{"action":"created","comment":{"url":"https://api.github.com/repos/houghb/HDSAviz/pulls/comments/53882369","id":53882369,"diff_hunk":"@@ -0,0 +1,443 @@\n+{\n+ \"cells\": [\n+  {\n+   \"cell_type\": \"markdown\",\n+   \"metadata\": {\n+    \"collapsed\": false\n+   },\n+   \"source\": [\n+    \"# Basic_Plot is revised as below to make it compatible with Interactivevis.py\"\n+   ]\n+  },\n+  {\n+   \"cell_type\": \"code\",\n+   \"execution_count\": 9,\n+   \"metadata\": {\n+    \"collapsed\": true\n+   },\n+   \"outputs\": [],\n+   \"source\": [\n+    \"\\\"\\\"\\\"\\n\",\n+    \"This is a basic script for plotting an analysis file.\\n\",\n+    \"\\n\",\n+    \"Modified from : Basic_Plot.py\\n\",\n+    \"\\\"\\\"\\\"\\n\",\n+    \"\\n\",\n+    \"from collections import OrderedDict\\n\",\n+    \"import numpy as np\\n\",\n+    \"import pandas as pd\\n\",\n+    \"import pdb\\n\",\n+    \"\\n\",\n+    \"from bokeh.plotting import figure, show, output_notebook, output_file\\n\",\n+    \"\\n\",\n+    \"\\n\",\n+    \"\\\"\\\"\\\"This script is just the first step in visualizing the data set. This file\\n\",\n+    \"comprises of the method creating an html bokeh plot and a command at the end to\\n\",\n+    \"implement the method\\n\",\n+    \"\\\"\\\"\\\"\\n\",\n+    \"\\n\",\n+    \"def makeplot(Dataframe, Cols, minvalues):\\n\",\n+    \"    \\\"\\\"\\\"Basic method to plot sensitivity anlaysis.\\n\",\n+    \"    This is the method to generate a bokeh plot followung the burtin example\\n\",\n+    \"    template at the bokeh website. For clarification, parameters refer to an\\n\",\n+    \"    output being measured (Tmax, C, rxn2, etc.) and stats refer to the 1st or\\n\",\n+    \"    total order sensitivity index.\\n\",\n+    \"    Inputs:\\n\",\n+    \"    Dataframe - Name of csv file to be read into as a panda dataframe (String)\\n\",\n+    \"                **Note file must be in same folder as script.**\\n\",\n+    \"    Cols- Names of the columns to be plotted (Array of strings)\\n\",\n+    \"    minvalues- Cutoff minimum for which parameters should be plotted (Array of\\n\",\n+    \"                floats)\\n\",\n+    \"    Outputs:\\n\",\n+    \"    Generates an html of the plot. The axis is a log scale.\\n\",\n+    \"    \\\"\\\"\\\"\\n\",\n+    \"    # Read in csv file as panda dataframe.\\n\",\n+    \"    tdf = pd.read_csv(Dataframe, delimiter=' ', skipinitialspace=True,\\n\",\n+    \"                      engine='python')\\n\",\n+    \"    df = tdf\\n\",\n+    \"    maxval = 0\\n\",\n+    \"    # Remove rows which have values less than cutoff values\\n\",\n+    \"    for i in range(0, minvalues.size):\\n\",\n+    \"        df = df[df[Cols[i]] > minvalues[i]]\\n\",\n+    \"        if maxval < max(df[Cols[i]]):\\n\",\n+    \"            maxval = max(df[Cols[i]])\\n\",\n+    \"    df = df.dropna()\\n\",\n+    \"\\n\",\n+    \"    # Create dictionary of bar colors, assume up to 3 stats are plotted\\n\",\n+    \"    # per parameter.\\n\",\n+    \"    colors = [\\\"#0d3362\\\", \\\"#c64737\\\", \\\"black\\\"]\\n\",\n+    \"    stat_color = OrderedDict()\\n\",\n+    \"    for i in range(0, Cols.size):\\n\",\n+    \"        stat_color[i] = colors[i]\\n\",\n+    \"    # Reset index of dataframe.\\n\",\n+    \"    df = df.reset_index(drop=True)\\n\",\n+    \"\\n\",\n+    \"    # Sizing parameters\\n\",\n+    \"    width = 800\\n\",\n+    \"    height = 800\\n\",\n+    \"    inner_radius = 90\\n\",\n+    \"    outer_radius = 300 - 10\\n\",\n+    \"\\n\",\n+    \"    # Determine wedge size based off number of parameters\\n\",\n+    \"    big_angle = 2.0 * np.pi / (len(df)+1)\\n\",\n+    \"    # Determine division of wedges for plotting bars based on # stats plotted\\n\",\n+    \"    small_angle = big_angle / (minvalues.size+2)\\n\",\n+    \"\\n\",\n+    \"    p = figure(plot_width=width, plot_height=height, title=\\\"\\\",\\n\",\n+    \"               x_axis_type=None, y_axis_type=None,\\n\",\n+    \"               x_range=(-420, 420), y_range=(-420, 420),\\n\",\n+    \"               min_border=0, outline_line_color=\\\"black\\\",\\n\",\n+    \"               background_fill=\\\"#f0e1d2\\\", border_fill=\\\"#f0e1d2\\\")\\n\",\n+    \"\\n\",\n+    \"    p.xgrid.grid_line_color = None\\n\",\n+    \"    p.ygrid.grid_line_color = None\\n\",\n+    \"\\n\",\n+    \"    # annular wedges divided into smaller sections for bars\\n\",\n+    \"    angles = np.pi/2 - big_angle/2 - df.index.to_series()*big_angle\\n\",\n+    \"    # circular axes and labels\\n\",\n+    \"    labels = np.power(10.0, np.arange(0, -5, -1))\\n\",\n+    \"    labz = np.power(10.0, np.arange(0, -4.5, -0.5))\\n\",\n+    \"    # Re-size if no values are above 0.1\\n\",\n+    \"    if maxval < 0.1:\\n\",\n+    \"        labels = np.delete(labels, 0)\\n\",\n+    \"    # Size of radii of each label\\n\",\n+    \"    #pdb.set_trace()\\n\",\n+    \"    rad = (((np.log10(labz / labels[0])) + labels.size) *\\n\",\n+    \"           (outer_radius - inner_radius) / labels.size + inner_radius)\\n\",\n+    \"    radii = (((np.log10(labels / labels[0])) + labels.size) *\\n\",\n+    \"             (outer_radius - inner_radius) / labels.size + inner_radius)\\n\",\n+    \"    # Add zero label to labels and radii\\n\",\n+    \"    labels = np.append(labels, 0.0)\\n\",\n+    \"    radii = np.append(radii, inner_radius)\\n\",\n+    \"    rad = np.append(rad, inner_radius)\\n\",\n+    \"    p.circle(0, 0, radius=rad, fill_color=None, line_color=\\\"white\\\")\\n\",\n+    \"    p.text(0, radii[:], [str(r) for r in labels[:]],\\n\",\n+    \"           text_font_size=\\\"8pt\\\", text_align=\\\"center\\\", text_baseline=\\\"middle\\\")\\n\",\n+    \"    # Plot the values of each stat for each parameter.\\n\",\n+    \"    for c in range(0, Cols.size):\\n\",\n+    \"        p.annular_wedge(0, 0, inner_radius, (((np.log10(df[Cols[c]] /\\n\",\n+    \"                                              labels[0])) + labels.size) *\\n\",\n+    \"                                             (outer_radius - inner_radius) /\\n\",\n+    \"                                             labels.size + inner_radius),\\n\",\n+    \"                        -big_angle + angles + (2*c + 1)*small_angle,\\n\",\n+    \"                        -big_angle + angles + (2*c + 2)*small_angle,\\n\",\n+    \"                        color=stat_color[c])\\n\",\n+    \"    # radial axes\\n\",\n+    \"    p.annular_wedge(0, 0, inner_radius-10, outer_radius+10,\\n\",\n+    \"                    -big_angle+angles, -big_angle+angles, color=\\\"black\\\")\\n\",\n+    \"\\n\",\n+    \"    # Placement of parameter labels\\n\",\n+    \"    xr = radii[0]*np.cos(np.array(-big_angle/2 + angles))\\n\",\n+    \"    yr = radii[0]*np.sin(np.array(-big_angle/2 + angles))\\n\",\n+    \"\\n\",\n+    \"    label_angle = np.array(-big_angle/2+angles)\\n\",\n+    \"    label_angle[label_angle < -np.pi/2] += np.pi\\n\",\n+    \"    # Placing Labels and Legend\\n\",\n+    \"    p.text(xr, yr, df.Parameter, angle=label_angle,\\n\",\n+    \"           text_font_size=\\\"9pt\\\", text_align=\\\"center\\\", text_baseline=\\\"middle\\\")\\n\",\n+    \"\\n\",\n+    \"    p.rect([-40, -40], [18, 0], width=30, height=13,\\n\",\n+    \"           color=list(stat_color.values()))\\n\",\n+    \"    p.text([-15, -15], [18, 0], text=Cols,\\n\",\n+    \"           text_font_size=\\\"9pt\\\", text_align=\\\"left\\\", text_baseline=\\\"middle\\\")\\n\",\n+    \"\\n\",\n+    \"    \\n\",\n+    \"    return p\\n\"\n+   ]\n+  },\n+  {\n+   \"cell_type\": \"markdown\",\n+   \"metadata\": {},\n+   \"source\": [\n+    \"# Code Below is the interactive plots version\"\n+   ]\n+  },\n+  {\n+   \"cell_type\": \"code\",\n+   \"execution_count\": 18,\n+   \"metadata\": {\n+    \"collapsed\": false\n+   },\n+   \"outputs\": [\n+    {\n+     \"name\": \"stdout\",\n+     \"output_type\": \"stream\",\n+     \"text\": [\n+      \"\\n\"\n+     ]\n+    }\n+   ],\n+   \"source\": [\n+    \"\\\"\\\"\\\"\\n\",\n+    \"The current program is meant to draw interactive visualizations using BOKEH\\n\",\n+    \"and ipywidgets libraries for sensitivity analysis\\n\",\n+    \"\\n\",\n+    \"Dependencies : \\n\",\n+    \"Currently this code needs to be run Inside Ipython notebook.