def slope(data,
kind='interval',
marker='%0.f',
color=None,
title='',
font_family='GillSans',
font_size=12,
width=12,
height=8,
ax=None,
savename=None,
dpi=150,
wspace=None, ):
"""====
Slope
====
Definition: slope(data,kind=['interval','ordinal'],height,width,font_size,savename,color,title)
----
Plot Slope plot Tufte Style
:class:`matplotlib.figure.Figure object`.
Parameters
----------
data : pandas dataFrame
index indicate the categories
columns indicate time / period
marker style : str, format
Format to present the data
default '%0.f'
label_position : str ['ordinal', 'interval']
how to position labels.
Interval will place them according to their values
Ordinal will place them according to their rank
font_family : font family name installed on your system
font_size : set the font size
in case your data have more lines than you can have text lines of text
in your figure height, data will be binned to fit
(default 12)
height : Figure height in inches (default 12)
with : Figure width in inches (default 8)
savename : file path to save your graph
color : a dictionary {label:color}
title : a title at the bottom of the graph
Examples
--------
>>> data = pd.read_csv(os.path.join('Data','EU_GDP_2007_2013.csv'),index_col=0,na_values='-')
>>> f = slope(data/1000,kind='interval',height= 12,width=20,font_size=12,savename='EU_interval.png',title = u'title')
"""
font = FontProperties(font_family)
font.set_size(font_size)
bx = None
df = data.copy()
cols = df.columns
df['__label__'] = df.index
df['__order__'] = range(len(df.index))
if kind == 'stack':
f, axarr = plt.subplots(len(df), len(cols) - 1,
facecolor="w",
squeeze=False,
sharex=True) #,sharey=True)
else:
#f, axarr = plt.subplots(2,len(cols)-1,facecolor="w",squeeze=True,figsize=(width,height),dpi=30)#,sharex=True)#,sharey=True)
f = plt.figure(figsize=(width, height), dpi=30, facecolor="w")
gs = gridspec.GridSpec(
nrows=20,
ncols=len(cols) - 1
) # the 20 rows are just there to provide enought space for the title
axarr = []
axarr_X = []
for i in range(len(cols) - 1):
axarr.append(plt.subplot(gs[:19, i]))
axarr_X.append(plt.subplot(gs[19, i]))
axarr = np.array(axarr)
axarr_X = np.array(axarr_X)
renderer = f.canvas.get_renderer()
data_range = [data.min().min(), data.max().max()]
fh = f.get_figheight()
fw = f.get_figwidth()
fdpi = f.get_dpi()
nt = fh // (font.get_size() / 72) / 2
res = np.diff(data_range)[0] / nt * 2
if not hasattr(axarr, 'transpose'):
axarr = [axarr]
for i in range((len(cols) - 1)):
ax = axarr[i]
axarr_X[i].yaxis.set_tick_params(width=0)
axarr_X[i].xaxis.set_tick_params(width=0)
"""
from matplotlib.offsetbox import AnchoredOffsetbox, TextArea, HPacker
# orange label
obox1 = TextArea("orange - ", textprops=dict(color="k", size=15))
obox2 = TextArea("5 ", textprops=dict(color="b", size=15))
obox3 = TextArea(": ", textprops=dict(color="k", size=15))
obox4 = TextArea("10 ", textprops=dict(color="r", size=15))
orangebox = HPacker(children=[obox1, obox2, obox3, obox4],
align="center", pad=0, sep=5)
"""
if kind == 'interval':
labelsL = df.groupby(pd.cut(df[cols[i]], nt))['__label__'].agg(
', '.join).dropna()
labelsR = df.groupby(pd.cut(df[cols[i + 1]], nt))['__label__'].agg(
', '.join).dropna()
yPos_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yPos_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yMark_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yMark_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yPos_ = df[[cols[i], cols[i + 1]]]
if kind == 'ordinal':
yPos_L = df[[cols[i]]].rank(ascending=False).applymap(
lambda el: round(el + 0.1))
yPos_R = df[[cols[i + 1]]].rank(ascending=False).applymap(
lambda el: round(el + 0.1))
yMark_L = df.groupby(cols[i])[cols[i]].mean().dropna()
yMark_R = df.groupby(cols[i + 1])[cols[i + 1]].mean().dropna()
yMark_L.sort(ascending=False)
yMark_R.sort(ascending=False)
#print yMark_L
labelsL = df.groupby(yPos_L[cols[i]].values)['__label__'].agg(
', '.join)
labelsR = df.groupby(yPos_R[cols[i + 1]].values)['__label__'].agg(
', '.join)
yPos_L.sort(cols[i], inplace=True)
yPos_R.sort(cols[i + 1], inplace=True)
yPos_ = yPos_L.join(yPos_R) #.sort(cols[i],inplace=True)
