refactoring test_06 and test_08

cyberosa · cyberosa · commit 9f1bf1d5b0c3 · 2023-12-21T17:25:04.000+01:00
diff --git a/nbs/tests/data/mocked_data_test_06.py b/nbs/tests/data/mocked_data_test_06.py
@@ -54,3 +54,12 @@
 df_test_treatment1 = df_test_treatment1.pivot(
     index="ID", columns="Time", values="Heart Rate"
 )
+
+dabest_default_kwargs = dict(
+    ci=95,
+    resamples=5000,
+    random_seed=12345,
+    idx=None,
+    proportional=False,
+    mini_meta=False,
+)
diff --git a/nbs/tests/data/mocked_data_test_08.py b/nbs/tests/data/mocked_data_test_08.py
@@ -13,3 +13,19 @@
     {"Rep1_Yes": rep1_yes, "Rep1_No": rep1_no, "Rep2_Yes": rep2_yes, "Rep2_No": rep2_no}
 )
 N = 6  # Size of each group
+
+# kwargs for Dabest class init.
+dabest_default_kwargs = dict(
+    x=None,
+    y=None,
+    ci=95,
+    resamples=5000,
+    random_seed=12345,
+    proportional=False,
+    delta2=False,
+    experiment=None,
+    experiment_label=None,
+    x1_level=None,
+    paired=None,
+    id_col=None,
+)
diff --git a/nbs/tests/test_06_delta-delta_effsize_pvals.ipynb b/nbs/tests/test_06_delta-delta_effsize_pvals.ipynb
@@ -8,10 +8,8 @@
    "outputs": [],
    "source": [
     "import pytest\n",
-    "import lqrt\n",
     "import numpy as np\n",
-    "import scipy as sp\n",
-    "import pandas as pd"
+    "from math import gamma"
    ]
   },
   {
@@ -21,8 +19,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from dabest._stats_tools import effsize\n",
-    "from dabest import Dabest, PermutationTest"
+    "from dabest import Dabest, PermutationTest\n",
+    "from data.mocked_data_test_06 import df_test, df_test_control, df_test_treatment1, dabest_default_kwargs"
    ]
   },
   {
@@ -32,58 +30,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Data for tests.\n",
-    "# See: Asheber Abebe. Introduction to Design and Analysis of Experiments \n",
-    "# with the SAS, from Example: Two-way RM Design Pg 137.\n",
-    "hr = [72, 78, 71, 72, 66, 74, 62, 69, 69, 66, 84, 80, 72, 65, 75, 71, \n",
-    "      86, 83, 82, 83, 79, 83, 73, 75, 73, 62, 90, 81, 72, 62, 69, 70]\n",
-    "\n",
-    "# Add experiment column\n",
-    "e1 = np.repeat('Treatment1', 8).tolist()\n",
-    "e2 = np.repeat('Control', 8).tolist()\n",
-    "experiment = e1 + e2 + e1 + e2\n",
-    "\n",
-    "# Add a `Drug` column as the first variable\n",
-    "d1 = np.repeat('AX23', 8).tolist()\n",
-    "d2 = np.repeat('CONTROL', 8).tolist()\n",
-    "drug = d1 + d2 + d1 + d2\n",
-    "\n",
-    "# Add a `Time` column as the second variable\n",
-    "t1 = np.repeat('T1', 16).tolist()\n",
-    "t2 = np.repeat('T2', 16).tolist()\n",
-    "time = t1 + t2\n",
-    "\n",
-    "# Add an `id` column for paired data plotting.\n",
-    "id_col = []\n",
-    "for i in range(1, 9):\n",
-    "    id_col.append(str(i)+\"a\")\n",
-    "for i in range(1, 9):\n",
-    "    id_col.append(str(i)+\"c\")\n",
-    "id_col.extend(id_col)\n",
-    "\n",
-    "# Combine samples and gender into a DataFrame.\n",
-    "df_test = pd.DataFrame({'ID'   : id_col,\n",
-    "                   'Drug'      : drug,\n",
-    "                   'Time'      : time, \n",
-    "                   'Experiment': experiment,\n",
-    "                   'Heart Rate': hr\n",
-    "                    })\n",
-    "\n",
-    "\n",
-    "df_test_control = df_test[df_test[\"Experiment\"]==\"Control\"]\n",
-    "df_test_control = df_test_control.pivot(index=\"ID\", columns=\"Time\", values=\"Heart Rate\")\n",
-    "\n",
-    "\n",
