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CLIMATE-230 Line colors in time series cycles through too few colors
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Michael Anderson authored and Michael Anderson committed Jan 4, 2018
1 parent 4cf79f3 commit 96ac07df4cec047adccf7a31e0fce82b634ce7e1
Showing 1 changed file with 35 additions and 1 deletion.
@@ -367,9 +367,24 @@ def draw_subregions(subregions, lats, lons, fname, fmt='png', ptitle='',

def _get_colors(num_colors):
matplotlib will recycle colors after a certain number. This can make
line type charts confusing as colors will be reused. This function
provides a distribution of colors across the default color map
to better approximate uniqueness.
:param num_colors: The number of unique colors to generate.
:return: A color map with num_colors.
cmap = plt.get_cmap()
return [cmap(1. * i / num_colors) for i in range(num_colors)]

def draw_time_series(results, times, labels, fname, fmt='png', gridshape=(1, 1),
xlabel='', ylabel='', ptitle='', subtitles=None,
label_month=False, yscale='linear', aspect=None):
label_month=False, yscale='linear', aspect=None,
cycle_colors=True, cmap=None):
''' Draw a time series plot.
:param results: 3D array of time series data.
@@ -415,7 +430,22 @@ def draw_time_series(results, times, labels, fname, fmt='png', gridshape=(1, 1),
:param aspect: (Optional) approximate aspect ratio of each subplot
(width / height). Default is 8.5 / 5.5
:type aspect: :class:`float`
:param cycle_colors: (Optional) flag to toggle whether to allow matlibplot
to re-use colors when plotting or force an evenly distributed range.
:type cycle_colors: :class:`bool`
:param cmap: (Optional) string or :class:`matplotlib.colors.LinearSegmentedColormap`
instance denoting the colormap. This must be able to be recognized by
`Matplotlib's get_cmap function <>`_.
Maps like rainbow and spectral with wide spectrum of colors are nice choices when used with
the cycle_colors option. tab20, tab20b, and tab20c are good if the plot has less than 20 datasets.
:type cmap: :mod:`string` or :class:`matplotlib.colors.LinearSegmentedColormap`
if cmap is not None:

# Handle the single plot case.
if results.ndim == 2:
results = results.reshape(1, *results.shape)
@@ -448,6 +478,10 @@ def draw_time_series(results, times, labels, fname, fmt='png', gridshape=(1, 1),
# Make the plots
for i, ax in enumerate(grid):
data = results[i]

if not cycle_colors:
ax.set_prop_cycle('color', _get_colors(data.shape[0]))

if label_month:
xfmt = mpl.dates.DateFormatter('%b')
xloc = mpl.dates.MonthLocator()

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