Added distance target range plotting to distance/time plot, added .pn…

…g figures in data/

data/PEC/Base/PEC_Base.md

@@ -230,7 +230,7 @@ Name | Value
 --- | ---
 show | False
 save | False
-pdf | True
+pdf | False
 dpi | 500
 base_string | Base
 title_string | Target cost range: 

data/PV_E/Base/PV_E_Base.md

@@ -193,7 +193,7 @@ Name | Value
 --- | ---
 show | False
 save | False
-pdf | True
+pdf | False
 dpi | 500
 base_string | Base
 title_string | Target cost range: 
@@ -247,7 +247,7 @@ Name | Value
 --- | ---
 show | False
 save | False
-pdf | True
+pdf | False
 dpi | 500
 fig_width | 5.5
 fig_height | 4.5

data/PV_E/Historical_Data/PV_E_Distance_Time.md

@@ -153,6 +153,7 @@ Name | Method Name | Arguments
 plot_distance_histogram_log | plot_distance_histogram | {'show': False, 'save': False, 'dpi': 400, 'pdf': True, 'image_kwargs': {'path': 'pyH2A.Other~PV_E_Clipart.png'}}
 plot_distance_cost_log | plot_distance_cost_relationship | {'show': False, 'save': False, 'dpi': 300, 'pdf': False, 'image_kwargs': {'path': 'pyH2A.Other~PV_E_Clipart.png'}}
 plot_distance_time | plot_distance_time_relationship | Arguments - Time Analysis - distance_time_plot
+plot_distance_time_no_table | plot_distance_time_relationship | Arguments - Time Analysis - distance_time_plot_no_table
 
 # Arguments - Time Analysis - distance_time_plot
 
@@ -162,8 +163,24 @@ show | True
 save | False
 dpi | 500
 pdf | True
+color_future | False
 image_kwargs | {'path': 'pyH2A.Other~PV_E_Clipart.png'}
 
+# Arguments - Time Analysis - distance_time_plot_no_table
+
+Name | Value
+--- | ---
+show | False
+save | False
+name | Distance_Time_Relationship_No_Table
+dpi | 500
+pdf | False
+parameter_table | False
+color_future | False
+target_distances | [0.5, 0.6]
+plot_kwargs | {'left': 0.34, 'right': 0.96, 'bottom': 0.13, 'top': 0.96, 'fig_width': 6.2, 'fig_height': 4.0}
+image_kwargs | {'x': -0.37, 'zoom': 0.092, 'y': 0.5, 'path': 'pyH2A.Other~PV_E_Clipart.png'}
+
 # Methods - Monte_Carlo_Analysis
 
 Name | Method Name | Arguments

data/Photocatalytic/Base/Photocatalytic_Base.md

@@ -238,7 +238,7 @@ Name | Value
 --- | ---
 show | False
 save | False
-pdf | True
+pdf | False
 dpi | 500
 base_string | Base
 title_string | Target cost range: 

data/pyH2A_execution.py

@@ -100,13 +100,13 @@ def test():
 	print(Energy(285.83 * (1000./2.) * con.Avogadro, kJmol).J)
 
 def main():
-	#pv_e_base()
+	pv_e_base()
 	#pv_e_limit()
 	#pv_e_distance_time()
 	#pec_base()
 	#pec_limit()
 	#pec_limit_no_concentration()
-	photocatalytic_base()
+	#photocatalytic_base()
 	#photocatalytic_limit()
 	#technology_comparison()
 	#test()

doc/plugins/Plugin_Guide.rst

@@ -8,9 +8,9 @@ pyH2A follows the open-closed principle, meaning that new plugins can be interfa
 Structure
 ---------
 
-Plugins are single ``.py`` files, which contain a class with the same name as the filename (this shared name should include the term ``Plugin``). This class is instantiated during pyH2A runtime. The file may also contain other classes and functions, which serve the central class.
+Plugins are single ``.py`` files, which contain a class with the same name as the filename (this shared name should include the term ``Plugin``). This class is instantiated during pyH2A runtime. Instantiation requires two arguments: ``dcf``, which is discounted cash flow object (generated during pyH2A runtime) and ``print_info``, which is a flag to control printing of additional runtime information (this flag is passed to :func:`~pyH2A.Utilities.input_modification.insert`) The file may also contain other classes and functions, which serve the central class.
 
-The overall idea is that during instantiation, the class reads information from ``dcf.inp`` (the directory generated from the input file), processes the information and inserts new information into ``dcf.inp``. ``dcf.inp`` is the medium of information exchange between plugins and by inserting information there, the results of the plugin affect the outcome of the discounted cashflow analysis.
+The overall idea is that during instantiation, the class reads information from ``dcf.inp`` (the dictionary generated from the input file), processes the information and inserts new information into ``dcf.inp``. ``dcf.inp`` is the medium of information exchange between plugins and by inserting information there, the results of the plugin affect the outcome of the discounted cashflow analysis.
 
