本文整理汇总了Python中matplotlib.pylab.bar方法的典型用法代码示例。如果您正苦于以下问题:Python pylab.bar方法的具体用法?Python pylab.bar怎么用?Python pylab.bar使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类matplotlib.pylab
的用法示例。
在下文中一共展示了pylab.bar方法的8个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: plot_feat_importance
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def plot_feat_importance(feature_names, clf, name):
pylab.clf()
coef_ = clf.coef_
important = np.argsort(np.absolute(coef_.ravel()))
f_imp = feature_names[important]
coef = coef_.ravel()[important]
inds = np.argsort(coef)
f_imp = f_imp[inds]
coef = coef[inds]
xpos = np.array(range(len(coef)))
pylab.bar(xpos, coef, width=1)
pylab.title('Feature importance for %s' % (name))
ax = pylab.gca()
ax.set_xticks(np.arange(len(coef)))
labels = ax.set_xticklabels(f_imp)
for label in labels:
label.set_rotation(90)
filename = name.replace(" ", "_")
pylab.savefig(os.path.join(
CHART_DIR, "feat_imp_%s.png" % filename), bbox_inches="tight")
开发者ID:PacktPublishing,项目名称:Building-Machine-Learning-Systems-With-Python-Second-Edition,代码行数:23,代码来源:utils.py
示例2: plot_feat_importance
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def plot_feat_importance(feature_names, clf, name):
pylab.figure(num=None, figsize=(6, 5))
coef_ = clf.coef_
important = np.argsort(np.absolute(coef_.ravel()))
f_imp = feature_names[important]
coef = coef_.ravel()[important]
inds = np.argsort(coef)
f_imp = f_imp[inds]
coef = coef[inds]
xpos = np.array(list(range(len(coef))))
pylab.bar(xpos, coef, width=1)
pylab.title('Feature importance for %s' % (name))
ax = pylab.gca()
ax.set_xticks(np.arange(len(coef)))
labels = ax.set_xticklabels(f_imp)
for label in labels:
label.set_rotation(90)
filename = name.replace(" ", "_")
pylab.savefig(os.path.join(
CHART_DIR, "feat_imp_%s.png" % filename), bbox_inches="tight")
开发者ID:PacktPublishing,项目名称:Building-Machine-Learning-Systems-With-Python-Second-Edition,代码行数:23,代码来源:utils.py
示例3: _plot_NWOE_bins
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def _plot_NWOE_bins(NWOE_dict, feats):
"""
Plots the NWOE by bin for the subset of features interested in (form of list)
Parameters
----------
- NWOE_dict = dictionary output of `NWOE` function
- feats = list of features to plot NWOE for
Returns
-------
- plots of NWOE for each feature by bin
"""
for feat in feats:
fig, ax = _plot_defaults()
feat_df = NWOE_dict[feat].reset_index()
plt.bar(range(len(feat_df)), feat_df['NWOE'], tick_label=feat_df[str(feat)+'_bin'], color='k', alpha=0.5)
plt.xticks(rotation='vertical')
ax.set_title('NWOE by bin for '+str(feat))
ax.set_xlabel('Bin Interval');
return ax
示例4: save_state_images
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def save_state_images(frame_idx, states, net, device="cpu", max_states=200):
ofs = 0
p = np.arange(Vmin, Vmax + DELTA_Z, DELTA_Z)
for batch in np.array_split(states, 64):
states_v = torch.tensor(batch).to(device)
action_prob = net.apply_softmax(net(states_v)).data.cpu().numpy()
batch_size, num_actions, _ = action_prob.shape
for batch_idx in range(batch_size):
plt.clf()
for action_idx in range(num_actions):
plt.subplot(num_actions, 1, action_idx+1)
plt.bar(p, action_prob[batch_idx, action_idx], width=0.5)
plt.savefig("states/%05d_%08d.png" % (ofs + batch_idx, frame_idx))
ofs += batch_size
if ofs >= max_states:
break
示例5: save_transition_images
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def save_transition_images(batch_size, predicted, projected, next_distr, dones, rewards, save_prefix):
for batch_idx in range(batch_size):
is_done = dones[batch_idx]
reward = rewards[batch_idx]
plt.clf()
p = np.arange(Vmin, Vmax + DELTA_Z, DELTA_Z)
plt.subplot(3, 1, 1)
plt.bar(p, predicted[batch_idx], width=0.5)
plt.title("Predicted")
plt.subplot(3, 1, 2)
plt.bar(p, projected[batch_idx], width=0.5)
plt.title("Projected")
plt.subplot(3, 1, 3)
plt.bar(p, next_distr[batch_idx], width=0.5)
plt.title("Next state")
suffix = ""
if reward != 0.0:
suffix = suffix + "_%.0f" % reward
if is_done:
suffix = suffix + "_done"
plt.savefig("%s_%02d%s.png" % (save_prefix, batch_idx, suffix))
示例6: autolabel
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def autolabel(ax, rects, strfrm='%.2f'):
'''
Automatically add value over each bar in bar chart
http://matplotlib.org/1.4.2/examples/api/barchart_demo.html
'''
for rect in rects:
height = rect.get_height()
ax.text(rect.get_x()+rect.get_width()/2., 1.05*height, strfrm % float(height),
ha='center', va='bottom')
示例7: plotData
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def plotData(Data, nObsPlot=5000):
''' Plot data items, at most nObsPlot distinct points (for quick rendering)
'''
if type(Data) == bnpy.data.XData:
PRNG = np.random.RandomState(nObsPlot)
pIDs = PRNG.permutation(Data.nObs)[:nObsPlot]
if Data.dim > 1:
pylab.plot(Data.X[pIDs,0], Data.X[pIDs,1], 'k.')
else:
hist, bin_edges = pylab.histogram(Data.X, bins=25)
xs = bin_edges[:-1]
ys = np.asarray(hist, dtype=np.float32) / np.sum(hist)
pylab.bar(xs, ys, width=0.8*(bin_edges[1]-bin_edges[0]), color='k')
示例8: bar
# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import bar [as 别名]
def bar(self, key_word_sep=" ", title=None, **kwargs):
"""Generates a pylab bar plot from the result set.
``matplotlib`` must be installed, and in an
IPython Notebook, inlining must be on::
%%matplotlib inline
The last quantitative column is taken as the Y values;
all other columns are combined to label the X axis.
:param title: plot title, defaults to names of Y value columns
:param key_word_sep: string used to separate column values
from each other in labels
Any additional keyword arguments will be passsed
through to ``matplotlib.pylab.bar``.
"""
if not plt:
raise ImportError("Try installing matplotlib first.")
self.guess_pie_columns(xlabel_sep=key_word_sep)
plot = plt.bar(range(len(self.ys[0])), self.ys[0], **kwargs)
if self.xlabels:
plt.xticks(range(len(self.xlabels)), self.xlabels,
rotation=45)
plt.xlabel(self.xlabel)
plt.ylabel(self.ys[0].name)
return plot