# if i == 1:
# #print yPos_.T
# print labelsL
# #yPos_ = df[[cols[i],cols[i+1]]]
#
# if kind=='stack' :
#
# yPos_L = df[cols[i]].rank()
# yPos_R = df[cols[i+1]].rank()
#
# labelsL = df.groupby(yPos_L)['__label__'].agg(', '.join)
# labelsR = df.groupby(yPos_R)['__label__'].agg(', '.join)
#
# yPos_ = yPos_L.join(yPos_R)
#
# yPos_L = labelsL.index.values
# yPos_R = labelsR.index.values
if kind == "stack":
ax.plot([0, 1], [0, 1], color='k', alpha=0.4)
else:
#print yPos_
lines = ax.plot(yPos_.T, color='k', alpha=0.4)
ax.spines['bottom'].set_visible(False)
ax.xaxis.set_ticks_position('bottom')
if kind == "ordinal":
ax.set_ybound(lower=1, upper=len(yPos_))
if kind == "interval":
ax.set_ybound(lower=data.min().min(), upper=data.max().max())
#ax.set_xbound(lower=0,upper=1)
ax.set_xticklabels([])
#print cols[i]
axarr_X[i].set_yticks([1])
axarr_X[i].set_xticklabels([])
axarr_X[i].set_yticklabels([str(cols[i])], fontproperties=font)
#ax.set_xticklabels([str(cols[i])],horizontalalignment='center',fontproperties=font)
# ax.spines['top'].set_visible(False)
# ax.spines['right'].set_visible(False)
# ax.spines['left'].set_visible(False)
if marker:
labelsL_str = [item[1] + (marker % item[0]).rjust(6)
for item in zip(yMark_L.values, labelsL.values)]
labelsR_str = [(marker % item[0]).ljust(6) + item[1]
for item in zip(yMark_R.values, labelsR.values)]
ylabelsL_str = map(lambda el: marker % el, yMark_L.values)
ylabelsR_str = map(lambda el: marker % el, yMark_R.values)
else:
labelsL_str = labelsL.values
labelsR_str = labelsR.values
ylabelsL_str = map(lambda el: u'', yPos_L.values)
ylabelsR_str = map(lambda el: u'', yPos_R.values)
if i == 0:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels(labelsL_str, fontproperties=font)
elif marker:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels(ylabelsL_str,
fontproperties=font,
ha='right'
) #ha='center')#,backgroundcolor='w')
else:
plt.setp(ax.get_yticklabels(), visible=False)
wspace = 0
if i == len(cols) - 2:
bx = ax.twinx()
bx.set_ybound(ax.get_ybound())
bx.set_yticks(yPos_R.values)
bx.set_yticklabels(labelsR_str, fontproperties=font)
bx.yaxis.set_tick_params(width=0)
bx_X = axarr_X[i].twinx()
bx_X.set_xticklabels([])
bx_X.set_yticks([1])
bx_X.yaxis.set_tick_params(width=0)
bx_X.set_yticklabels([str(cols[i + 1])], fontproperties=font)
if kind == 'ordinal':
ax.invert_yaxis()
if bx:
bx.invert_yaxis()
if color:
for tl in ax.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
print('fail')
pass
if bx:
for tl in bx.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
pass
if color:
for kw, c in color.items():
for j, lab__ in enumerate(yPos_.index):
if kw in lab__:
lines[j].set_color(c)
lines[j].set_linewidth(2)
lines[j].set_alpha(0.6)
for kk, tic_pos in enumerate(
ax.yaxis.get_ticklocs()):
if yPos_.values[j][0] == tic_pos:
ax.yaxis.get_ticklabels()[kk].set_color(c)
ax.yaxis.set_tick_params(width=0)
ax.xaxis.set_tick_params(width=0)
ax.xaxis.grid(False)
f.suptitle(title, x=0.5, y=0.02, fontproperties=font)
plt.tight_layout()
for ax in f.axes:
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
tw = ax.yaxis.get_text_widths(renderer)[0]
#dpi = f.properties()['dpi']
if wspace == 0:
pass
else:
#wspace = tw/dpi
aw = ax.get_tightbbox(renderer).width
wspace = tw / aw * 1.4
#f.subplots_adjust(wspace=wspace)
f.subplots_adjust(wspace=wspace)
if kind == "stack":
f.subplots_adjust(wspace=wspace, hspace=0)
else:
pass
if savename:
f.savefig(os.path.join('Output', savename), dpi=dpi)
#os.system("start " + savename)
return f
def slope(
data,
kind='interval',
marker='%0.f',
color=None,
title='',
font_family='GillSans',
font_size=12,
width=12,
height=8,
ax=None,
savename=None,
dpi=150,
wspace=None,
):
"""====
Slope
====
Definition: slope(data,kind=['interval','ordinal'],height,width,font_size,savename,color,title)
----
Plot Slope plot Tufte Style
:class:`matplotlib.figure.Figure object`.
Parameters
----------
data : pandas dataFrame
index indicate the categories
columns indicate time / period
marker style : str, format
Format to present the data
default '%0.f'
label_position : str ['ordinal', 'interval']
how to position labels.
