Test preparation for week 05

.travis.yml

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+## yaml file for travis
+language: python
+python:
+  - "3.8"
+# command to install dependencies
+install:
+  pip install requests pyyaml pytest pytest-cov
+# command to run tests
+script:
+  - cd week05-testing
+  - pytest --cov

MyFirstColabNotebook.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyOPlIfISBZfaHXcsqARRLam",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/goldsmdn/rse-classwork-2020/blob/testing/MyFirstColabNotebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "time.sleep(5)\n",
+        "print (time.ctime())\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "O9oxYXdBIqbw",
+        "outputId": "66a38f09-f582-41ca-9be0-42d3d5ec03bb"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Fri Jan 24 16:34:46 2025\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "5oFavWTQG3eU",
+        "outputId": "bd234d1f-c978-42b1-88ee-1be210fc625c"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Fri Jan 24 16:34:41 2025\n"
+          ]
+        }
+      ],
+      "source": [
+        "import time\n",
+        "print(time.ctime())"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [],
+      "metadata": {
+        "id": "FHVD_VJ3LAK4"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "This is **bold**\n",
+        "This is *italic*\n",
+        "This is ~strikethrough~"
+      ],
+      "metadata": {
+        "id": "L4dShNKlLDlc"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "$\\sqrt{3x-1}+(1+x)^2$"
+      ],
+      "metadata": {
+        "id": "jLFXfJ_kLQbW"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "$e^x = \\sum_{i = 0}^\\infty \\frac{1}{i!}x^i$"
+      ],
+      "metadata": {
+        "id": "wbTdUXr1LhZ5"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "oz5FolwCLpou"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Constraints are\n",
+        "   - $3x_1 + 6x_2 + x_3 =< 28$\n",
+        "   - $7x_1 + 3x_2 + 2x_3 =< 37$\n",
+        "   - $4x_1 + 5x_2 + 2x_3 =< 19$\n",
+        "   - $x_1,x_2,x_3 >=0 $\n",
+        "\n",
+        "The trial vector is calculated as follows:\n",
+        "- $u_i(t) = x_i(t) + \\beta(\\hat{x}(t) − x_i(t)) + \\beta \\sum_{k = 1}^{n_v}(x_{i1,k}(t) − x_{i2,k}(t))$\n",
+        "$f(x_1, x_2) = 20 + e - 20exp(-0.2 \\sqrt {\\frac {1}{n} (x_1^2 + x_2^2)}) - exp (\\frac {1}{n}(cos(2\\pi x_1) + cos(2\\pi x_2))$\n",
+        "\n",
+        "$x ∈ [-5, 5]$\n",
+        ">$A_{m,n} =\n",
+        "   \\begin{pmatrix}\n",
+        "   a_{1,1} > a_{1,2} > \\cdots > a_{1,n} \\\\\n",
+        "   a_{2,1} > a_{2,2} > \\cdots > a_{2,n} \\\\\n",
+        "   \\vdots > \\vdots > \\ddots > \\vdots \\\\\n",
+        "   a_{m,1} > a_{m,2} > \\cdots > a_{m,n}\n",
+        "   \\end{pmatrix}$"
+      ],
+      "metadata": {
+        "id": "84QMwRsxLvWe"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [],
+      "metadata": {
+        "id": "AENi3b1fLxDP"
+      }
+    }
+  ]
+}

