本文整理汇总了Python中pylab.savefig方法的典型用法代码示例。如果您正苦于以下问题:Python pylab.savefig方法的具体用法?Python pylab.savefig怎么用?Python pylab.savefig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pylab
的用法示例。
在下文中一共展示了pylab.savefig方法的15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_hits
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def plot_hits(filename_fil, filename_dat):
""" Plot the hits in a .dat file. """
table = find_event.read_dat(filename_dat)
print(table)
plt.figure(figsize=(10, 8))
N_hit = len(table)
if N_hit > 10:
print("Warning: More than 10 hits found. Only plotting first 10")
N_hit = 10
for ii in range(N_hit):
plt.subplot(N_hit, 1, ii+1)
plot_event.plot_hit(filename_fil, filename_dat, ii)
plt.tight_layout()
plt.savefig(filename_dat.replace('.dat', '.png'))
plt.show()
示例2: train
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def train(self):
# self.load_model('./save_model/cartpole_a3c.h5')
agents = [Agent(i, self.actor, self.critic, self.optimizer, self.env_name, self.discount_factor,
self.action_size, self.state_size) for i in range(self.threads)]
for agent in agents:
agent.start()
while True:
time.sleep(20)
plot = scores[:]
pylab.plot(range(len(plot)), plot, 'b')
pylab.savefig("./save_graph/cartpole_a3c.png")
self.save_model('./save_model/cartpole_a3c.h5')
示例3: summarise_reads
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def summarise_reads(path):
"""Count reads in all files in path"""
resultfile = os.path.join(path, 'read_stats.csv')
files = glob.glob(os.path.join(path,'*.fastq'))
vals=[]
rl=[]
for f in files:
label = os.path.splitext(os.path.basename(f))[0]
s = utils.fastq_to_dataframe(f)
l = len(s)
vals.append([label,l])
print (label, l)
df = pd.DataFrame(vals,columns=['path','total reads'])
df.to_csv(resultfile)
df.plot(x='path',y='total reads',kind='barh')
plt.tight_layout()
plt.savefig(os.path.join(path,'total_reads.png'))
#df = pd.concat()
return df
示例4: plot_evaluation_episode_reward
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def plot_evaluation_episode_reward():
pylab.clf()
sns.set_context("poster")
pylab.plot(0, 0)
episodes = [0]
average_scores = [0]
median_scores = [0]
for n in xrange(len(csv_evaluation)):
params = csv_evaluation[n]
episodes.append(params[0])
average_scores.append(params[1])
median_scores.append(params[2])
pylab.plot(episodes, average_scores, sns.xkcd_rgb["windows blue"], lw=2)
pylab.xlabel("episodes")
pylab.ylabel("average score")
pylab.savefig("%s/evaluation_episode_average_reward.png" % args.plot_dir)
pylab.clf()
pylab.plot(0, 0)
pylab.plot(episodes, median_scores, sns.xkcd_rgb["windows blue"], lw=2)
pylab.xlabel("episodes")
pylab.ylabel("median score")
pylab.savefig("%s/evaluation_episode_median_reward.png" % args.plot_dir)
示例5: main
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def main():
l2_base_dir = '/media/admin228/00027E210001A5BD/train_pytorch/change_detection/CMU/prediction_cons/l2_5,6,7/roc'