Interval will place them according to their values
Ordinal will place them according to their rank
font_family : font family name installed on your system
font_size : set the font size
in case your data have more lines than you can have text lines of text
in your figure height, data will be binned to fit
(default 12)
height : Figure height in inches (default 12)
with : Figure width in inches (default 8)
savename : file path to save your graph
color : a dictionary {label:color}
title : a title at the bottom of the graph
Examples
--------
>>> data = pd.read_csv(os.path.join('Data','EU_GDP_2007_2013.csv'),index_col=0,na_values='-')
>>> f = slope(data/1000,kind='interval',height= 12,width=20,font_size=12,savename='EU_interval.png',title = u'title')
"""
font = FontProperties(font_family)
font.set_size(font_size)
bx = None
df = data.copy()
cols = df.columns
df['__label__'] = df.index
df['__order__'] = range(len(df.index))
if kind == 'stack':
f, axarr = plt.subplots(len(df),
len(cols) - 1,
facecolor="w",
squeeze=False,
sharex=True) #,sharey=True)
else:
#f, axarr = plt.subplots(2,len(cols)-1,facecolor="w",squeeze=True,figsize=(width,height),dpi=30)#,sharex=True)#,sharey=True)
f = plt.figure(figsize=(width, height), dpi=30, facecolor="w")
gs = gridspec.GridSpec(
nrows=20, ncols=len(cols) - 1
) # the 20 rows are just there to provide enought space for the title
axarr = []
axarr_X = []
for i in range(len(cols) - 1):
axarr.append(plt.subplot(gs[:19, i]))
axarr_X.append(plt.subplot(gs[19, i]))
axarr = np.array(axarr)
axarr_X = np.array(axarr_X)
renderer = f.canvas.get_renderer()
data_range = [data.min().min(), data.max().max()]
fh = f.get_figheight()
fw = f.get_figwidth()
fdpi = f.get_dpi()
nt = fh // (font.get_size() / 72) / 2
res = np.diff(data_range)[0] / nt * 2
if not hasattr(axarr, 'transpose'):
axarr = [axarr]
for i in range((len(cols) - 1)):
ax = axarr[i]
axarr_X[i].yaxis.set_tick_params(width=0)
axarr_X[i].xaxis.set_tick_params(width=0)
"""
from matplotlib.offsetbox import AnchoredOffsetbox, TextArea, HPacker
# orange label
obox1 = TextArea("orange - ", textprops=dict(color="k", size=15))
obox2 = TextArea("5 ", textprops=dict(color="b", size=15))
obox3 = TextArea(": ", textprops=dict(color="k", size=15))
obox4 = TextArea("10 ", textprops=dict(color="r", size=15))
orangebox = HPacker(children=[obox1, obox2, obox3, obox4],
align="center", pad=0, sep=5)
"""
if kind == 'interval':
labelsL = df.groupby(pd.cut(df[cols[i]], nt))['__label__'].agg(
', '.join).dropna()
labelsR = df.groupby(pd.cut(df[cols[i + 1]], nt))['__label__'].agg(
', '.join).dropna()
yPos_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yPos_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yMark_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yMark_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yPos_ = df[[cols[i], cols[i + 1]]]
if kind == 'ordinal':
yPos_L = df[[
cols[i]
]].rank(ascending=False).applymap(lambda el: round(el + 0.1))
yPos_R = df[[
cols[i + 1]
]].rank(ascending=False).applymap(lambda el: round(el + 0.1))
yMark_L = df.groupby(cols[i])[cols[i]].mean().dropna()
yMark_R = df.groupby(cols[i + 1])[cols[i + 1]].mean().dropna()
yMark_L.sort(ascending=False)
yMark_R.sort(ascending=False)
#print yMark_L
labelsL = df.groupby(yPos_L[cols[i]].values)['__label__'].agg(
', '.join)
labelsR = df.groupby(yPos_R[cols[i + 1]].values)['__label__'].agg(
', '.join)
yPos_L.sort(cols[i], inplace=True)
yPos_R.sort(cols[i + 1], inplace=True)
yPos_ = yPos_L.join(yPos_R) #.sort(cols[i],inplace=True)
# if i == 1:
# #print yPos_.T
# print labelsL
# #yPos_ = df[[cols[i],cols[i+1]]]
#
# if kind=='stack' :
#
# yPos_L = df[cols[i]].rank()
# yPos_R = df[cols[i+1]].rank()
#
# labelsL = df.groupby(yPos_L)['__label__'].agg(', '.join)
# labelsR = df.groupby(yPos_R)['__label__'].agg(', '.join)
#
# yPos_ = yPos_L.join(yPos_R)
#
# yPos_L = labelsL.index.values
# yPos_R = labelsR.index.values
if kind == "stack":
ax.plot([0, 1], [0, 1], color='k', alpha=0.4)
else:
#print yPos_
