Display files updated.

plot_scripts/plot_display_com_cap_all.py

@@ -16,7 +16,7 @@ def _build_data_mat(task, cc_1, cc_2, pr, _n_arr):
 
     dir = os.getcwd()
 
-    data_mat = np.zeros((len(package_str), len(_n_arr)))
+    data_mat = np.log(np.zeros((len(package_str), len(_n_arr))))
 
     for p_i, pack in enumerate(package_str):
 

plot_scripts/plot_display_com_prec_all.py

@@ -16,7 +16,7 @@ def _build_data_mat(task, cc, pr_1, pr_2, _n_arr):
 
     dir = os.getcwd()
 
-    data_mat = np.zeros((len(package_str), len(_n_arr)))
+    data_mat = np.log(np.zeros((len(package_str), len(_n_arr))))
 
     for p_i, pack in enumerate(package_str):
 
@@ -25,6 +25,7 @@ def _build_data_mat(task, cc, pr_1, pr_2, _n_arr):
 
         if os.path.isfile(dat_pr1) and os.path.isfile(dat_pr2):
 
+
             h5f_pr1 = h5py.File(dat_pr1, 'r')
             dat_pr1 = h5f_pr1[storage_dict[pack]][:]
             h5f_pr1.close()
@@ -75,11 +76,11 @@ def abs_time_pack(task, cc, N_end, pr_1, pr_2):
 
     if pr_1 == "Single":
         pr_1 = "sp"
-    elif pr_2 == "Double":
-        pr_2 = "dp"
+    elif pr_1 == "Double":
+        pr_1 = "dp"
 
     if pr_2 == "Single":
-        pr_1 = "sp"
+        pr_2 = "sp"
     elif pr_2 == "Double":
         pr_2 = "dp"
 
@@ -118,7 +119,7 @@ def abs_time_pack(task, cc, N_end, pr_1, pr_2):
     # plt.savefig(fn)
     plt.show()
 
-# abs_time_pack("Heisenberg dynamics", "Double", 36, "Singlethread", "Multithread")
+# abs_time_pack("Heisenberg dynamics", "Singlethread", 36, "Double", "Single")
 # abs_time_pack("Random Quantum Circuit", "Double", 36, "Singlethread", "Multithread")
 
 def comp_time_pack(task_1, task_2, cc, N_end, pr_1, pr_2):
@@ -146,9 +147,15 @@ def comp_time_pack(task_1, task_2, cc, N_end, pr_1, pr_2):
 
     if pr_1 == "Single":
         pr_1 = "sp"
+    elif pr_1 == "Double":
+        pr_1 = "dp"
+
+    if pr_2 == "Single":
+        pr_2 = "sp"
     elif pr_2 == "Double":
         pr_2 = "dp"
 
+
     fig, ax = plt.subplots()
 
 

