本文整理匯總了Python中matplotlib.ticker.EngFormatter方法的典型用法代碼示例。如果您正苦於以下問題：Python ticker.EngFormatter方法的具體用法？Python ticker.EngFormatter怎麽用？Python ticker.EngFormatter使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類matplotlib.ticker的用法示例。
在下文中一共展示了ticker.EngFormatter方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: plot_specgrams
# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import EngFormatter [as 別名]
def plot_specgrams(base_dir=CHART_DIR):
"""
Plot a bunch of spectrograms of wav files in different genres
"""
plt.clf()
genres = ["classical", "jazz", "country", "pop", "rock", "metal"]
num_files = 3
f, axes = plt.subplots(len(genres), num_files)
for genre_idx, genre in enumerate(genres):
for idx, fn in enumerate(glob.glob(os.path.join(GENRE_DIR, genre, "*.wav"))):
if idx == num_files:
break
axis = axes[genre_idx, idx]
axis.yaxis.set_major_formatter(EngFormatter())
axis.set_title("%s song %i" % (genre, idx + 1))
plot_specgram(axis, fn)
specgram_file = os.path.join(base_dir, "Spectrogram_Genres.png")
plt.savefig(specgram_file, bbox_inches="tight")
plt.show() 開發者ID:PacktPublishing，項目名稱:Building-Machine-Learning-Systems-With-Python-Second-Edition，代碼行數:24，代碼來源:fft.py
示例2: main
# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import EngFormatter [as 別名]
def main():
mm = machinemodel.MachineModel(sys.argv[1])
kernels = sorted(mm['benchmarks']['kernels'])
cache_levels = sorted(mm['benchmarks']['measurements'])
fig, axs = plt.subplots(len(cache_levels), 1, figsize=(7, 14), tight_layout=True)
lines = {}
for i, cache_level in enumerate(cache_levels):
max_bw = 0
max_bw_core = 0
axs[i].set_title(cache_level)
formatter1 = EngFormatter(places=0) # , sep="\N{THIN SPACE}") # U+2009
axs[i].yaxis.set_major_formatter(formatter1)
if cache_level == 'L1':
axs[i].set_ylabel("Bandwidth [B/s]")
else:
axs[i].set_ylabel("Bandwidth [B/s]\n(incl. write-allocate)")
axs[i].set_xlabel('cores')
# axs[i].set_xscale('log')
for ki, kernel in enumerate(kernels):
if cache_level == 'L1':
# L1 does not have write-allocate, so everything is measured correctly
factor = 1.0
else:
measurement_kernel_info = mm['benchmarks']['kernels'][kernel]
factor = (float(measurement_kernel_info['read streams']['bytes']) +
2.0 * float(measurement_kernel_info['write streams']['bytes']) -
float(measurement_kernel_info['read+write streams']['bytes'])) / \
(float(measurement_kernel_info['read streams']['bytes']) +
float(measurement_kernel_info['write streams']['bytes']))
for SMT in mm['benchmarks']['measurements'][cache_level]:
measurements = [
bw*factor
for bw in mm['benchmarks']['measurements'][cache_level][SMT]['results'][kernel]]
max_bw = max(measurements+[max_bw])
max_bw_core = max(max_bw_core, measurements[0])
lines[kernel], = axs[i].plot(
range(1, 1 + len(measurements)),
measurements,
linestyle=['-', '--', '..', '-.'][SMT-1],
color=kernel_colors[ki])
axs[i].set_xlim(1)
axs[i].axhline(max_bw, color='black')
axs[i].axhline(max_bw_core, color='black')
axs[i].set_yticks(np.append(axs[i].get_yticks(), [float(max_bw), float(max_bw_core)]))
axs[i].set_xticks(range(1, 1+len(measurements)))
fig.legend(lines.values(), lines.keys(), 'lower center', ncol=10)
fig.savefig(sys.argv[1]+'.pdf')
#plt.show()