cos_base_dir = '/media/admin228/00027E210001A5BD/train_pytorch/change_detection/CMU/prediction_cons/dist_cos_new_5,6,7/roc'
CSF_dir = os.path.join(l2_base_dir)
CSF_fig_dir = os.path.join(l2_base_dir,'fig.png')
end_number = 22
csf_conv5_l2_ls,csf_fc6_l2_ls,csf_fc7_l2_ls,x_l2 = get_csf_ls(l2_base_dir,end_number)
csf_conv5_cos_ls,csf_fc6_cos_ls,csf_fc7_cos_ls,x_cos = get_csf_ls(cos_base_dir,end_number)
Fig = pylab.figure()
setFigLinesBW(Fig)
#pylab.plot(x,csf_conv4_ls, color='k',label= 'conv4')
pylab.plot(x_l2,csf_conv5_l2_ls, color='m',label= 'l2:conv5')
pylab.plot(x_l2,csf_fc6_l2_ls, color = 'b',label= 'l2:fc6')
pylab.plot(x_l2,csf_fc7_l2_ls, color = 'g',label= 'l2:fc7')
pylab.plot(x_cos,csf_conv5_cos_ls, color='c',label= 'cos:conv5')
pylab.plot(x_cos,csf_fc6_cos_ls, color = 'r',label= 'cos:fc6')
pylab.plot(x_cos,csf_fc7_cos_ls, color = 'y',label= 'cos:fc7')
pylab.legend(loc='lower right', prop={'size': 10})
pylab.ylabel('RMS Contrast', fontsize=14)
pylab.xlabel('Epoch', fontsize=14)
pylab.savefig(CSF_fig_dir)
示例6: plot
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def plot(ifile, varkey, options, before='', after=''):
import pylab as pl
outpath = getattr(options, 'outpath', '.')
var = ifile.variables[varkey]
dims = [(k, l) for l, k in zip(var[:].shape, var.dimensions) if l > 1]
if len(dims) > 1:
raise ValueError(
'Plots can have only 1 non-unity dimensions; got %d - %s' %
(len(dims), str(dims)))
exec(before)
ax = pl.gca()
print(varkey, end='')
if options.logscale:
ax.set_yscale('log')
ax.plot(var[:].squeeze())
ax.set_xlabel('unknown')
ax.set_ylabel(getattr(var, 'standard_name',
varkey).strip() + ' ' + var.units.strip())
fmt = 'png'
figpath = os.path.join(outpath + '_1d_' + varkey + '.' + fmt)
exec(after)
pl.savefig(figpath)
print('Saved fig', figpath)
return figpath
示例7: on_epoch_end
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def on_epoch_end(self, epoch, logs={}):
self.model.save_weights(os.path.join(self.output_dir, 'weights%02d.h5' % (epoch)))
self.show_edit_distance(256)
word_batch = next(self.text_img_gen)[0]
res = decode_batch(self.test_func, word_batch['the_input'][0:self.num_display_words])
if word_batch['the_input'][0].shape[0] < 256:
cols = 2
else:
cols = 1
for i in range(self.num_display_words):
pylab.subplot(self.num_display_words // cols, cols, i + 1)
if K.image_data_format() == 'channels_first':
the_input = word_batch['the_input'][i, 0, :, :]
else:
the_input = word_batch['the_input'][i, :, :, 0]
pylab.imshow(the_input.T, cmap='Greys_r')
pylab.xlabel('Truth = \'%s\'\nDecoded = \'%s\'' % (word_batch['source_str'][i], res[i]))
fig = pylab.gcf()
fig.set_size_inches(10, 13)
pylab.savefig(os.path.join(self.output_dir, 'e%02d.png' % (epoch)))
pylab.close()
示例8: _plot_example
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def _plot_example(xv, yv, b):
"""Plot for debugging purposes."""
