看起来第一张图中的数据点意外地覆盖了第二张图。我正在运行的代码正在运行几次,当我第一次运行时很短,第二次运行它时,我有一个较长的时间段,而短期内的数据点也是较长时间段的一部分。
那么在开始构建图形之前有没有办法清理图表?
您可以在此处查看构建图表的代码:
def create_graph(self, device):
# 800 and 355 pixels.
ticks = 5
width = 8
height = 3.55
dpi = 100
bgcolor = '#f3f6f6'
font = {
'size': 16,
'family': 'Arial'
}
plt.rc('font', **font)
# size of figure and setting background color
fig = plt.gcf()
fig.set_size_inches(width, height)
fig.set_facecolor(bgcolor)
# axis color, no ticks and bottom line in grey color.
ax = plt.axes(axisbg=bgcolor, frameon=True)
ax.xaxis.set_ticks_position('none')
ax.spines['bottom'].set_color('#aabcc2')
ax.yaxis.set_ticks_position('none')
# removing all but bottom spines
for key, sp in ax.spines.items():
if key != 'bottom':
sp.set_visible(False)
# setting amounts of ticks on y axis
yloc = plt.MaxNLocator(ticks)
ax.yaxis.set_major_locator(yloc)
x_no_ticks = 8
# Deciding how many ticks we want on the graph
locator = AutoDateLocator(maxticks=x_no_ticks)
formatter = AutoDateFormatter(locator)
# Formatter always chooses the most granular since we have granular dates
# either change format or round dates depending on how granular
# we want them to be for different date ranges.
formatter.scaled[1/(24.*60.)] = '%d/%m %H:%M'
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(formatter)
# turns off small ticks
plt.tick_params(axis='x',
which='both',
bottom='on',
top='off',
pad=10)
# Can't seem to set label color differently, changing tick_params color changes labels.
ax.xaxis.label.set_color('#FFFFFF')
# setting dates in x-axis automatically triggers use of AutoDateLocator
x = [datetime.fromtimestamp(point['x']) for point in device['data']]
y = [point['y'] for point in device['data']]
plt.plot(x, y, color='#53b4d4', linewidth=2)
# pick values for y-axis
y_ticks_values = np.array([point['y'] for point in device['data']])
y_ticks = np.linspace(y_ticks_values.min(), y_ticks_values.max(), ticks)
y_ticks = np.round(y_ticks, decimals=2)
plt.yticks(y_ticks, [str(val) + self.extract_unit(device) for val in y_ticks])
# plt.ylim(ymin=0.1) # Only show values of a certain threshold.
plt.tight_layout()
buf = io.BytesIO()
plt.savefig(buf,
format='png',
facecolor=fig.get_facecolor(),
dpi=dpi)
答案 0 :(得分:1)
您必须在plt.close()
之后添加plt.savefig()
。因此,下一个plt.gcf()
电话不会捕捉该数字。