plots_display_all.ipynb

@@ -8,7 +8,7 @@
    "outputs": [
     {
      "data": {
-      "application/mercury+json": "{\n    \"widget\": \"App\",\n    \"title\": \"Performance Benchmarks\",\n    \"description\": \"Collated Performance Benchmarks\",\n    \"show_code\": false,\n    \"show_prompt\": false,\n    \"output\": \"app\",\n    \"schedule\": \"\",\n    \"notify\": \"{}\",\n    \"continuous_update\": true,\n    \"static_notebook\": false,\n    \"show_sidebar\": true,\n    \"full_screen\": true,\n    \"allow_download\": true,\n    \"model_id\": \"mercury-app\",\n    \"code_uid\": \"App.0.40.24.2-rand575588ff\"\n}",
+      "application/mercury+json": "{\n    \"widget\": \"App\",\n    \"title\": \"Performance Benchmarks\",\n    \"description\": \"Collated Performance Benchmarks\",\n    \"show_code\": false,\n    \"show_prompt\": false,\n    \"output\": \"app\",\n    \"schedule\": \"\",\n    \"notify\": \"{}\",\n    \"continuous_update\": true,\n    \"static_notebook\": false,\n    \"show_sidebar\": true,\n    \"full_screen\": true,\n    \"allow_download\": true,\n    \"model_id\": \"mercury-app\",\n    \"code_uid\": \"App.0.40.24.2-rand6ab06af5\"\n}",
       "text/html": [
        "<h3>Mercury Application</h3><small>This output won't appear in the web app.</small>"
       ],
@@ -33,9 +33,9 @@
    "outputs": [
     {
      "data": {
-      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare all\",\n    \"model_id\": \"8fc6f0c5cfcd4cf0b9c8f492973bfe2f\",\n    \"code_uid\": \"Checkbox.0.40.11.1-rand869054f8\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
+      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare all\",\n    \"model_id\": \"7835f9036ce3498f97e52ea76c23d024\",\n    \"code_uid\": \"Checkbox.0.40.11.1-rand3a52d4f8\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8fc6f0c5cfcd4cf0b9c8f492973bfe2f",
+       "model_id": "7835f9036ce3498f97e52ea76c23d024",
        "version_major": 2,
        "version_minor": 0
       },
@@ -48,9 +48,9 @@
     },
     {
      "data": {
-      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare across compute capabilities\",\n    \"model_id\": \"da211301386140ab88c63127ca4afb6c\",\n    \"code_uid\": \"Checkbox.0.40.11.2-rand370209d7\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
+      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare across compute capabilities\",\n    \"model_id\": \"4b9f0bc68f2f4c018ec4be0fb41b5ea8\",\n    \"code_uid\": \"Checkbox.0.40.11.2-rand96a14bb7\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "da211301386140ab88c63127ca4afb6c",
+       "model_id": "4b9f0bc68f2f4c018ec4be0fb41b5ea8",
        "version_major": 2,
        "version_minor": 0
       },
@@ -63,9 +63,9 @@
     },
     {
      "data": {
-      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare one-on-one\",\n    \"model_id\": \"3e2c82d1327e49f1a18996e2b1c7daa4\",\n    \"code_uid\": \"Checkbox.0.40.11.3-randf8131acb\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
+      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare across precision\",\n    \"model_id\": \"e3381e5e2c4f4c63a284230d2f69055f\",\n    \"code_uid\": \"Checkbox.0.40.11.3-rand4bc78cbc\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3e2c82d1327e49f1a18996e2b1c7daa4",
+       "model_id": "e3381e5e2c4f4c63a284230d2f69055f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -78,9 +78,9 @@
     },
     {
      "data": {
-      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare between tasks\",\n    \"model_id\": \"c912f15226ef42089b33a41622898c8c\",\n    \"code_uid\": \"Checkbox.0.40.11.4-rand5cb01cff\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
+      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare one-on-one\",\n    \"model_id\": \"2a39943b849c453f81cf513c5af87efd\",\n    \"code_uid\": \"Checkbox.0.40.11.4-rand4b127455\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c912f15226ef42089b33a41622898c8c",
+       "model_id": "2a39943b849c453f81cf513c5af87efd",
        "version_major": 2,
        "version_minor": 0
       },
@@ -93,9 +93,24 @@
     },
     {
      "data": {
-      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Multi-GPU\",\n    \"model_id\": \"52458e93dabb4cf9a24db4f479338eb4\",\n    \"code_uid\": \"Checkbox.0.40.11.5-rand38d0b2ca\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
+      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Compare between tasks\",\n    \"model_id\": \"2cb81fd3152f46ea8605df67ecc39f6f\",\n    \"code_uid\": \"Checkbox.0.40.11.5-rand852c5407\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "52458e93dabb4cf9a24db4f479338eb4",
+       "model_id": "2cb81fd3152f46ea8605df67ecc39f6f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "mercury.Checkbox"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/mercury+json": "{\n    \"widget\": \"Checkbox\",\n    \"value\": false,\n    \"label\": \"Multi-GPU\",\n    \"model_id\": \"5135bd3a7fff4a22889496727aa63f11\",\n    \"code_uid\": \"Checkbox.0.40.11.6-rand5c1d04aa\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5135bd3a7fff4a22889496727aa63f11",
        "version_major": 2,
        "version_minor": 0
       },
@@ -170,6 +185,18 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "data": {
+      "text/markdown": [
+       "- Compare across different precision: Compare the performance of package(s) with different precision with fixed compute capability"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "text/markdown": [
@@ -379,7 +406,7 @@
     "            task2 = mr.Select(label=\"Select Task: \", value=\"Heisenberg dynamics\", choices=[\"Heisenberg dynamics\", \"Random Quantum Circuit\", \"Quantum Fourier Transform\"])\n",
     "            comp_time_pack(task.value, task2.value, cc.value, N_slider.value+2, com_pr_1.value, com_pr_2.value)\n",
     "            \n",
-    "    elif cc_pack_flag.value == True:\n",
+    "    elif pr_pack_flag.value == True:\n",
     "        \n",
     "        import sys\n",
     "        \n",