Fixed docstrings and examples.

pytplot/timebar.py

@@ -1,96 +1,134 @@
-# Copyright 2018 Regents of the University of Colorado. All Rights Reserved.
-# Released under the MIT license.
-# This software was developed at the University of Colorado's Laboratory for Atmospheric and Space Physics.
-# Verify current version before use at: https://github.com/MAVENSDC/PyTplot
-
 from . import tplot_utilities
 import pytplot
 import logging
 
-def timebar(t, varname = None, databar = False, delete = False, color = 'black', thick = 1, dash = False):    
+
+def timebar(t, varname=None, databar=False, delete=False, color="black", thick=1, dash=False):
     """
     This function will add a vertical bar to all time series plots.  This is useful if you
-    want to bring attention to a specific time.  
-    
+    want to bring attention to a specific time.
+
     Parameters:
-        t : flt/list
+        t : float/list
             The time in seconds since Jan 01 1970 to place the vertical bar.  If a list of numbers are supplied,
-            multiple bars will be created.  If "databar" is set, then "t" becomes the point on the y axis to 
-            place a horizontal bar.  
+            multiple bars will be created.  If "databar" is set, then "t" becomes the point on the y axis to
+            place a horizontal bar.
         varname : str/list, optional
-            The variable(s) to add the vertical bar to.  If not set, the default is to add it to all current plots.  
+            The variable(s) to add the vertical bar to.  If not set, the default is to add it to all current plots.
         databar : bool, optional
-            This will turn the timebar into a horizontal data bar.  If this is set True, then variable "t" becomes 
-            the point on the y axis to place a horizontal bar.  
+            This will turn the timebar into a horizontal data bar.  If this is set True, then variable "t" becomes
+            the point on the y axis to place a horizontal bar.
         delete : bool, optional
             If set to True, at lease one varname must be supplied.  The timebar at point "t" for variable "varname"
-            will be removed.  
+            will be removed.
         color : str
             The color of the bar
         thick : int
             The thickness of the bar
         dash : bool
             If set to True, the bar is dashed rather than solid
-            
+
     Returns:
         None
-    
+
     Examples:
         >>> # Place a green time bar at 2017-07-17 00:00:00
         >>> import pytplot
         >>> pytplot.timebar(1500249600, color='green')
-        
+
         >>> # Place a dashed data bar at 5500 on the y axis
         >>> pytplot.timebar(5500, dashed=True, databar=True)
-        
-        >>> Place 3 magenta time bars of thickness 5 
+
+        >>> Place 3 magenta time bars of thickness 5
             at [2015-12-26 05:20:01, 2015-12-26 08:06:40, 2015-12-26 08:53:19]
             for variable 'sgx' plot
         >>> pytplot.timebar([1451107201,1451117200,1451119999],'sgx',color='m',thick=5)
 
     """
-
+    """
+    This function will add a vertical bar to all time series plots. This is useful if you
+    want to bring attention to a specific time.
+
+    Parameters
+    ----------
+    t : float or list
+        The time in seconds since Jan 01 1970 to place the vertical bar. If a list of numbers are supplied,
+        multiple bars will be created. If "databar" is set, then "t" becomes the point on the y axis to
+        place a horizontal bar.
+    varname : str or list, optional
+        The variable(s) to add the vertical bar to. If not set, the default is to add it to all current plots.
+    databar : bool, optional
+        This will turn the timebar into a horizontal data bar. If this is set True, then variable "t" becomes
+        the point on the y axis to place a horizontal bar.
+    delete : bool, optional
+        If set to True, at least one varname must be supplied. The timebar at point "t" for variable "varname"
+        will be removed.
+    color : str
+        The color of the bar.
+    thick : int
+        The thickness of the bar.
+    dash : bool
+        If set to True, the bar is dashed rather than solid.
+
+    Returns
+    -------
+    None
+
+    Examples
+    --------
+    >>> # Place a green time bar at 2017-07-17 00:00:00
+    >>> import pytplot
+    >>> pytplot.timebar(1500249600, color='green')
+
+    >>> # Place a dashed data bar at 5500 on the y axis
+    >>> pytplot.timebar(5500, dash=True, databar=True)
+
+    >>> # Place 3 magenta time bars of thickness 5
+    >>> # at [2015-12-26 05:20:01, 2015-12-26 08:06:40, 2015-12-26 08:53:19]
+    >>> # for variable 'sgx' plot
+    >>> pytplot.timebar([1451107201,1451117200,1451119999],'sgx',color='m',thick=5)
+    """
+
     # make sure t entered is a list
     if not isinstance(t, list):
         t = [t]
-    
+
     # if entries in list not numerical, run str_to_int
     if not isinstance(t[0], (int, float, complex)):
         t1 = []
         for time in t:
             t1.append(tplot_utilities.str_to_float_fuzzy(time))
         t = t1
-        
-    dim = 'height'
+
+    dim = "height"
     if databar is True:
-        dim = 'width'
-    
-    dash_pattern = 'solid'
+        dim = "width"
+
+    dash_pattern = "solid"
     if dash is True:
-        dash_pattern = 'dashed'
-
-
+        dash_pattern = "dashed"
+
     if delete is True:
         tplot_utilities.timebar_delete(t, varname, dim)
         return
-    
-    #if no varname specified, add timebars to every plot
+
+    # if no varname specified, add timebars to every plot
     if varname is None:
         num_bars = len(t)
         for i in range(num_bars):
             tbar = {}
-            tbar['location'] = t[i]
-            tbar['dimension'] = dim
-            tbar['line_color'] = pytplot.tplot_utilities.rgb_color(color)[0]
-            tbar['line_width'] = thick
-            tbar['line_dash'] = dash_pattern
+            tbar["location"] = t[i]
+            tbar["dimension"] = dim
+            tbar["line_color"] = pytplot.tplot_utilities.rgb_color(color)[0]
+            tbar["line_width"] = thick
+            tbar["line_dash"] = dash_pattern
             for name in pytplot.data_quants:
                 temp_data_quants = pytplot.data_quants[name]
                 if isinstance(temp_data_quants, dict):
                     # non-record varying variable
-                    continue 
-                temp_data_quants.attrs['plot_options']['time_bar'].append(tbar)
-    #if varname specified
+                    continue
+                temp_data_quants.attrs["plot_options"]["time_bar"].append(tbar)
+    # if varname specified
     else:
         if not isinstance(varname, list):
             varname = [varname]
@@ -101,14 +139,14 @@ def timebar(t, varname = None, databar = False, delete = False, color = 'black',
                 num_bars = len(t)
                 for i in range(num_bars):
                     tbar = {}
-                    tbar['location'] = t[i]
-                    tbar['dimension'] = dim
-                    tbar['line_color'] = pytplot.tplot_utilities.rgb_color(color)[0]
-                    tbar['line_width'] = thick
-                    tbar['line_dash'] = dash_pattern
+                    tbar["location"] = t[i]
+                    tbar["dimension"] = dim
+                    tbar["line_color"] = pytplot.tplot_utilities.rgb_color(color)[0]
+                    tbar["line_width"] = thick
+                    tbar["line_dash"] = dash_pattern
                     temp_data_quants = pytplot.data_quants[j]
                     if isinstance(temp_data_quants, dict):
                         # non-record varying variable
-                        continue 
-                    temp_data_quants.attrs['plot_options']['time_bar'].append(tbar)
-    return
+                        continue
+                    temp_data_quants.attrs["plot_options"]["time_bar"].append(tbar)
+    return

