div>\n",
@@ -810,9 +810,9 @@
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" /* Instantiate the Animation class. */\n",
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" /* The IDs given should match those used in the template above. */\n",
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" (function() {\n",
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" var slider_id = \"_anim_slider1e93c6dd911e4fc0a2f799828d5ca19d\";\n",
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" var img_id = \"_anim_imga55b011d02734fd39f65ee611c7e77c5\";\n",
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" var slider_id = \"_anim_slidera55b011d02734fd39f65ee611c7e77c5\";\n",
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" var loop_select_id = \"_anim_loop_selecta55b011d02734fd39f65ee611c7e77c5\";\n",
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" var frames = new Array(153);\n",
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" \n",
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" frames[0] = \"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAB9AAAAJYCAYAAAA6431rAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90\\\n",
@@ -266127,7 +266127,7 @@
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" /* set a timeout to make sure all the above elements are created before\n",
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" the object is initialized. */\n",
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" setTimeout(function() {\n",
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266130+
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" loop_select_id);\n",
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" }, 0);\n",
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" })()\n",
@@ -266221,22 +266221,22 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
266224-
"Full Matrix Profile: [2.43 2.73 2.83 3.18 2.42 1.46 1.57 0.78 1.17 1.26 1.42 1.93 2.85 2.4\n",
266225-
" 2.48 2.33 1.64 1.58 1.76 1.97 2.58 2.43 2.23 2.21 1.58 1.76 1.97 2.34\n",
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" 1.93 2.22 2.4 1.57 0.78 1.17 1.26 1.55 1.38 1.92 2.1 1.46 1.97 1.65\n",
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" 1.55 1.38 2.06 2.38 2.21 2.4 1.84 2.26 1.64 2.12 2.22 2.05 1.97 1.57\n",
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" 1.42]\n",
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"Left Matrix Profile: [ inf inf inf 3.35 3.03 3.44 3.71 3.97 3.35 2.81 3.38 3.39 4.01 4.01\n",
266230-
" 2.58 2.33 2.61 2.9 2.52 2.68 3.18 2.43 2.23 2.66 1.58 1.76 1.97 2.58\n",
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" 1.93 2.42 2.4 1.57 0.78 1.17 1.26 2.44 2.81 2.34 2.1 1.46 2.01 1.65\n",
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" 1.55 1.38 2.06 2.38 2.21 2.4 1.84 2.26 1.64 2.12 2.22 2.05 1.97 1.57\n",
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" 1.42]\n",
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"Full Matrix Profile Indices: [21 25 26 37 29 39 31 32 33 34 56 28 29 30 31 7 50 24 25 26 27 0 5 46\n",
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" 17 18 19 37 11 52 13 6 7 8 9 42 43 56 8 5 54 34 35 36 37 28 23 24\n",
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" 25 26 16 28 29 32 40 36 10]\n",
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"Left Matrix Profile Indices: [-1 -1 -1 0 0 0 1 2 0 5 5 7 8 5 6 7 11 9 5 6 7 0 5 6\n",
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" 17 18 19 20 11 4 13 6 7 8 9 10 19 10 8 5 33 34 35 36 37 28 23 24\n",
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" 25 26 16 28 29 32 40 36 10]\n"
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"Full Matrix Profile: [1.86 1.75 2.11 1.91 1.76 1.93 2.3 2.03 2.14 2.41 1.66 1.56 1.61 2.11\n",
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" 2.04 1.92 1.73 2.02 2.05 2.32 2.32 1.53 1.61 2.11 2.42 2.2 2.04 1.53\n",
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" 1.52 1.94 1.95 1.76 2.05 1.52 1.94 1.95 1.66 1.56 2.05 2.28 2.04 1.86\n",
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" 1.75 2.11 1.77 1.84 2.02 2.08 2.08 2.51 2.45 2.04 1.77 1.76 1.93 1.76\n",
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" 2.1 ]\n",
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"Left Matrix Profile: [ inf inf inf 2.67 3.46 2.4 2.3 2.84 2.81 2.91 2.75 2.61 2.92 2.41\n",
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" 2.09 1.92 1.73 2.65 3.1 3.28 2.92 2.9 1.61 2.11 2.74 2.86 2.38 1.53\n",
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" 2.12 2.02 2.2 2.28 2.05 1.52 1.94 1.95 1.66 1.56 2.05 2.28 2.04 1.86\n",
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" 1.75 2.11 2.21 1.84 2.02 2.08 2.08 2.51 2.45 2.04 1.77 1.76 1.93 1.76\n",
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" 2.1 ]\n",
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"Full Matrix Profile Indices: [41 42 43 52 53 54 1 33 34 13 36 37 22 23 51 11 12 46 38 54 55 27 12 13\n",
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" 51 30 40 21 33 34 35 55 27 28 29 30 10 11 18 13 26 0 1 2 52 1 17 36\n",
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" 37 8 39 14 44 4 5 31 32]\n",
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"Left Matrix Profile Indices: [-1 -1 -1 0 1 0 1 2 3 4 2 3 4 9 10 11 12 13 0 15 16 17 12 13\n",
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" 14 1 14 21 4 5 25 26 27 28 29 30 10 11 18 13 26 0 1 2 3 1 17 36\n",
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" 37 8 39 14 44 4 5 31 32]\n"
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]
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}
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],

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