week04/quakes.py

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+"""A script to find the biggest earthquake in an online dataset."""
+
+# At the top of the file, import any libraries you will use.
+import requests
+import json
+
+# When you run the file, it should print out the location and magnitude
+# of the biggest earthquake.
+# You can run the file with `python quakes.py` from this directory.
+if __name__ == "__main__":
+    quakes = requests.get("http://earthquake.usgs.gov/fdsnws/event/1/query.geojson",
+                      params={
+                          'starttime': "1900-01-01",
+                          "maxlatitude": "58.723",
+                          "minlatitude": "50.008",
+                          "maxlongitude": "1.67",
+                          "minlongitude": "-9.756",
+                          "minmagnitude": "1",
+                          "endtime": "1999-12-31",
+                          "orderby": "time-asc"}
+                      )
+#initialize variables for the loop
+max_magnitude = 0
+coords = ''
+
+#loop around the structure
+for items in quakes.json()["features"]:
+    events = items['properties']
+    geometries = items['geometry']
+    if events['mag'] > max_magnitude:
+        # new biggest magnitude - reset variables
+        max_magnitude = events['mag']
+        coords= geometries['coordinates']  
+
+
+    # The results are stored in variables
+    # named max_magnitude and coords,
+
+print(f"The maximum magnitude is {max_magnitude} "
+      f"and it occured at coordinates {coords}.")

week04/quakes_graph.py

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+"""A script to plot average earthquake in an online dataset."""
+
+# At the top of the file, import any libraries you will use.
+import requests
+import json
+import datetime
+import time
+import matplotlib.pyplot as plt
+
+#constants
+START = 2000  # start year = need to align to selection below
+POINTS = 21   # number of years considered
+STARTTIME = "2000-01-01" # Start time in string format
+ENDTIME = "2020-12-31"   # End time in string format
+
+# When you run the file, it should graph the average magnitude of quakes by year.
+# You can run the file with `python graphs.py` from this directory.
+if __name__ == "__main__":
+    quakes = requests.get("http://earthquake.usgs.gov/fdsnws/event/1/query.geojson",
+                      params={
+                          'starttime': STARTTIME,
+                          "maxlatitude": "58.723",
+                          "minlatitude": "50.008",
+                          "maxlongitude": "1.67",
+                          "minlongitude": "-9.756",
+                          "minmagnitude": "1",
+                          "endtime": ENDTIME,
+                          "orderby": "time-asc"}
+                      )
+
+#define and initialise lists
+years = [x+ START for x in range(POINTS)]
+counts = [0 for x in range(POINTS)]
+mags = [0 for x in range(POINTS)]
+averages = [0 for x in range(POINTS)]
+#loop around the whole structure
+#find year and update count and mags
+for items in quakes.json()["features"]:
+    events = items['properties']
+    timestring = time.gmtime(events['time']/1000)
+    year = (time.strftime("%Y ", timestring))
+    int_year = int(year)
+    index = int_year - START
+    counts[index] = counts[index]+1
+    mags[index] = mags[index]+events['mag']
+
+# calculate average from counts
+for i in range(POINTS):
+    if counts[i]>0:
+        averages[i] = mags[i]/counts[i]
+
+plt.plot(years, averages, 'ro')
+plt.style.use('ggplot')
+plt.xlabel('Year')
+plt.ylabel('Frequency')
+plt.title('Earthquake analysis by year')
+plt.show()

week05-testing/fixture.yml

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+## fixtures.yaml file#
+- generic:
+    time_range_1: ["2010-01-12 10:00:00", "2010-01-12 12:00:00"]
+    time_range_2: ["2010-01-12 10:30:00", "2010-01-12 10:45:00", 2, 60]
+    expected: 
+        - ["2010-01-12 10:30:00","2010-01-12 10:37:00"]
+        - ["2010-01-12 10:38:00", "2010-01-12 10:45:00"]
+- test_non_overlap:
+    time_range_1: ["2010-01-12 10:00:00", "2010-01-12 12:00:00"]
+    time_range_2: ["2010-01-12 14:30:00", "2010-01-12 14:45:00", 2, 60]
+    expected: 
+        []
+- test_several_interval:
+    time_range_1: ["2010-01-12 10:00:00", "2010-01-12 11:00:00", 2, 60]
+    time_range_2: ["2010-01-12 10:30:00", "2010-01-12 10:45:00", 2, 60]
+    expected: 
+      - ["2010-01-12 10:30:30", "2010-01-12 10:37:00"]
+      - ["2010-01-12 10:38:00", "2010-01-12 10:45:00"]    