\\n\",\n+    \"Python version :2.7\\n\",\n+    \"\\n\",\n+    \"Note:\\n\",\n+    \"Please ensure Basic_Plot.py exists in same directory and necessary data files are\\n\",\n+    \"located in c:/HDSAviz_data folder\\n\",\n+    \"\\n\",\n+    \"Basically files should be organized as : \\n\",\n+    \"\\n\",\n+    \"C: HDSAviz_data/\\n\",\n+    \"C: HDSAviz_data/analysis_CO.txt \\n\",\n+    \"C: HDSAviz_data/analysis_CO2.txt \\n\",\n+    \"etc.\\n\",\n+    \"\\n\",\n+    \"C: HDSAviz_data/interactivevislib.py \\n\",\n+    \"C: HDSAviz_data/Interactive_vis_toolkit.ipynb\\n\",\n+    \"\\n\",\n+    \"\\\"\\\"\\\"\\n\",\n+    \"\\n\",\n+    \"#import Basic_Plot  once Basic_Plot.py file is ammended.\\n\",\n+    \"\\n\",\n+    \"import os\\n\",\n+    \"from bokeh.models.widgets import Panel, Tabs\\n\",\n+    \"from bokeh.io import output_file, output_notebook, show, vform\\n\",\n+    \"from ipywidgets import FloatSlider\\n\",\n+    \"from IPython.html.widgets import interact\\n\",\n+    \"from collections import OrderedDict\\n\",\n+    \"from bokeh.plotting import figure, show, output_notebook, output_file\\n\",\n+    \"\\n\",\n+    \"# initializing the range of values for total order (ST) and first order \\n\",\n+    \"# (S1) sensitivity tests \\n\",\n+    \"ST_Range = 1\\n\",\n+    \"S1_Range = 1\\n\",\n+    \"\\n\",\n+    \"def change_directory():\\n\",","path":"HDSAviz/Interactive_vis_toolkit.ipynb","position":210,"original_position":210,"commit_id":"417350acc30f7427b71b032ed6a74712e3a9f09d","original_commit_id":"417350acc30f7427b71b032ed6a74712e3a9f09d","user":{"login":"cdf6gc","id":16655107,"avatar_url":"https://avatars.githubusercontent.com/u/16655107?v=3","gravatar_id":"","url":"https://api.github.com/users/cdf6gc","html_url":"https://github.com/cdf6gc","followers_url":"https://api.github.com/users/cdf6gc/followers","following_url":"https://api.github.com/users/cdf6gc/following{/other_user}","gists_url":"https://api.github.com/users/cdf6gc/gists{/gist_id}","starred_url":"https://api.github.com/users/cdf6gc/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cdf6gc/subscriptions","organizations_url":"https://api.github.com/users/cdf6gc/orgs","repos_url":"https://api.github.com/users/cdf6gc/repos","events_url":"https://api.github.com/users/cdf6gc/events{/privacy}","received_events_url":"https://api.github.com/users/cdf6gc/received_events","type":"User","site_admin":false},"body":"Blake and I are on macs so C: will not work for us. The path of  ../../HDSAviz_data will work so long as we are all consistent in storing the data outside of our repos","created_at":"2016-02-24T01:38:30Z","updated_at":"2016-02-24T01:38:30Z","html_url":"https://github.com/houghb/HDSAviz/pull/3#discussion_r53882369","pull_request_url":"https://api.github.com/repos/houghb/HDSAviz/pulls/3","_links":{"self":{"href":"https://api.github.com/repos/houghb/HDSAviz/pulls/comments/53882369"},"html":{"href":"https://github.com/houghb/HDSAviz/pull/3#discussion_r53882369"},"pull_request":{"href":"https://api.github.com/repos/houghb/HDSAviz/pulls/3"}}},"pull_request":{"url":"https://api.github.com/repos/houghb/HDSAviz/pulls/3","id":60366944,"html_url":"https://github.com/houghb/HDSAviz/pull/3","diff_url":"https://github.com/houghb/HDSAviz/pull/3.diff","patch_url":"https://github.com/houghb/HDSAviz/pull/3.patch","issue_url":"https://api.github.com/repos/houghb/HDSAviz/issues/3","number":3,"state":"open","locked":false,"title":"Pull