 Example
 -------

src/pyH2A.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: pyH2A
-Version: 0.0a7
+Version: 0.0a8
 Summary: A framework for the analysis of hydrogen production cost
 Home-page: https://github.com/jschneidewind/pyH2A
 Author: Jacob Schneidewind

src/pyH2A/Analysis/Development_Distance_Time_Analysis.py

@@ -475,6 +475,24 @@ def plot_distance_cost_relationship(self, ax = None, figure_lean = True,
 			figure.execute()
 			return figure.fig
 
+	def plot_distance_indicator(self, ax, target_distances, model, years, color, ylim_lower):
+
+		idx = find_nearest(model, target_distances)
+
+		x = years[idx[0]:idx[1]+1]
+		y = model[idx[0]:idx[1]+1]
+		y_lower = np.ones(len(x)) * ylim_lower
+
+		ax.fill_between(x, y, y_lower, color = color)
+
+		# for i in idx:
+		# 	x_coord = years[i]
+		# 	y_coord = model[i]
+
+		# 	ax.annotate('', xy = (x_coord, y_coord), 
+		# 					xytext = (x_coord, ylim_lower), 
+		# 					arrowprops={'arrowstyle': '-', 'ls': 'dashed', 'color': color})
+
 	def plot_distance_time_relationship(self, ax = None, figure_lean = True,  
 										legend_loc = 'upper left',
 										xlabel_string = 'Year',
@@ -483,7 +501,9 @@ def plot_distance_time_relationship(self, ax = None, figure_lean = True,
 										linear_label_string = 'Linear model',
 										datapoint_label_string = ' historical distance',
 										markersize = 10,
+										color_future = True,
 										parameter_table = True,
+										target_distances = None,
 										table_kwargs = {}, image_kwargs = {}, plot_kwargs = {},
 										**kwargs):
 		'''Ploting relationship between time and development distance based on 
@@ -510,8 +530,13 @@ def plot_distance_time_relationship(self, ax = None, figure_lean = True,
 			is the display name of the model.
 		markersize : float, optional
 			Size of markers in scatter plot.
+		color_future : bool, optional
+			Boolean flag to control if past or future region of plot is colored.
 		parameter_table : bool, optional
 			If parameter_table is True, the parameter table is shown in the plot.
+		target_distances : ndarray, optional
+			Target distance range as an 1D array with two entries ([lower_limit, higher_limit]),
+			which is highlighted in the plot.
 		image_kwargs: dict, optional
 			Dictionary containing optional keyword arguments for
 			:func:`~pyH2A.Utilities.output_utilities.insert_image`
@@ -552,10 +577,18 @@ def plot_distance_time_relationship(self, ax = None, figure_lean = True,
 		ax.plot(self.years, self.distances, '.', color = self.color, markersize = markersize,
 				label = self.display_name + datapoint_label_string)
 
+		xlim = ax.get_xlim()
+		ax.set_xlim(left = xlim[0], right = np.amax(self.years_extended))
+
+		ylim = ax.get_ylim()
+		ax.set_ylim(ylim)
+
 		ax.axhspan(0, 1, color = cm(0.5), alpha = 0.1)
-		ax.axvspan(self.base_year, np.amax(self.years_extended), color = cm(0.75), alpha = 0.1)
 
-		ax.set_xlim(right = np.amax(self.years_extended))
+		if color_future:
+			ax.axvspan(self.base_year, np.amax(self.years_extended), color = cm(0.75), alpha = 0.1)
+		else:
+			ax.axvspan(xlim[0], self.base_year, color = cm(0.75), alpha = 0.1)
 
 		ax.set_xlabel(xlabel_string)
 		ax.set_ylabel(ylabel_string)
@@ -569,6 +602,16 @@ def plot_distance_time_relationship(self, ax = None, figure_lean = True,
 		if image_kwargs['path'] is not None:
 			insert_image(ax = ax, **image_kwargs)
 
+		if target_distances is not None:
+			ax.axhspan(target_distances[0], target_distances[1], color = 'gray', alpha = 0.3)
+
+			self.plot_distance_indicator(ax, target_distances, self.linear_distance_model,
+										 self.years_extended, cm(0.25), ylim[0])
+
+			self.plot_distance_indicator(ax, target_distances, self.expo_distance_model,
+										 self.years_extended, cm(0.0), ylim[0])
+
+
 		if figure_lean is True:
 			figure.execute()
 			return figure.fig