1 files changed, 0 insertions, 84 deletions
diff --git a/python/grahphics.py b/python/grahphics.py
deleted file mode 100644
index 0f348a04..00000000
--- a/python/grahphics.py
+++ /dev/null
@@ -1,84 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-from matplotlib import cm
-
-def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):
-    '''
-    Function to offset the "center" of a colormap. Useful for
-    data with a negative min and positive max and you want the
-    middle of the colormap's dynamic range to be at zero
-
-    Input
-    -----
-      cmap : The matplotlib colormap to be altered
-      start : Offset from lowest point in the colormap's range.
-          Defaults to 0.0 (no lower ofset). Should be between
-          0.0 and `midpoint`.
-      midpoint : The new center of the colormap. Defaults to
-          0.5 (no shift). Should be between 0.0 and 1.0. In
-          general, this should be  1 - vmax/(vmax + abs(vmin))
-          For example if your data range from -15.0 to +5.0 and
-          you want the center of the colormap at 0.0, `midpoint`
-          should be set to  1 - 5/(5 + 15)) or 0.75
-      stop : Offset from highets point in the colormap's range.
-          Defaults to 1.0 (no upper ofset). Should be between
-          `midpoint` and 1.0.
-    '''
-    cdict = {
-        'red': [],
-        'green': [],
-        'blue': [],
-        'alpha': []
-    }
-
-    # regular index to compute the colors
-    reg_index = np.linspace(start, stop, 257)
-
-    # shifted index to match the data
-    shift_index = np.hstack([
-        np.linspace(0.0, midpoint, 128, endpoint=False),
-        np.linspace(midpoint, 1.0, 129, endpoint=True)
-    ])
-
-    for ri, si in zip(reg_index, shift_index):
-        r, g, b, a = cmap(ri)
-
-        cdict['red'].append((si, r, r))
-        cdict['green'].append((si, g, g))
-        cdict['blue'].append((si, b, b))
-        cdict['alpha'].append((si, a, a))
-
-    newcmap = matplotlib.colors.LinearSegmentedColormap(name, cdict)
-    plt.register_cmap(cmap=newcmap)
-
-    return newcmap
-
-
-def plot_time_color_map(df, spread_shock, attr="pnl", path=".", color_map=cm.RdYlGn, index='IG'):
-
-    val_date = df.index[0].date()
-    df = df.reset_index()
-    df['days'] = (df['date'] - val_date).dt.days
-    ascending = [True,True] if index == 'HY' else [True,False]
-    df.sort_values(by=['date','spread'], ascending = ascending, inplace = True)
-    date_range = df.days.unique()
-
-    #plt.style.use('seaborn-whitegrid')
-    fig, ax = plt.subplots()
-    series = df[attr]
-    midpoint = 1 - series.max() / (series.max() + abs(series.min()))
-    shifted_cmap = shiftedColorMap(color_map, midpoint=midpoint, name='shifted')
-
-    chart = ax.imshow(series.values.reshape(date_range.size, spread_shock.size).T,
-                      extent=(date_range.min(), date_range.max(),
-                              spread_shock.min(), spread_shock.max()),
-                      aspect='auto', interpolation='bilinear', cmap=shifted_cmap)
-
-    #chart = ax.contour(date_range, spread_shock, series.values.reshape(date_range.size, spread_shock.size).T)
-
-    ax.set_xlabel('Days')
-    ax.set_ylabel('Price') if index == 'HY' else ax.set_ylabel('Spread')
-    ax.set_title('{} of Trade'.format(attr.title()))
-
-    fig.colorbar(chart, shrink=.8)
-    #fig.savefig(os.path.join(path, "spread_time_color_map_"+ attr+ "_{}.png".format(val_date)))