pytplot/timespan.py

@@ -1,53 +1,54 @@
-# Copyright 2018 Regents of the University of Colorado. All Rights Reserved.
-# Released under the MIT license.
-# This software was developed at the University of Colorado's Laboratory for Atmospheric and Space Physics.
-# Verify current version before use at: https://github.com/MAVENSDC/PyTplot
-
 from . import time_double
 from .xlim import xlim
 import logging
 
-def timespan(t1, dt, keyword='days'):
+
+def timespan(t1, dt, keyword="days"):
     """
-    This function will set the time range for all time series plots.  This is a wrapper for the function "xlim" to
-    better handle time axes.  
-    
-    Parameters:
-        t1 : flt/str
-            The time to start all time series plots.  Can be given in seconds since epoch, or as a string
-            in the format "YYYY-MM-DD HH:MM:SS"
-        dt : flt
-            The time duration of the plots.  Default is number of days.  
-        keyword : str
-            Sets the units of the "dt" variable.  Days, hours, minutes, and seconds are all accepted.  
-            
-    Returns:
-        None
-    
-    Examples:
-        >>> # Set the timespan to be 2017-07-17 00:00:00 plus 1 day
-        >>> import pytplot
-        >>> pytplot.timespan(1500249600, 1)
-        
-        >>> # The same as above, but using different inputs
-        >>> pytplot.timespan("2017-07-17 00:00:00", 24, keyword='hours')
+    This function will set the time range for all time series plots. This is a wrapper for the function "xlim" to
+    better handle time axes.
+
+    Parameters
+    ----------
+    t1 : float or str
+        The time to start all time series plots. Can be given in seconds since epoch, or as a string
+        in the format "YYYY-MM-DD HH:MM:SS".
+    dt : float
+        The time duration of the plots. Default is number of days.
+    keyword : str, optional
+        Sets the units of the "dt" variable. Days, hours, minutes, and seconds are all accepted. Default is 'days'.
+
+    Returns
+    -------
+    None
 
+    Examples
+    --------
+    >>> # Set the timespan to be 2017-07-17 00:00:00 plus 1 day
+    >>> import pytplot
+    >>> pytplot.timespan(1500249600, 1)
+
+    >>> # The same as above, but using different inputs
+    >>> pytplot.timespan("2017-07-17 00:00:00", 24, keyword='hours')
     """
-    
-    if keyword == 'days':
+
+    if keyword == "days":
         dt *= 86400
-    elif keyword == 'hours':
+    elif keyword == "hours":
         dt *= 3600
-    elif keyword == 'minutes':
+    elif keyword == "minutes":
         dt *= 60
-    elif keyword == 'seconds':
+    elif keyword == "seconds":
         dt *= 1
     else:
-        logging.warning("Invalid 'keyword' option %s.\nEnum(None, 'hours', 'minutes', 'seconds', 'days')",keyword)
-
+        logging.warning(
+            "Invalid 'keyword' option %s.\nEnum(None, 'hours', 'minutes', 'seconds', 'days')",
+            keyword,
+        )
+
     if not isinstance(t1, (int, float, complex)):
         t1 = time_double.time_double(t1)
-    t2 = t1+dt
+    t2 = t1 + dt
     xlim(t1, t2)
-    
-    return
+
+    return