improved docs

README.md

@@ -15,11 +15,11 @@ at one place. Currently only 1-dimensional data is supported.
 
 ## How to Install
 
-using `pip`
+You can install SeqMetrics using `pip`
 
     pip install SeqMetrics
 
-or using github link for the latest code
+or using GitHub link for the latest code
 
 	python -m pip install git+https://github.com/AtrCheema/SeqMetrics.git
 
@@ -49,7 +49,7 @@ er.nse()   # calculate Nash Sutcliff efficiency
 er.calculate_all(verbose=True)  # or calculate errors using all available methods 
 ```
 
-We can visualize the calcuated performance metrics if we have [easy_mpl]() package installed.
+We can visualize the calcuated performance metrics if we have [easy_mpl](https://easy-mpl.readthedocs.io) package installed.
 ```python
 import numpy as np
 from SeqMetrics import RegressionMetrics, plot_metrics
@@ -62,12 +62,19 @@ er = RegressionMetrics(true, pred)
 
 plot_metrics(er.calculate_all(),  color="Blues")
 ```
-# ![MLP based model](docs/source/imgs/reg1.png "Title")
-# ![MLP based model](docs/source/imgs/reg2.png "Title")
-# ![MLP based model](docs/source/imgs/reg3.png "Title")
-# ![MLP based model](docs/source/imgs/reg4.png "Title")
 
-Currently following regression performance metrics are being calculated.
+<p float="left">
+  <img src="/docs/source/imgs/reg1.png" width="500" />
+  <img src="/docs/source/imgs/reg2.png" width="500" />
+</p>
+
+<p float="left">
+  <img src="/docs/source/imgs/reg3.png" width="500" />
+  <img src="/docs/source/imgs/reg4.png" width="500" />
+</p>
+
+
+`RegressionMetrics` currently, calculates following performane metrics for regression.
 
 | Name                          | Name in this repository  |
 | -------------------------- | ------------- |

SeqMetrics/utils.py

@@ -33,18 +33,19 @@ def plot_metrics(
         show: bool = True,
         save: bool = False,
         save_path: str = '',
-        **kwargs):
+        **kwargs
+)->None:
     """
     Plots the metrics given as dictionary as radial or bar plot between specified ranges.
 
     Arguments:
-        metrics:
+        metrics : dict
             dictionary whose keys are names are erros and values are error values.
-        ranges:
+        ranges :
             tuple of tuples defining range of errors to plot in one plot
-        exclude:
+        exclude : list
             List of metrics to be excluded from plotting.
-        max_metrics_per_fig:
+        max_metrics_per_fig : int
             maximum number of metrics to show in one figure.
         plot_type:
             either of ``radial`` or ``bar``.
@@ -56,6 +57,9 @@ def plot_metrics(
         kwargs:
             keyword arguments for plotting
 
+    Retuns:
+    None
+
     Examples:
         >>> import numpy as np
         >>> from SeqMetrics import RegressionMetrics
@@ -67,7 +71,7 @@ def plot_metrics(
         >>> plot_metrics(all_errors, plot_type='bar', max_metrics_per_fig=50)
         >>> # or draw the radial plot
         >>> plot_metrics(all_errors, plot_type='radial', max_metrics_per_fig=50)
-    ```
+
     """
     for idx, rng in enumerate(ranges):
         assert rng[1] > rng[0], f'For range {idx}, second value: {rng[1]} is not greater than first value: {rng[0]}. '

docs/source/conf.py

@@ -57,6 +57,12 @@
 # This pattern also affects html_static_path and html_extra_path.
 exclude_patterns = []
 
+# intersphinx configuration
+intersphinx_mapping = {
+    'python': ('https://docs.python.org/{.major}'.format(
+        sys.version_info), None),
+    'numpy': ('https://docs.scipy.org/doc/numpy/', None),
+}
 
 # -- Options for HTML output -------------------------------------------------
 

docs/source/utils.rst

@@ -2,13 +2,8 @@ utility functions
 *****************
 
 
-
-
 Utils
 ========
 .. autoclass:: SeqMetrics.utils.plot_metrics
    :members:
    :undoc-members:
-   :show-inheritance:
-
-   .. automethod:: __init__