From 2c09316f5fe66e6201a5b832ccafbbdb728e653d Mon Sep 17 00:00:00 2001
From: cxan96 <c.p.xanten@gmail.com>
Date: Mon, 7 Jun 2021 18:32:55 +0200
Subject: [PATCH] plots for synthetic dataset

---
 notebooks/ratio_plots.ipynb   | 15 +++++++++++++--
 notebooks/runtime_plots.ipynb | 16 ++++++++++++++--
 2 files changed, 27 insertions(+), 4 deletions(-)

diff --git a/notebooks/ratio_plots.ipynb b/notebooks/ratio_plots.ipynb
index 06d4787..f9a5bba 100644
--- a/notebooks/ratio_plots.ipynb
+++ b/notebooks/ratio_plots.ipynb
@@ -7,7 +7,7 @@
    "outputs": [],
    "source": [
     "from sketching import settings\n",
-    "from sketching.datasets import Dataset, Covertype_Sklearn, KDDCup_Sklearn, Webspam_libsvm\n",
+    "from sketching.datasets import Dataset, Covertype_Sklearn, KDDCup_Sklearn, Webspam_libsvm, Synthetic_Dataset\n",
     "\n",
     "import pandas as pd\n",
     "\n",
@@ -80,7 +80,8 @@
     "    titles = {\n",
     "        \"covertype_sklearn\": \"Covertype\",\n",
     "        \"kddcup_sklearn\": \"Kddcup\",\n",
-    "        \"webspam_libsvm_desparsed\": \"Webspam\"\n",
+    "        \"webspam_libsvm_desparsed\": \"Webspam\",\n",
+    "        \"synthetic_n_100000\": \"Synthetic\"\n",
     "    }\n",
     "\n",
     "    # add SGD\n",
@@ -140,6 +141,16 @@
     "dataset = Webspam_libsvm()\n",
     "make_plot(dataset, x_min=0, x_max=15000, y_min=1, y_max=2)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset = Synthetic_Dataset(n_rows=100000)\n",
+    "make_plot(dataset, x_min=0, x_max=3000, y_min=1, y_max=35)"
+   ]
   }
  ],
  "metadata": {
diff --git a/notebooks/runtime_plots.ipynb b/notebooks/runtime_plots.ipynb
index f0a0f90..3c453b2 100644
--- a/notebooks/runtime_plots.ipynb
+++ b/notebooks/runtime_plots.ipynb
@@ -7,7 +7,7 @@
    "outputs": [],
    "source": [
     "from sketching import settings\n",
-    "from sketching.datasets import Dataset, Covertype_Sklearn, KDDCup_Sklearn, Webspam_libsvm\n",
+    "from sketching.datasets import Dataset, Covertype_Sklearn, KDDCup_Sklearn, Webspam_libsvm, Synthetic_Dataset\n",
     "\n",
     "import pandas as pd\n",
     "\n",
@@ -77,7 +77,8 @@
     "    titles = {\n",
     "        \"covertype_sklearn\": \"Covertype\",\n",
     "        \"kddcup_sklearn\": \"Kddcup\",\n",
-    "        \"webspam_libsvm_desparsed\": \"Webspam\"\n",
+    "        \"webspam_libsvm_desparsed\": \"Webspam\",\n",
+    "        \"synthetic_n_100000\": \"Synthetic\"\n",
     "    }\n",
     "\n",
     "    for cur_method in [\"l2s\", \"uniform\", \"sketching\"]:\n",
@@ -140,6 +141,17 @@
     "make_plot(dataset, x_min=None, x_max=None, y_min=1, y_max=2, sampling_time=False)\n",
     "make_plot(dataset, x_min=None, x_max=None, y_min=1, y_max=2, sampling_time=True)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset = Synthetic_Dataset(n_rows=100000)\n",
+    "make_plot(dataset, x_min=None, x_max=None, y_min=None, y_max=None, sampling_time=False)\n",
+    "make_plot(dataset, x_min=None, x_max=None, y_min=None, y_max=None, sampling_time=True)"
+   ]
   }
  ],
  "metadata": {