matplotlib.rcParams['font.family'] = "serif"
matplotlib.rcParams['font.sans-serif'] = "Times"
matplotlib.rcParams["legend.edgecolor"] = "None"
matplotlib.rcParams["axes.spines.top"] = False
matplotlib.rcParams["axes.spines.bottom"] = True
matplotlib.rcParams["axes.spines.left"] = True
matplotlib.rcParams["axes.spines.right"] = False
matplotlib.rcParams['axes.grid'] = True
matplotlib.rcParams['axes.grid.axis'] = 'both'
matplotlib.rcParams['axes.grid.which'] = 'major'
matplotlib.rcParams['legend.edgecolor'] = '1.0'
plt.plot(xv[:, 113], yv[:, 113], 'ko')
plt.plot(xv[:, 113], xv[:, 113] * b[113, 1] + b[113, 0], 'nneighbors')
# plt.plot(x[113], x[113]*b[113, 1] + b[113, 0], 'ro')
plt.grid(True)
plt.xlabel('Radiance, $\mu{W }nm^{-1} sr^{-1} cm^{-2}$')
plt.ylabel('Reflectance')
plt.show(block=True)
plt.savefig('empirical_line.pdf')
示例9: plotdata
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def plotdata(obsmode,spectrum,val,odict,sdict,
instr,fieldname,outdir,outname):
isetting=P.isinteractive()
P.ioff()
P.clf()
P.plot(obsmode,val,'.')
P.ylabel('(pysyn-syn)/syn')
P.xlabel('obsmode')
P.title("%s: %s"%(instr,fieldname))
P.savefig(os.path.join(outdir,outname+'_obsmode.ps'))
P.clf()
P.plot(spectrum,val,'.')
P.ylabel('(pysyn-syn)/syn')
P.xlabel('spectrum')
P.title("%s: %s"%(instr,fieldname))
P.savefig(os.path.join(outdir,outname+'_spectrum.ps'))
matplotlib.interactive(isetting)
示例10: save
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def save(GUI):
global txtResultPath
if GUI:
import pylab as pl
import nest.raster_plot
import nest.voltage_trace
logger.debug("Saving IMAGES into {0}".format(SAVE_PATH))
for key in spikedetectors:
try:
nest.raster_plot.from_device(spikedetectors[key], hist=True)
pl.savefig(f_name_gen(SAVE_PATH, "spikes_" + key.lower()), dpi=dpi_n, format='png')
pl.close()
except Exception:
print(" * * * from {0} is NOTHING".format(key))
txtResultPath = SAVE_PATH + 'txt/'
logger.debug("Saving TEXT into {0}".format(txtResultPath))
if not os.path.exists(txtResultPath):
os.mkdir(txtResultPath)
for key in spikedetectors:
save_spikes(spikedetectors[key], name=key)
with open(txtResultPath + 'timeSimulation.txt', 'w') as f:
for item in times:
f.write(item)
示例11: draw_graph_row
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def draw_graph_row(graphs,
index=0,
contract=True,
n_graphs_per_line=5,
size=4,
xlim=None,
ylim=None,
**args):
"""draw_graph_row."""
dim = len(graphs)
size_y = size
size_x = size * n_graphs_per_line * args.get('size_x_to_y_ratio', 1)
plt.figure(figsize=(size_x, size_y))
if xlim is not None:
plt.xlim(xlim)
plt.ylim(ylim)
else:
plt.xlim(xmax=3)
for i in range(dim):
plt.subplot(1, n_graphs_per_line, i + 1)
graph = graphs[i]
draw_graph(graph,
size=None,
pos=graph.graph.get('pos_dict', None),
**args)
if args.get('file_name', None) is None:
plt.show()
else:
row_file_name = '%d_' % (index) + args['file_name']
plt.savefig(row_file_name,
bbox_inches='tight',
transparent=True,
pad_inches=0)
plt.close()
示例12: dendrogram
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def dendrogram(data,
vectorizer,
method="ward",
color_threshold=1,
size=10,
filename=None):
"""dendrogram.