requests swapil","user":{"login":"swapilpaliwal","id":11746393,"avatar_url":"https://avatars.githubusercontent.com/u/11746393?v=3","gravatar_id":"","url":"https://api.github.com/users/swapilpaliwal","html_url":"https://github.com/swapilpaliwal","followers_url":"https://api.github.com/users/swapilpaliwal/followers","following_url":"https://api.github.com/users/swapilpaliwal/following{/other_user}","gists_url":"https://api.github.com/users/swapilpaliwal/gists{/gist_id}","starred_url":"https://api.github.com/users/swapilpaliwal/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/swapilpaliwal/subscriptions","organizations_url":"https://api.github.com/users/swapilpaliwal/orgs","repos_url":"https://api.github.com/users/swapilpaliwal/repos","events_url":"https://api.github.com/users/swapilpaliwal/events{/privacy}","received_events_url":"https://api.github.com/users/swapilpaliwal/received_events","type":"User","site_admin":false},"body":"# Contains files for interactive visualizations and related documentation.\r\n- Please try running the Ipython notebook file as code needs notebook environment currently for plotting inline in current demos.\r\n","created_at":"2016-02-23T16:26:26Z","updated_at":"2016-02-24T01:38:30Z","closed_at":null,"merged_at":null,"merge_commit_sha":"2b5c37a0f8614723db5638183ed38ad78ae7575a","assignee":null,"milestone":null,"commits_url":"https://api.github.com/repos/houghb/HDSAviz/pulls/3/commits","review_comments_url":"https://api.github.com/repos/houghb/HDSAviz/pulls/3/comments","review_comment_url":"https://api.github.com/repos/houghb/HDSAviz/pulls/comments{/number}","comments_url":"https://api.github.com/repos/houghb/HDSAviz/issues/3/comments","statuses_url":"https://api.github.com/repos/houghb/HDSAviz/statuses/417350acc30f7427b71b032ed6a74712e3a9f09d","head":{"label":"houghb:branch_swapil","ref":"branch_swapil","sha":"417350acc30f7427b71b032ed6a74712e3a9f09d","user":{"login":"houghb","id":12754861,"avatar_url":"https://avatars.githubusercontent.com/u/12754861?v=3","gravatar_id":"","url":"https://api.github.com/users/houghb","html_url":"https://github.com/houghb","followers_url":"https://api.github.com/users/houghb/followers","following_url":"https://api.github.com/users/houghb/following{/other_user}","gists_url":"https://api.github.com/users/houghb/gists{/gist_id}","starred_url":"https://api.github.com/users/houghb/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/houghb/subscriptions","organizations_url":"https://api.github.com/users/houghb/orgs","repos_url":"https://api.github.com/users/houghb/repos","events_url":"https://api.github.com/users/houghb/events{/privacy}","received_events_url":"https://api.github.com/users/houghb/received_events","type":"User","site_admin":false},"repo":{"id":51385164,"name":"HDSAviz","full_name":"houghb/HDSAviz","owner":{"login":"houghb","id":12754861,"avatar_url":"https://avatars.githubusercontent.com/u/12754861?v=3","gravatar_id":"","url":"https://api.github.com/users/houghb","html_url":"https://github.com/houghb","followers_url":"https://api.github.com/users/houghb/followers","following_url":"https://api.github.com/users/houghb/following{/other_user}","gists_url":"https://api.github.com/users/houghb/gists{/gist_id}","starred_url":"https://api.github.com/users/houghb/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/houghb/subscriptions","organizations_url":"https://api.github.com/users/houghb/orgs","repos_url":"https://api.github.com/users/houghb/repos","events_url":"https://api.github.com/users/houghb/events{/privacy}","received_events_url":"https://api.github.com/users/houghb/received_events","type":"User","site_admin":false},"private":false,"html_url":"https://github.com/houghb/HDSAviz","description":"A 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