-    "df_test_treatment1 = df_test[df_test[\"Experiment\"]==\"Treatment1\"]\n",
-    "df_test_treatment1 = df_test_treatment1.pivot(index=\"ID\", columns=\"Time\", values=\"Heart Rate\")\n",
-    "\n",
-    "\n",
-    "# kwargs for Dabest class init.\n",
-    "dabest_default_kwargs = dict(ci=95, \n",
-    "                            resamples=5000, random_seed=12345,\n",
-    "                            idx=None, proportional=False, mini_meta=False\n",
-    "                            )\n",
-    "\n",
     "# example of unpaired delta-delta calculation\n",
     "unpaired = Dabest(data = df_test, x = [\"Time\", \"Drug\"], y = \"Heart Rate\", \n",
     "                  delta2 = True, experiment = \"Experiment\",\n",
@@ -333,7 +279,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from math import gamma\n",
     "hedges_g = unpaired.hedges_g.results['difference'].to_list()\n",
     "a = 8*2-2\n",
     "fac = gamma(a/2)/(np.sqrt(a/2)*gamma((a-1)/2))\n",
@@ -360,7 +305,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from math import gamma\n",
     "hedges_g = paired.hedges_g.results['difference'].to_list()\n",
     "a = 8*2-2\n",
     "fac = gamma(a/2)/(np.sqrt(a/2)*gamma((a-1)/2))\n",
@@ -387,7 +331,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from math import gamma\n",
     "hedges_g = paired_specified_level.hedges_g.results['difference'].to_list()\n",
     "a = 8*2-2\n",
     "fac = gamma(a/2)/(np.sqrt(a/2)*gamma((a-1)/2))\n",
diff --git a/nbs/tests/test_08_mini_meta_pvals.ipynb b/nbs/tests/test_08_mini_meta_pvals.ipynb
@@ -7,7 +7,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
     "import numpy as np\n",
     "import pytest"
    ]
@@ -21,7 +20,8 @@
    "source": [
     "from dabest._stats_tools import effsize\n",
     "from dabest._stats_tools import confint_2group_diff as ci2g\n",
-    "from dabest import Dabest, PermutationTest"
+    "from dabest import Dabest, PermutationTest\n",
+    "from data.mocked_data_test_08 import df_mini_meta, rep1_yes, rep1_no, rep2_yes, rep2_no, N, dabest_default_kwargs"
    ]
   },
   {
@@ -31,33 +31,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Data for tests.\n",
-    "# See Oehlert, G. W. (2000). A First Course in Design \n",
-    "# and Analysis of Experiments (1st ed.). W. H. Freeman.\n",
-    "# from Problem 16.3 Pg 444.\n",
-    "\n",
-    "rep1_yes = [53.4,54.3,55.9,53.8,56.3,58.6]\n",
-    "rep1_no = [58.2,60.4,62.4,59.5,64.5,64.5]\n",
-    "rep2_yes = [46.5,57.2,57.4,51.1,56.9,60.2]\n",
-    "rep2_no = [49.2,61.6,57.2,51.3,66.8,62.7]\n",
-    "df_mini_meta = pd.DataFrame({\n",
-    "    \"Rep1_Yes\":rep1_yes,\n",
-    "    \"Rep1_No\" :rep1_no,\n",
-    "    \"Rep2_Yes\":rep2_yes,\n",
-    "    \"Rep2_No\" :rep2_no\n",
-    "})\n",
-    "N=6 # Size of each group\n",
-    "\n",
-    "\n",
-    "# kwargs for Dabest class init.\n",
-    "dabest_default_kwargs = dict(x=None, y=None, ci=95, \n",
-    "                            resamples=5000, random_seed=12345,\n",
-    "                            proportional=False, delta2=False, experiment=None, \n",
-    "                            experiment_label=None, x1_level=None, paired=None,\n",
-    "                            id_col=None\n",
-    "                            )\n",
-    "\n",
-    "\n",
     "unpaired = Dabest(data = df_mini_meta, idx =((\"Rep1_No\", \"Rep1_Yes\"), \n",
     "                                             (\"Rep2_No\", \"Rep2_Yes\")), \n",
     "                                             mini_meta=True,\n",