"median","centroid","weighted","single","ward","complete","average"
"""
data = list(data)
# get labels
labels = []
for graph in data:
label = graph.graph.get('id', None)
if label:
labels.append(label)
# transform input into sparse vectors
data_matrix = vectorizer.transform(data)
# labels
if not labels:
labels = [str(i) for i in range(data_matrix.shape[0])]
# embed high dimensional sparse vectors in 2D
from sklearn import metrics
from scipy.cluster.hierarchy import linkage, dendrogram
distance_matrix = metrics.pairwise.pairwise_distances(data_matrix)
linkage_matrix = linkage(distance_matrix, method=method)
plt.figure(figsize=(size, size))
dendrogram(linkage_matrix,
color_threshold=color_threshold,
labels=labels,
orientation='right')
if filename is not None:
plt.savefig(filename)
else:
plt.show()
示例13: save_plot
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def save_plot(self, filename):
plt.ion()
targarr = np.array(self.targvalue)
self.posi[0].set_xdata(self.wt_positions[:,0])
self.posi[0].set_ydata(self.wt_positions[:,1])
while len(self.plotel)>0:
self.plotel.pop(0).remove()
self.plotel = self.shape_plot.plot(np.array([self.wt_positions[[i,j],0] for i, j in self.elnet_layout.keys()]).T,
np.array([self.wt_positions[[i,j],1] for i, j in self.elnet_layout.keys()]).T, 'y-', linewidth=1)
for i in range(len(self.posb)):
self.posb[i][0].set_xdata(self.iterations)
self.posb[i][0].set_ydata(targarr[:,i])
self.legend.texts[i].set_text('%s = %8.2f'%(self.targname[i], targarr[-1,i]))
self.objf_plot.set_xlim([0, self.iterations[-1]])
self.objf_plot.set_ylim([0.5, 1.2])
if not self.title == '':
plt.title('%s = %8.2f'%(self.title, getattr(self, self.title)))
plt.draw()
#print self.iterations[-1] , ': ' + ', '.join(['%s=%6.2f'%(self.targname[i], targarr[-1,i]) for i in range(len(self.targname))])
with open(self.result_file+'.results','a') as f:
f.write( '%d:'%(self.inc) + ', '.join(['%s=%6.2f'%(self.targname[i], targarr[-1,i]) for i in range(len(self.targname))]) +
'\n')
#plt.show()
#plt.savefig(filename)
display(plt.gcf())
#plt.show()
clear_output(wait=True)
示例14: plotGraph
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def plotGraph(x, y, z, filename):
v = [0,5000,0,200]
plt.axis(v)
plt.scatter(x, y, alpha = 0.10, cmap=plt.cm.cool, edgecolors='None')
# plt.colorbar()
pylab.savefig(filename, bbox_inches = 0)
plt.clf()
#scale input data and plot graphs
示例15: saveBEVImageWithAxes
# 需要导入模块: import pylab [as 别名]
# 或者: from pylab import savefig [as 别名]
def saveBEVImageWithAxes(data, outputname, cmap = None, xlabel = 'x [m]', ylabel = 'z [m]', rangeX = [-10, 10], rangeXpx = None, numDeltaX = 5, rangeZ = [7, 62], rangeZpx = None, numDeltaZ = 5, fontSize = 16):
'''
:param data:
:param outputname:
:param cmap:
'''
aspect_ratio = float(data.shape[1])/data.shape[0]
fig = pylab.figure()
Scale = 8
# add +1 to get axis text
fig.set_size_inches(Scale*aspect_ratio+1,Scale*1)
ax = pylab.gca()
#ax.set_axis_off()
#fig.add_axes(ax)
if cmap != None:
pylab.set_cmap(cmap)
#ax.imshow(data, interpolation='nearest', aspect = 'normal')
ax.imshow(data, interpolation='nearest')
if rangeXpx == None:
rangeXpx = (0, data.shape[1])
if rangeZpx == None:
rangeZpx = (0, data.shape[0])
modBev_plot(ax, rangeX, rangeXpx, numDeltaX, rangeZ, rangeZpx, numDeltaZ, fontSize, xlabel = xlabel, ylabel = ylabel)
#plt.savefig(outputname, bbox_inches='tight', dpi = dpi)
pylab.savefig(outputname, dpi = data.shape[0]/Scale)
pylab.close()
fig.clear()