lines = ax.plot(yPos_.T, color='k', alpha=0.4)
ax.spines['bottom'].set_visible(False)
ax.xaxis.set_ticks_position('bottom')
if kind == "ordinal":
ax.set_ybound(lower=1, upper=len(yPos_))
if kind == "interval":
ax.set_ybound(lower=data.min().min(), upper=data.max().max())
#ax.set_xbound(lower=0,upper=1)
ax.set_xticklabels([])
#print cols[i]
axarr_X[i].set_yticks([1])
axarr_X[i].set_xticklabels([])
axarr_X[i].set_yticklabels([str(cols[i])], fontproperties=font)
#ax.set_xticklabels([str(cols[i])],horizontalalignment='center',fontproperties=font)
# ax.spines['top'].set_visible(False)
# ax.spines['right'].set_visible(False)
# ax.spines['left'].set_visible(False)
if marker:
labelsL_str = [
item[1] + (marker % item[0]).rjust(6)
for item in zip(yMark_L.values, labelsL.values)
]
labelsR_str = [(marker % item[0]).ljust(6) + item[1]
for item in zip(yMark_R.values, labelsR.values)]
ylabelsL_str = map(lambda el: marker % el, yMark_L.values)
ylabelsR_str = map(lambda el: marker % el, yMark_R.values)
else:
labelsL_str = labelsL.values
labelsR_str = labelsR.values
ylabelsL_str = map(lambda el: u'', yPos_L.values)
ylabelsR_str = map(lambda el: u'', yPos_R.values)
if i == 0:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels(labelsL_str, fontproperties=font)
elif marker:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels(
ylabelsL_str, fontproperties=font,
ha='right') #ha='center')#,backgroundcolor='w')
else:
plt.setp(ax.get_yticklabels(), visible=False)
wspace = 0
if i == len(cols) - 2:
bx = ax.twinx()
bx.set_ybound(ax.get_ybound())
bx.set_yticks(yPos_R.values)
bx.set_yticklabels(labelsR_str, fontproperties=font)
bx.yaxis.set_tick_params(width=0)
bx_X = axarr_X[i].twinx()
bx_X.set_xticklabels([])
bx_X.set_yticks([1])
bx_X.yaxis.set_tick_params(width=0)
bx_X.set_yticklabels([str(cols[i + 1])], fontproperties=font)
if kind == 'ordinal':
ax.invert_yaxis()
if bx:
bx.invert_yaxis()
if color:
for tl in ax.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
print('fail')
pass
if bx:
for tl in bx.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
pass
if color:
for kw, c in color.items():
for j, lab__ in enumerate(yPos_.index):
if kw in lab__:
lines[j].set_color(c)
lines[j].set_linewidth(2)
lines[j].set_alpha(0.6)
for kk, tic_pos in enumerate(
ax.yaxis.get_ticklocs()):
if yPos_.values[j][0] == tic_pos:
ax.yaxis.get_ticklabels()[kk].set_color(c)
ax.yaxis.set_tick_params(width=0)
ax.xaxis.set_tick_params(width=0)
ax.xaxis.grid(False)
f.suptitle(title, x=0.5, y=0.02, fontproperties=font)
plt.tight_layout()
for ax in f.axes:
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
tw = ax.yaxis.get_text_widths(renderer)[0]
#dpi = f.properties()['dpi']
if wspace == 0:
pass
else:
#wspace = tw/dpi
aw = ax.get_tightbbox(renderer).width
wspace = tw / aw * 1.4
#f.subplots_adjust(wspace=wspace)
f.subplots_adjust(wspace=wspace)
if kind == "stack":
f.subplots_adjust(wspace=wspace, hspace=0)
else:
pass
if savename:
f.savefig(os.path.join('Output', savename), dpi=dpi)
#os.system("start " + savename)
return f
def slope(data,
kind='interval',
marker='%0.f',
color=None,
title='',
font_family='GillSans',
font_size=12,
width=12,
height=8,
ax=None,
savename=None,
dpi=150,
wspace=None, ):
font = FontProperties(font_family)
font.set_size(font_size)
bx = None
df = data.copy()
cols = df.columns
df['__label__'] = df.index
df['__order__'] = range(len(df.index))
if kind == 'stack':
f, axarr = plt.subplots(len(df), len(cols) - 1,
facecolor="w",
squeeze=False,
sharex=True) #,sharey=True)
else:
f = plt.figure(figsize=(width, height), dpi=30, facecolor="w")
gs = gridspec.GridSpec(
nrows=20,
ncols=len(cols) - 1
) # the 20 rows are just there to provide enought space for the title
axarr = []
axarr_X = []
for i in range(len(cols) - 1):
axarr.append(plt.subplot(gs[:19, i]))
axarr_X.append(plt.subplot(gs[19, i]))
axarr = np.array(axarr)
axarr_X = np.array(axarr_X)
renderer = f.canvas.get_renderer()
data_range = [data.min().min(), data.max().max()]
fh = f.get_figheight()
fw = f.get_figwidth()