week05-testing/passes.py

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+#passes.py
+def iss_passes(lat = 51.482218, lon = -.264547, alt =10, n=5):
+    import requests
+    import json
+    import datetime
+
+    response = requests.get("http://api.open-notify.org/iss-pass.json",
+                                    params={
+                                        "lat": lat,
+                                        "lon": lon,
+                                        "alt": alt,
+                                        "n": n})
+
+
+    passes=response.json()['response']
+
+    print(response)
+
+#    for items in passes:
+#        print 
+
+#    return [(datetime.datetime.fromtimestamp(item['risetime']).strftime("%Y-%m-%d %H:%M:%S"),
+#             (datetime.datetime.fromtimestamp(item['risetime'] + item['duration'])).strftime("%Y-%m-%d %H:%M:%S"))
+#            for item in passes]

week05-testing/test_times.py

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+from times import compute_overlap_time, iss_passes, time_range
+import yaml
+import pytest
+from pytest import raises
+# needed to add to example to get to work.
+import mock
+import datetime
+
+#testing file
+
+with open('fixture.yml', 'r') as yamlfile:
+   fixture = yaml.safe_load(yamlfile)
+
+@pytest.mark.parametrize("test_name", fixture)
+# fixture is a list of dictionaries [{'generic':...}, {'no_overlap':...}, ...]
+
+def test_eval(test_name):
+ # test_name will be a dictionary, e.g. for the first case: {'generic': {'time_range_1':..., 'time_range2':..., 'expected':...}
+    properties = list(test_name.values())[0]
+    first_range = time_range(*properties['time_range_1'])
+    second_range = time_range(*properties['time_range_2'])
+    expected = [(start, stop) for start, stop in properties['expected']]
+    assert compute_overlap_time(first_range, second_range) == expected
+
+def test_time_back():
+
+    start_time = "2010-01-12 12:00:00"
+    end_time = "2010-01-12 10:00:00"
+
+    with raises(ValueError):
+        time_range(start_time, end_time)
+
+class ISS_response:
+    '''
+    This class provides "hardcoded" return values to mock the calls to the online API.
+    '''
+    @property
+    def status_code(self):
+        return 200
+
+    def json(self):
+    #    '''
+    #   mocks the bit from the json output we need from querying the API.
+    #    '''
+        now = datetime.datetime.now().timestamp()
+        return {'message': 'success',
+                'request': {'altitude': 10.0, 'datetime': now, 'latitude': 51.5074, 'longitude': -0.1278, 'passes': 5},
+                'response': [{'duration': 446, 'risetime': now + 88433},
+                             {'duration': 628, 'risetime': now + 94095},
+                             {'duration': 656, 'risetime': now + 99871},
+                             {'duration': 655, 'risetime': now + 105676},
+                             {'duration': 632, 'risetime': now + 111480}]}
+
+def test_iss_passes():
+    with mock.patch("requests.get", new=mock.MagicMock(return_value=ISS_response())) as mymock:
+        iss_over_London = iss_passes(51.5074, -0.1278)
+        mymock.assert_called_with("http://api.open-notify.org/iss-pass.json",
+                                  params={
+                                      "lat": 51.5074,
+                                      "alt":10, # needed to add to example to get to work.
+                                      "lon": -0.1278,
+                                      "n": 5})
+        assert len(iss_over_London) == 5
+        # Create a range from yesterday to next week whether the overlap ranges are still 5
+        yesterday = datetime.datetime.now() - datetime.timedelta(days=1)
+        next_week = datetime.datetime.now() + datetime.timedelta(days=7)
+        large = time_range(f"{yesterday:%Y-%m-%d %H:%M:%S}", f"{next_week:%Y-%m-%d %H:%M:%S}")
+        assert compute_overlap_time(large, iss_over_London) == iss_over_London