#-----global.flag web_get001txtFg = False # @zt_web.web_get001txtFg #-----bs4.findall bs_get_ktag_kstr = '' #--colors #10,prism,brg,dark2,hsv,jet #10,,hot,Vega10,Vega20 cors_brg = cm.brg(np.linspace(0, 1, 10)) cors_hot = cm.hot(np.linspace(0, 1, 10)) cors_hsv = cm.hsv(np.linspace(0, 1, 10)) cors_jet = cm.jet(np.linspace(0, 1, 10)) cors_prism = cm.prism(np.linspace(0, 1, 10)) cors_Dark2 = cm.Dark2(np.linspace(0, 1, 10)) cors_Vega10 = cm.Vega10(np.linspace(0, 1, 10)) cors_Vega20 = cm.Vega20(np.linspace(0, 1, 10)) #------str.xxx sgnSP4 = ' ' sgnSP8 = sgnSP4 + sgnSP4 #-----FN.xxx logFN = '' #--------------dir # rdat0 = 'zDat/' rdatCN = rdat0 + "cn/day/" rdatCNX = rdat0 + "cn/xday/" rdatInx = rdat0 + "inx/"
def stacked_bar_plot(data, labels, legend=None, table_header=None, title=None,
ax_names=None, normalize=False, normalize_factor=None):
"""
Creates a tight stacked bar plot
:param data: list, data for 2 groups should be like [[1,2], [2,3]]
:param labels: list, should match the number of items in data.
"""
plt.rcParams["figure.figsize"] = (8, 6)
if normalize:
data_original = np.copy(data)
data = np.array([[y / normalize_factor for y in x] for x in data])
if len(labels) > 10:
plt.rcParams["figure.figsize"] = (len(labels) / 3, 6)
else:
plt.rcParams["figure.figsize"] = (8, 6)
# Use ggpot style
plt.style.use("ggplot")
fig, ax = plt.subplots()
# Get bottom positions for stacked bar
bottoms = np.cumsum(np.vstack((np.zeros(data.shape[1]), data)),
axis=0)[:-1]
w = .8
# Get x positions
xpos = [x + (w / 2) for x in range(len(labels))]
for c, d in enumerate(data):
if len(data) <= 10:
c1 = c if c < 9 else c - 10
clr = cm.Vega10(c1, 1)
else:
c1 = c if c < 19 else c - 20
clr = cm.Vega20c(c1, 1)
if c == 0:
bplot = ax.bar(xpos, d, w, color=clr, label=legend[c], alpha=.9)
else:
bplot = ax.bar(xpos, d, w, color=clr, label=legend[c], alpha=.9,
bottom=bottoms[c])
# Set x labels
plt.xticks([x + (w / 2) for x in xpos], labels, ha="right", rotation=45)
# Set legend
if legend:
if len(legend) <= 4:
cols = 1
else:
cols = len(legend) if len(legend) < 3 else 3
borderpad = cols * -6
lgd = plt.legend(loc=7, fancybox=True,
shadow=True, framealpha=.8, ncol=cols,
borderaxespad=borderpad)
if ax_names:
_add_labels(ax_names)
# Generate table structure
if table_header:
table = [table_header]
else:
table = []
if normalize:
for i, lbl in enumerate(labels):
table.append([lbl] + list(chain.from_iterable((int(x[i]), y[i])
for x, y in zip(*[data_original, data]))))
else:
for i, lbl in enumerate(labels):
table.append([lbl] + [int(x[i]) for x in data])
return fig, lgd, table
def stacked_bar_plot(data,
labels,
legend=None,
table_header=None,
title=None,
ax_names=None,
normalize=False,
normalize_factor=None,
width=0.8):
"""Creates a stacked bar plot.
Parameters
----------
data : numpy.array
Multi-dimensional array.
labels : list
List of xtick labels. Should have the same length as `data`.
title : str
Title of the plot.
table_header : list
List with the header of the table object. Each element represents
a column.
title : str
Title of the plot.
ax_names : list
List with the labels for the x-axis (first element) and y-axis
(second element).
normalize : bool
If True, values of the `data` array will be normalized by the
`normalize_factor`
normalize_factor : int or float
Number used to normalize values of the `data` array.
Returns
-------
fig : matplotlib.Figure
Figure object of the plot.
lgd : matplotlib.Legend
Legend object of the plot.
table : list
Table data in list format. Each item in the list corresponds to a
table row.
"""
plt.rcParams["figure.figsize"] = (8, 6)
if normalize:
data_original = np.copy(data)
data = np.array([[y / normalize_factor for y in x] for x in data])
if len(labels) > 10:
plt.rcParams["figure.figsize"] = (len(labels) / 3, 6)
else:
plt.rcParams["figure.figsize"] = (8, 6)
# Use ggpot style
plt.style.use("ggplot")
fig, ax = plt.subplots()
# Get bottom positions for stacked bar
bottoms = np.cumsum(np.vstack((np.zeros(data.shape[1]), data)),
axis=0)[:-1]
# Get x positions
xpos = [x + (width / 2) for x in range(len(labels))]
for c, d in enumerate(data):
if len(data) <= 10:
c1 = c if c < 9 else c - 10
clr = cm.Vega10(c1, 1)
else:
c1 = c if c < 19 else c - 20
clr = cm.Vega20c(c1, 1)
if legend:
current_lgd = legend[c]
else:
current_lgd = None
if c == 0:
bplot = ax.bar(xpos,
d,
width,
color=clr,
label=current_lgd,
alpha=.9)
else:
bplot = ax.bar(xpos,
d,
width,
color=clr,
label=current_lgd,
alpha=.9,
bottom=bottoms[c])
# Set x labels
plt.xticks([x + (width / 2) for x in xpos],
labels,
ha="right",
rotation=45)
# Set legend
if legend:
if len(legend) <= 4:
cols = 1
else:
cols = len(legend) if len(legend) < 3 else 3
borderpad = cols * -6
lgd = plt.legend(loc=7,
fancybox=True,
shadow=True,
framealpha=.8,
ncol=cols,
borderaxespad=borderpad)
else:
lgd = None
# Generate table structure
if table_header:
table = [table_header]
else:
table = []
if normalize:
for i, lbl in enumerate(labels):
table.append([lbl] + list(
chain.from_iterable((int(x[i]), y[i])
for x, y in zip(*[data_original, data]))))
else:
for i, lbl in enumerate(labels):
table.append([lbl] + [x[i] for x in data])
return fig, lgd, table