fdpi = f.get_dpi()
nt = fh // (font.get_size() / 72) / 2
res = np.diff(data_range)[0] / nt * 2
if not hasattr(axarr, 'transpose'):
axarr = [axarr]
for i in range((len(cols) - 1)):
ax = axarr[i]
axarr_X[i].yaxis.set_tick_params(width=0)
axarr_X[i].xaxis.set_tick_params(width=0)
"""
from matplotlib.offsetbox import AnchoredOffsetbox, TextArea, HPacker
# orange label
obox1 = TextArea("orange - ", textprops=dict(color="k", size=15))
obox2 = TextArea("5 ", textprops=dict(color="b", size=15))
obox3 = TextArea(": ", textprops=dict(color="k", size=15))
obox4 = TextArea("10 ", textprops=dict(color="r", size=15))
orangebox = HPacker(children=[obox1, obox2, obox3, obox4],
align="center", pad=0, sep=5)
"""
if kind == 'interval':
labelsL = df.groupby(pd.cut(df[cols[i]], nt))['__label__'].agg(
', '.join).dropna()
labelsR = df.groupby(pd.cut(df[cols[i + 1]], nt))['__label__'].agg(
', '.join).dropna()
yPos_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yPos_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yMark_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yMark_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yPos_ = df[[cols[i], cols[i + 1]]]
if kind == 'ordinal':
yPos_L = df[[cols[i]]].rank(ascending=False).applymap(
lambda el: round(el + 0.1))
yPos_R = df[[cols[i + 1]]].rank(ascending=False).applymap(
lambda el: round(el + 0.1))
yMark_L = df.groupby(cols[i])[cols[i]].mean().dropna()
yMark_R = df.groupby(cols[i + 1])[cols[i + 1]].mean().dropna()
yMark_L.sort(ascending=False)
yMark_R.sort(ascending=False)
#print yMark_L
labelsL = df.groupby(yPos_L[cols[i]].values)['__label__'].agg(
', '.join)
labelsR = df.groupby(yPos_R[cols[i + 1]].values)['__label__'].agg(
', '.join)
yPos_L.sort(cols[i], inplace=True)
yPos_R.sort(cols[i + 1], inplace=True)
yPos_ = yPos_L.join(yPos_R) #.sort(cols[i],inplace=True)
# if i == 1:
# #print yPos_.T
# print labelsL
# #yPos_ = df[[cols[i],cols[i+1]]]
#
# if kind=='stack' :
#
# yPos_L = df[cols[i]].rank()
# yPos_R = df[cols[i+1]].rank()
#
# labelsL = df.groupby(yPos_L)['__label__'].agg(', '.join)
# labelsR = df.groupby(yPos_R)['__label__'].agg(', '.join)
#
# yPos_ = yPos_L.join(yPos_R)
#
# yPos_L = labelsL.index.values
# yPos_R = labelsR.index.values
if kind == "stack":
ax.plot([0, 1], [0, 1], color='k', alpha=0.4)
else:
#print yPos_
lines = ax.plot(yPos_.T, color='k', alpha=0.4)
ax.spines['bottom'].set_visible(False)
ax.xaxis.set_ticks_position('bottom')
if kind == "ordinal":
ax.set_ybound(lower=1, upper=len(yPos_))
if kind == "interval":
ax.set_ybound(lower=data.min().min(), upper=data.max().max())
#ax.set_xbound(lower=0,upper=1)
ax.set_xticklabels([])
#print cols[i]
axarr_X[i].set_yticks([1])
axarr_X[i].set_xticklabels([])
axarr_X[i].set_yticklabels([str(cols[i])], fontproperties=font)
if marker:
labelsL_str = [item[1] + (marker % item[0]).rjust(6)
for item in zip(yMark_L.values, labelsL.values)]
labelsR_str = [(marker % item[0]).ljust(6) + item[1]
for item in zip(yMark_R.values, labelsR.values)]
ylabelsL_str = map(lambda el: marker % el, yMark_L.values)
ylabelsR_str = map(lambda el: marker % el, yMark_R.values)
else:
labelsL_str = labelsL.values
labelsR_str = labelsR.values
ylabelsL_str = map(lambda el: u'', yPos_L.values)
ylabelsR_str = map(lambda el: u'', yPos_R.values)
if i == 0:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels(labelsL_str, fontproperties=font)
elif marker:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels([el for el in ylabelsL_str],
fontproperties=font,
ha='right'
) #ha='center')#,backgroundcolor='w')
else:
plt.setp(ax.get_yticklabels(), visible=False)
wspace = 0
if i == len(cols) - 2:
bx = ax.twinx()
bx.set_ybound(ax.get_ybound())
bx.set_yticks(yPos_R.values)
bx.set_yticklabels(labelsR_str, fontproperties=font)
bx.yaxis.set_tick_params(width=0)
bx_X = axarr_X[i].twinx()
bx_X.set_xticklabels([])
bx_X.set_yticks([1])
bx_X.yaxis.set_tick_params(width=0)
bx_X.set_yticklabels([str(cols[i + 1])], fontproperties=font)
if kind == 'ordinal':
ax.invert_yaxis()
if bx:
