Linted notebook Z

Author: ipeirotis

notes/Z-Libraries_and_Matplotlib_Example.ipynb

@@ -33,6 +33,7 @@
    "outputs": [],
    "source": [
     "import math\n",
+    "\n",
     "number = 2\n",
     "math.sqrt(number)"
    ]
@@ -44,6 +45,7 @@
    "outputs": [],
    "source": [
     "import math as m\n",
+    "\n",
     "m.log(number)"
    ]
   },
@@ -62,24 +64,14 @@
     "In most cases, the input to matplotlib plotting functions is arrays of numerical types,  floats or integers. "
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# The code below installs the latest version of numpy and matplotlib\n",
-    "!sudo -H pip3 install -U numpy\n",
-    "!sudo -H pip3 install -U matplotlib"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import matplotlib\n",
+    "\n",
     "matplotlib.__version__"
    ]
   },
@@ -90,15 +82,15 @@
    "outputs": [],
    "source": [
     "# used to embed plots inside an ipython notebook\n",
-    "%matplotlib inline \n",
+    "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
     "# really simple example:\n",
-    "y = [1,2,3,4,5,4,3,2,1]\n",
-    "x = [1,2,3,4,5,6,7,8,9]\n",
+    "y = [1, 2, 3, 4, 5, 4, 3, 2, 1]\n",
+    "x = [1, 2, 3, 4, 5, 6, 7, 8, 9]\n",
     "plt.plot(x, y)\n",
-    "plt.plot([1,2,3,4])\n",
-    "plt.ylabel('some numbers')\n",
+    "plt.plot([1, 2, 3, 4])\n",
+    "plt.ylabel(\"some numbers\")\n",
     "plt.show()"
    ]
   },
@@ -110,7 +102,7 @@
    "source": [
     "import numpy as np\n",
     "\n",
-    "X = np.linspace(0, 10, 101) #create values from 0 to 10, and use 101 values\n",
+    "X = np.linspace(0, 10, 101)  # create values from 0 to 10, and use 101 values\n",
     "X"
    ]
   },
@@ -123,17 +115,17 @@
     "import numpy as np\n",
     "import math as math\n",
     "\n",
-    "X = np.linspace(0, 10, 100001) #create values from 0 to 10, and use 10001 values\n",
+    "X = np.linspace(0, 10, 100001)  # create values from 0 to 10, and use 10001 values\n",
     "Y = []\n",
     "\n",
     "for x in X:\n",
     "    y = math.sin(x)\n",
     "    Y.append(y)\n",
-    "    \n",
-    "plt.plot(X, Y, 'mx')\n",
-    "plt.title('The Sine Wave')\n",
-    "plt.xlabel('X')\n",
-    "plt.ylabel('sin(X)')"
+    "\n",
+    "plt.plot(X, Y, \"mx\")\n",
+    "plt.title(\"The Sine Wave\")\n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"sin(X)\")"
    ]
   },
   {
@@ -194,11 +186,11 @@
    "source": [
     "Y = []\n",
     "for x in X:\n",
-    "    y = [math.sin(x), math.cos(x), 0.1*x]\n",
+    "    y = [math.sin(x), math.cos(x), 0.1 * x]\n",
     "    Y.append(y)\n",
     "\n",
     "plt.plot(X, Y)\n",
-    "plt.legend(['sin(x)', 'cos(x)', 'x/10'])"
+    "plt.legend([\"sin(x)\", \"cos(x)\", \"x/10\"])"
    ]
   },
   {
@@ -215,9 +207,9 @@
    "outputs": [],
    "source": [
     "plt.plot(Y)\n",
-    "plt.xlabel('index')\n",
-    "plt.ylabel('f(x)')\n",
-    "plt.legend(['sin(x)', 'cos(x)', 'x/10'])"
+    "plt.xlabel(\"index\")\n",
+    "plt.ylabel(\"f(x)\")\n",
+    "plt.legend([\"sin(x)\", \"cos(x)\", \"x/10\"])"
    ]
   },
   {
@@ -238,10 +230,10 @@
     "for x in X:\n",
     "    Y.append(math.sin(x))\n",
     "    Z.append(math.cos(x))\n",
-    "    \n",
-    "plt.plot(X, Y, 'b-.')\n",
-    "plt.plot(X, Z, 'r--')\n",
-    "plt.legend(['sin(x)', 'cos(x)'])"
+    "\n",
+    "plt.plot(X, Y, \"b-.\")\n",
+    "plt.plot(X, Z, \"r--\")\n",
+    "plt.legend([\"sin(x)\", \"cos(x)\"])"
    ]
   },
   {
@@ -261,7 +253,7 @@
    "source": [
     "vals = [7, 6.2, 3, 5, 9]\n",
     "xval = [1, 2, 3, 4, 5]\n",
-    "plt.bar(xval, vals)\n"
+    "plt.bar(xval, vals)"
    ]
   },
   {
@@ -280,9 +272,9 @@
    "outputs": [],
    "source": [
     "Y = []\n",
-    "for x in range(0,100000):\n",
+    "for x in range(0, 100000):\n",
     "    Y.append(np.random.randn())\n",
-    "    \n",
+    "\n",
     "plt.hist(Y, 50)"
    ]
   },
@@ -310,9 +302,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.8.2"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }