Update docs because of simulation API changes (#15)

* Updated guide notebook + logging level

* Updating docs notebook and README file

* Fix formatting and update README tldr

* Updated class details and howto documentation

README.md

@@ -55,6 +55,198 @@ Quickstart Example
 The following Jupyter notebook is a good way to get started: [notebook](http://sunpower.github.io/pvfactors/developer/pvfactors_demo.html)
 
 
+TL;DR
+-----
+
+Given some timeseries inputs:
+
+
+```python
+timestamps = np.array([datetime(2017, 8, 31, 11), datetime(2017, 8, 31, 12)])
+solar_zenith = np.array([20., 10.])
+solar_azimuth = np.array([110., 140.])
+array_tilt = np.array([10., 0.])
+array_azimuth = np.array([90., 90.])
+dni = np.array([1000., 300.])
+dhi = np.array([50., 500.])
+```
+
+And some PV array parameters:
+
+
+```python
+pvarray_parameters = {
+    'n_pvrows': 3,  # number of pv rows
+    'pvrow_height': 1.75,  # height of pvrows (measured at center / torque tube)
+    'pvrow_width': 2.44,  # width of pvrows
+    'gcr': 0.4,  # ground coverage ratio
+    'rho_ground': 0.2,  # albedo
+}
+```
+
+The user can quickly run a timeseries simulation using ``pvfactors`` as shown below:
+
+
+```python
+from pvfactors.timeseries import calculate_radiosities_serially_perez
+
+df_registries, _ = calculate_radiosities_serially_perez((
+    pvarray_parameters, timestamps,
+    solar_zenith, solar_azimuth,
+    array_tilt, array_azimuth, dni, dhi))
+```
+
+    Progress: |██████████████████████████████████████████████████| 100.0% Complete
+
+
+If the raw outputs are too detailed for the user, they can be formatted quickly thanks to helper functions:
+
+```python
+from pvfactors.timeseries import get_average_pvrow_outputs
+
+df_avg_outputs = get_average_pvrow_outputs(df_registries,
+                                           values=['qinc', 'isotropic_term', 'reflection_term', 'horizon_term'])
+df_avg_outputs
+```
+
+
+<div>
+<table border="1" class="dataframe">
+  <thead>
+    <tr>
+      <th>pvrow_index</th>
+      <th colspan="10" halign="left">0</th>
+      <th>...</th>
+      <th colspan="10" halign="left">2</th>
+    </tr>
+    <tr>
+      <th>surface_side</th>
+      <th colspan="5" halign="left">back</th>
+      <th colspan="5" halign="left">front</th>
+      <th>...</th>
+      <th colspan="5" halign="left">back</th>
+      <th colspan="5" halign="left">front</th>
+    </tr>
+    <tr>
+      <th>term</th>
+      <th>horizon_term</th>
+      <th>isotropic_term</th>
+      <th>qinc</th>
+      <th>reflection_term</th>
+      <th>shaded</th>
+      <th>horizon_term</th>
+      <th>isotropic_term</th>
+      <th>qinc</th>
+      <th>reflection_term</th>
+      <th>shaded</th>
+      <th>...</th>
+      <th>horizon_term</th>
+      <th>isotropic_term</th>
+      <th>qinc</th>
+      <th>reflection_term</th>
+      <th>shaded</th>
+      <th>horizon_term</th>
+      <th>isotropic_term</th>
+      <th>qinc</th>
+      <th>reflection_term</th>
+      <th>shaded</th>
+    </tr>
+    <tr>
+      <th>timestamps</th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>2017-08-31 11:00:00</th>
+      <td>1.221181</td>
+      <td>0.117972</td>
+      <td>93.339589</td>
+      <td>92.000435</td>
+      <td>False</td>
+      <td>1.640681</td>
+      <td>20.982303</td>
+      <td>1035.231572</td>
+      <td>1.217963e+00</td>
+      <td>False</td>
+      <td>...</td>
+      <td>1.640681</td>
+      <td>0.199001</td>
+      <td>97.261729</td>
+      <td>95.422048</td>
+      <td>False</td>
+      <td>1.640681</td>
+      <td>20.849825</td>
+      <td>1034.889434</td>
+      <td>1.008302e+00</td>
+      <td>False</td>
+    </tr>
+    <tr>
+      <th>2017-08-31 12:00:00</th>
+      <td>0.000000</td>
+      <td>0.863797</td>
+      <td>83.197488</td>
+      <td>82.333691</td>
+      <td>False</td>
+      <td>0.000000</td>
+      <td>206.332401</td>
+      <td>795.442326</td>
+      <td>-5.684342e-14</td>
+      <td>False</td>
+      <td>...</td>
+      <td>0.000000</td>
+      <td>382.033336</td>
+      <td>170.382030</td>
+      <td>-211.651306</td>
+      <td>False</td>
+      <td>0.000000</td>
+      <td>206.332401</td>
+      <td>795.442326</td>
+      <td>-5.684342e-14</td>
+      <td>False</td>
+    </tr>
+  </tbody>
+</table>
+<p>2 rows × 30 columns</p>
+</div>
+
+
+The user can also plot the pv array at a given time of the simulation:
+
+
+```python
+from pvfactors.plot import plot_array_from_registry
+
+f, ax = plt.subplots(figsize=(10, 4))
+plot_array_from_registry(ax, df_registries.set_index('timestamps').loc["2017-8-31 11:00:00", :])
+ax.set_xlim(-2, 15)
+plt.show()
+```
+
+
+![png](pvfactors/docs/_static/pvarray.png)
+
+
 References
 ----------