bx.invert_yaxis()
if color:
for tl in ax.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
print('fail')
pass
if bx:
for tl in bx.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
pass
if color:
for kw, c in color.items():
for j, lab__ in enumerate(yPos_.index):
if kw in lab__:
lines[j].set_color(c)
lines[j].set_linewidth(2)
lines[j].set_alpha(0.6)
for kk, tic_pos in enumerate(
ax.yaxis.get_ticklocs()):
if yPos_.values[j][0] == tic_pos:
ax.yaxis.get_ticklabels()[kk].set_color(c)
ax.yaxis.set_tick_params(width=0)
ax.xaxis.set_tick_params(width=0)
ax.xaxis.grid(False)
f.suptitle(title, x=0.5, y=0.02, fontproperties=font)
plt.tight_layout()
for ax in f.axes:
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
tw = ax.yaxis.get_text_widths(renderer)[0]
if wspace == 0:
pass
else:
#wspace = tw/dpi
aw = ax.get_tightbbox(renderer).width
wspace = tw / aw * 1.4
f.subplots_adjust(wspace=wspace)
if kind == "stack":
f.subplots_adjust(wspace=wspace, hspace=0)
else:
pass
if savename:
f.savefig( savename, dpi=dpi)
return f
def slope(
data,
kind='interval',
marker='%0.f',
color=None,
title='',
font_family='GillSans',
font_size=12,
width=12,
height=8,
ax=None,
savename=None,
dpi=150,
wspace=None,
):
font = FontProperties(font_family)
font.set_size(font_size)
bx = None
df = data.copy()
cols = df.columns
df['__label__'] = df.index
df['__order__'] = range(len(df.index))
if kind == 'stack':
f, axarr = plt.subplots(len(df),
len(cols) - 1,
facecolor="w",
squeeze=False,
sharex=True) #,sharey=True)
else:
f = plt.figure(figsize=(width, height), dpi=30, facecolor="w")
gs = gridspec.GridSpec(
nrows=20, ncols=len(cols) - 1
) # the 20 rows are just there to provide enought space for the title
axarr = []
axarr_X = []
for i in range(len(cols) - 1):
axarr.append(plt.subplot(gs[:19, i]))
axarr_X.append(plt.subplot(gs[19, i]))
axarr = np.array(axarr)
axarr_X = np.array(axarr_X)
renderer = f.canvas.get_renderer()
data_range = [data.min().min(), data.max().max()]
fh = f.get_figheight()
fw = f.get_figwidth()
fdpi = f.get_dpi()
nt = fh // (font.get_size() / 72) / 2
res = np.diff(data_range)[0] / nt * 2
if not hasattr(axarr, 'transpose'):
axarr = [axarr]
for i in range((len(cols) - 1)):
ax = axarr[i]
axarr_X[i].yaxis.set_tick_params(width=0)
axarr_X[i].xaxis.set_tick_params(width=0)
"""
from matplotlib.offsetbox import AnchoredOffsetbox, TextArea, HPacker
# orange label
obox1 = TextArea("orange - ", textprops=dict(color="k", size=15))
obox2 = TextArea("5 ", textprops=dict(color="b", size=15))
obox3 = TextArea(": ", textprops=dict(color="k", size=15))
obox4 = TextArea("10 ", textprops=dict(color="r", size=15))
orangebox = HPacker(children=[obox1, obox2, obox3, obox4],
align="center", pad=0, sep=5)
"""
if kind == 'interval':
labelsL = df.groupby(pd.cut(df[cols[i]], nt))['__label__'].agg(
', '.join).dropna()
labelsR = df.groupby(pd.cut(df[cols[i + 1]], nt))['__label__'].agg(
', '.join).dropna()
yPos_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yPos_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yMark_L = df.groupby(pd.cut(df[cols[i]],
nt))[cols[i]].mean().dropna()
yMark_R = df.groupby(pd.cut(df[cols[i + 1]],
nt))[cols[i + 1]].mean().dropna()
yPos_ = df[[cols[i], cols[i + 1]]]
if kind == 'ordinal':
yPos_L = df[[
cols[i]
]].rank(ascending=False).applymap(lambda el: round(el + 0.1))
yPos_R = df[[
cols[i + 1]
]].rank(ascending=False).applymap(lambda el: round(el + 0.1))
yMark_L = df.groupby(cols[i])[cols[i]].mean().dropna()
yMark_R = df.groupby(cols[i + 1])[cols[i + 1]].mean().dropna()
yMark_L.sort(ascending=False)
yMark_R.sort(ascending=False)
#print yMark_L
labelsL = df.groupby(yPos_L[cols[i]].values)['__label__'].agg(
', '.join)
labelsR = df.groupby(yPos_R[cols[i + 1]].values)['__label__'].agg(
', '.join)
yPos_L.sort(cols[i], inplace=True)
yPos_R.sort(cols[i + 1], inplace=True)
yPos_ = yPos_L.join(yPos_R) #.sort(cols[i],inplace=True)
# if i == 1:
# #print yPos_.T
# print labelsL
# #yPos_ = df[[cols[i],cols[i+1]]]
#
# if kind=='stack' :
#
# yPos_L = df[cols[i]].rank()
# yPos_R = df[cols[i+1]].rank()
#
# labelsL = df.groupby(yPos_L)['__label__'].agg(', '.join)
# labelsR = df.groupby(yPos_R)['__label__'].agg(', '.join)
#
# yPos_ = yPos_L.join(yPos_R)
#
# yPos_L = labelsL.index.values
# yPos_R = labelsR.index.values
if kind == "stack":
ax.plot([0, 1], [0, 1], color='k', alpha=0.4)
else:
#print yPos_
lines = ax.plot(yPos_.T, color='k', alpha=0.4)
ax.spines['bottom'].set_visible(False)
ax.xaxis.set_ticks_position('bottom')
if kind == "ordinal":
ax.set_ybound(lower=1, upper=len(yPos_))
if kind == "interval":
ax.set_ybound(lower=data.min().min(), upper=data.max().max())
#ax.set_xbound(lower=0,upper=1)
ax.set_xticklabels([])
#print cols[i]
axarr_X[i].set_yticks([1])
axarr_X[i].set_xticklabels([])
axarr_X[i].set_yticklabels([str(cols[i])], fontproperties=font)
if marker:
labelsL_str = [
item[1] + (marker % item[0]).rjust(6)
for item in zip(yMark_L.values, labelsL.values)
]
labelsR_str = [(marker % item[0]).ljust(6) + item[1]
for item in zip(yMark_R.values, labelsR.values)]
ylabelsL_str = map(lambda el: marker % el, yMark_L.values)
ylabelsR_str = map(lambda el: marker % el, yMark_R.values)
else:
labelsL_str = labelsL.values
labelsR_str = labelsR.values
ylabelsL_str = map(lambda el: u'', yPos_L.values)
ylabelsR_str = map(lambda el: u'', yPos_R.values)
if i == 0:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels(labelsL_str, fontproperties=font)
elif marker:
ax.set_yticks(yPos_L.values)
ax.set_yticklabels(
[el for el in ylabelsL_str],
fontproperties=font,
ha='right') #ha='center')#,backgroundcolor='w')
else:
plt.setp(ax.get_yticklabels(), visible=False)
wspace = 0
if i == len(cols) - 2:
bx = ax.twinx()
bx.set_ybound(ax.get_ybound())
bx.set_yticks(yPos_R.values)
bx.set_yticklabels(labelsR_str, fontproperties=font)
bx.yaxis.set_tick_params(width=0)
bx_X = axarr_X[i].twinx()
bx_X.set_xticklabels([])
bx_X.set_yticks([1])
bx_X.yaxis.set_tick_params(width=0)
bx_X.set_yticklabels([str(cols[i + 1])], fontproperties=font)
if kind == 'ordinal':
ax.invert_yaxis()
if bx:
bx.invert_yaxis()
if color:
for tl in ax.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
print('fail')
pass
if bx:
for tl in bx.yaxis.get_ticklabels():
try:
for kw, c in color.items():
if kw in tl.get_text():
tl.set_color(c)
except:
pass
if color:
for kw, c in color.items():
for j, lab__ in enumerate(yPos_.index):
if kw in lab__:
lines[j].set_color(c)
lines[j].set_linewidth(2)
lines[j].set_alpha(0.6)
for kk, tic_pos in enumerate(
ax.yaxis.get_ticklocs()):
if yPos_.values[j][0] == tic_pos:
ax.yaxis.get_ticklabels()[kk].set_color(c)
ax.yaxis.set_tick_params(width=0)
ax.xaxis.set_tick_params(width=0)
ax.xaxis.grid(False)
f.suptitle(title, x=0.5, y=0.02, fontproperties=font)
plt.tight_layout()
for ax in f.axes:
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
tw = ax.yaxis.get_text_widths(renderer)[0]
if wspace == 0:
pass
else:
#wspace = tw/dpi
aw = ax.get_tightbbox(renderer).width
wspace = tw / aw * 1.4
f.subplots_adjust(wspace=wspace)
if kind == "stack":
f.subplots_adjust(wspace=wspace, hspace=0)
else:
pass
if savename:
f.savefig(savename, dpi=dpi)
return f
class Chart:
def __init__(self, props, subdefaults):
self.file = None
self.filename = None
self.props = {
"imageType": "png", # Output image type.
"dpi": 72, # Image DPI resolution.
"width": 800, # Output image width in pixels (vs. DPI).
"height": 600, # Output image height in pixels (vs. DPI).
"padding": 50, # Padding around the figure edge, in pixels.
"textPadding": 3, # Padding around text, in pixels.
"fontFamily": "sans-serif", # Font family.
"fontName": "Luxi Sans", # Font name.
"fontSize": 12, # Size of non-title text, in pixels.
"titleFontName": "Bitstream Vera Sans",
"titleFontSize": 18, # Size of title text, in pixels.
"subtitleFontSize": 14, # Size of subtitle text, in pixels.
"axtitleFontSize": 16, # Size of axis title text, in pixels.
"xAxisScale": "lin", # X axis scale, lin or log.
"yAxisScale": "lin", # Y axis scale, lin or log.
"square": False, # Force square layout.
"integral": False, #force integral display on legend
"notitle": False, #suppress title
"nolabels": False, #suppress axis labels
"sort":False, #sort items and legend entries by value
"max_legend":100 #maximum items in the legend
}
for (k, v) in subdefaults.iteritems():
self.props[k] = v
for (k, v) in props.iteritems():
self.props[k] = v
self.font = FontProperties()
self.font.set_family(self.get('fontFamily'))
self.font.set_name(self.get('fontName'))
self.font.set_size(float(self.get('fontSize')))
self.tfont = FontProperties()
self.tfont.set_family(self.get('titleFontFamily', self.font.get_family()[-1]))
self.tfont.set_name(self.get('titleFontName', self.font.get_name()))
self.tfont.set_size(self.get('titleFontSize', self.font.get_size()))
self.tfont.set_weight('bold')
self.sfont = FontProperties()
self.sfont.set_family(self.get('subtitleFontFamily', self.tfont.get_family()[-1]))
self.sfont.set_name(self.get('subtitleFontName', self.tfont.get_name()))
self.sfont.set_size(self.get('subtitleFontSize', self.tfont.get_size()))
self.afont = FontProperties()
self.afont.set_family(self.get('axtitleFontFamily', self.tfont.get_family()[-1]))
self.afont.set_name(self.get('axtitleFontName', self.tfont.get_name()))
self.afont.set_size(self.get('axtitleFontSize', self.tfont.get_size()))
self.afont.set_weight('bold')
def __del__(self):
if self.file != None:
os.close(self.file)
def get(self, key, default=None):
return getattr(self, key, self.props.get(key, default))
def draw(self):
(fig, canvas, w, h) = self.canvas()
fig.text(.5, .5, "No data.", horizontalalignment='center', fontproperties=self.font)
return self.save(fig, canvas)
def legend(self):
(fig, canvas, w, h) = self.canvas()
fig.text(.5, .5, "No legend.", horizontalalignment='center', fontproperties=self.font)
return self.save(fig, canvas)
def details(self):
return {}
def canvas(self):
type = self.get("imageType", "png")
fig = Figure()
if type == "png":
canvas = FigureCanvasAgg(fig)
(self.file, self.filename) = mkstemp(".%s" % type)
elif type == "svg":
canvas = FigureCanvasSVG(fig)
(self.file, self.filename) = mkstemp(".%s" % type)
elif type == "pdf":
canvas = FigureCanvasPdf(fig)
(self.file, self.filename) = mkstemp(".%s" % type)
elif type == "ps" or type == "eps":
canvas = FigureCanvasPS(fig)
(self.file, self.filename) = mkstemp(".%s" % type)
else:
raise "Invalid render target requested"
# Set basic figure parameters
dpi = float(self.get('dpi'))
(w, h) = (float(self.get('width')), float(self.get('height')))
(win, hin) = (w/dpi, h/dpi)
fig.set_size_inches(win, hin)
fig.set_dpi(dpi)
fig.set_facecolor('white')
return (fig, canvas, w, h)
def save(self, fig, canvas):
canvas.draw()
if not self.filename:
canvas.print_figure(self.file, dpi=float(self.get('dpi')))
return self.file
else:
canvas.print_figure(self.filename, dpi=float(self.get('dpi')))
f = file(self.filename, "r") # PS backend writes over the file
os.remove(self.filename) # return os.fdopen(self.file)
os.close(self.file)
self.file = None
self.filename = None
return f
def prepare(self):
# Create canvas and determine figure parameters
(fig, canvas, w, h) = self.canvas()
dpif = float(self.get('dpi')) / 72
padding = float(self.get('padding')) * dpif / h
textPadding = float(self.get('textPadding')) * dpif
titleFontSize = float(self.get('titleFontSize'))
axFontSize = float(self.get('axtitleFontSize'))
subFontSize = float(self.get('subtitleFontSize'))
title = self.get("title", "").split("\n")
if not self.get("notitle",False):
hsub = (len(title)-1) * (subFontSize * dpif + 4) + textPadding
htitle = hsub + titleFontSize * dpif + textPadding * 2
else:
hsub = 0
htitle = 0
if self.get("nolabels",False):
padding = 0
# Configure axes
if self.get('square'):
minsize = 1 - 2*padding
axrect = (.5 - minsize/2 * h/w, padding, h/w * minsize, minsize)
else:
axrect = (padding, padding, 1 - 1.25*padding, 1 - htitle/h - padding)
ax = fig.add_axes(axrect)
#frame = ax.get_frame()
#frame.set_fill(False)
xlog = (str(self.get('xAxisScale', "lin")) == 'log')
ylog = (str(self.get('yAxisScale', "lin")) == 'log')
if xlog:
ax.semilogx()
if ylog:
ax.semilogy()
setp(ax.get_xticklabels(), fontproperties=self.font)
setp(ax.get_yticklabels(), fontproperties=self.font)
setp(ax.get_xticklines(), markeredgewidth=2.0, zorder=4.0)
setp(ax.get_yticklines(), markeredgewidth=2.0)
ax.grid(True, alpha=0.25, color='#000000', linewidth=0.1)
# Set titles
if not self.get("notitle",False):
ax.title = ax.text(.5, 1+(hsub+textPadding)/(axrect[-1]*h), title[0],
verticalalignment='bottom',
horizontalalignment='center',
transform=ax.transAxes,
clip_box=None,
fontproperties=self.tfont)
ax._set_artist_props(ax.title)
if len(title) > 1:
ax.subtitle = ax.text(.5, 1+textPadding/(axrect[-1]*h), "\n".join(title[1:]),
verticalalignment='bottom',
horizontalalignment='center',
transform=ax.transAxes,
clip_box=None,
fontproperties=self.sfont)
if not self.get("nolabels",False):
ax.set_xlabel(self.get("xAxisTitle", ""), fontproperties=self.afont)
ax.set_ylabel(self.get("yAxisTitle", ""), fontproperties=self.afont)
return (fig, canvas, ax)
def map(self):
return ''
def make(self):
img = self.draw().read()
legend = self.legend().read()
map = self.map()
return img,legend,map
