import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.graph_objects as go
import plotly.express as px
from scipy.stats import gaussian_kde
import matplotlib.font_manager as fm
from matplotlib.colors import LinearSegmentedColormap
# 设置中文字体支持
plt.rcParams['font.sans-serif'] = ['SimHei', 'Arial Unicode MS', 'Microsoft YaHei', 'WenQuanYi Micro Hei']
plt.rcParams['axes.unicode_minus'] = False
# 设置随机种子,确保结果可复现
np.random.seed(42)
# 根据92.02%的高准确率生成模拟数据
# 总样本数
n_samples = 1000
# 正确样本比例 (92.02%)
correct_ratio = 0.9202
n_correct = int(n_samples * correct_ratio)
n_incorrect = n_samples - n_correct
# 生成预测不确定性数据
# 正确样本的不确定性较低,分布更集中
correct_uncertainty = np.random.normal(0.3, 0.15, n_correct)
# 错误样本的不确定性较高,分布更分散
incorrect_uncertainty = np.random.normal(1.2, 0.4, n_incorrect)
# 合并数据
uncertainty = np.concatenate([correct_uncertainty, incorrect_uncertainty])
correctness = np.concatenate([np.ones(n_correct), np.zeros(n_incorrect)])
# 添加峰高变异系数作为第三维度特征
cv_correct = np.random.normal(0.2, 0.1, n_correct) # 正确样本峰高变异系数较低
cv_incorrect = np.random.normal(0.6, 0.2, n_incorrect) # 错误样本峰高变异系数较高
cv = np.concatenate([cv_correct, cv_incorrect])
# 创建数据框
df = pd.DataFrame({
'uncertainty': uncertainty,
'correctness': correctness,
'result': ['正确' if c == 1 else '错误' for c in correctness],
'cv': cv
})
# 确保不确定性值为非负数
df['uncertainty'] = df['uncertainty'].clip(lower=0)
# 计算整体准确率
overall_accuracy = df['correctness'].mean()
print(f"模拟数据准确率: {overall_accuracy:.4f}")
# 创建自定义颜色映射
def create_green_cmap():
colors = ["#f0f9e8", "#bae4bc", "#7bccc4", "#2b8cbe"]
return LinearSegmentedColormap.from_list("green_cmap", colors)
# 保存所有图像的函数
def save_all_figures():
# 方案1:核密度估计(KDE)+ 统计摘要图
plt.figure(figsize=(12, 8))
kde = gaussian_kde(df['uncertainty'])
x_range = np.linspace(0, df['uncertainty'].max(), 200)
y_kde = kde(x_range)
# 计算统计指标
mean_uncert = df['uncertainty'].mean()
median_uncert = df['uncertainty'].median()
q25, q75 = np.percentile(df['uncertainty'], [25, 75])
std_uncert = df['uncertainty'].std()
plt.plot(x_range, y_kde, 'b-', linewidth=2, label='KDE分布')
plt.fill_between(x_range, y_kde, color='royalblue', alpha=0.2, label='分布区域')
# 标注统计指标
plt.axvline(mean_uncert, color='r', linestyle='--', label=f'均值: {mean_uncert:.2f}')
plt.axvline(median_uncert, color='g', linestyle=':', label=f'中位数: {median_uncert:.2f}')
plt.axvline(q25, color='purple', linestyle='-.', label=f'25%分位数: {q25:.2f}')
plt.axvline(q75, color='orange', linestyle='-.', label=f'75%分位数: {q75:.2f}')
plt.title(f'预测不确定性分布 (准确率: {overall_accuracy * 100:.2f}%)', fontsize=16, pad=20)
plt.xlabel('预测方差', fontsize=14)
plt.ylabel('概率密度', fontsize=14)
plt.legend(loc='upper right', fontsize=12)
plt.grid(alpha=0.2, linestyle='--')
# 添加统计信息框
stats_text = f'统计摘要:\n样本数: {n_samples}\n标准差: {std_uncert:.2f}\n最小值: {df["uncertainty"].min():.2f}\n最大值: {df["uncertainty"].max():.2f}'
plt.text(0.95, 0.95, stats_text,
transform=plt.gca().transAxes,
fontsize=12,
verticalalignment='top',
horizontalalignment='right',
bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))
plt.tight_layout()
plt.savefig('1_kde_distribution.png', dpi=300, bbox_inches='tight')
plt.close()
# 方案2:分组小提琴图 + 抖动散点图
plt.figure(figsize=(12, 8))
sns.set_style("whitegrid")
# 创建自定义调色板
palette = {"正确": "#4caf50", "错误": "#f44336"}
# 绘制小提琴图
sns.violinplot(x='result', y='uncertainty', data=df, palette=palette,
inner='quartile', linewidth=2, saturation=0.8)
# 绘制散点图(带透明度)
sns.stripplot(x='result', y='uncertainty', data=df,
palette=palette, alpha=0.4, size=4, jitter=0.2)
# 添加中位数线
medians = df.groupby('result')['uncertainty'].median()
for i, category in enumerate(medians.index):
plt.hlines(medians[category], i - 0.3, i + 0.3, color='black', linestyles='dashed', linewidth=2)
plt.title(f'预测不确定性与结果分类 (准确率: {overall_accuracy * 100:.2f}%)', fontsize=16, pad=15)
plt.xlabel('预测结果', fontsize=14)
plt.ylabel('预测方差', fontsize=14)
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
# 添加准确率注释
for i, category in enumerate(['正确', '错误']):
count = len(df[df['result'] == category])
percentage = count / len(df) * 100
plt.text(i, df['uncertainty'].max() + 0.1,
f'{count}个样本 ({percentage:.1f}%)',
ha='center', fontsize=12)
plt.ylim(-0.1, df['uncertainty'].max() + 0.3)
plt.tight_layout()
plt.savefig('2_violin_scatter.png', dpi=300, bbox_inches='tight')
plt.close()
# 方案3:热力图(分箱统计正确率)
bins = np.linspace(0, df['uncertainty'].max(), 11)
df['bin'] = pd.cut(df['uncertainty'], bins=bins, include_lowest=True, labels=False)
bin_stats = df.groupby(['bin', 'result']).size().unstack(fill_value=0)
bin_stats['accuracy'] = bin_stats['正确'] / bin_stats.sum(axis=1)
bin_stats['total_samples'] = bin_stats.sum(axis=1)
# 创建热力图数据
heatmap_data = bin_stats['accuracy'].values.reshape(-1, 1)
bin_labels = [f'{bins[i]:.2f}-{bins[i + 1]:.2f}' for i in range(len(bins) - 1)]
# 使用自定义绿色渐变颜色映射
cmap = create_green_cmap()
plt.figure(figsize=(12, 8))
plt.imshow(heatmap_data, cmap=cmap, aspect='auto', vmin=0, vmax=1)
# 添加颜色条
cbar = plt.colorbar()
cbar.set_label('正确率', fontsize=14)
# 添加单元格注释
for i in range(len(bin_labels)):
acc = heatmap_data[i, 0]
samples = bin_stats['total_samples'].iloc[i]
text_color = 'white' if acc < 0.6 else 'black'
plt.text(0, i, f'{acc:.2%}\n({samples}样本)',
ha='center', va='center',
color=text_color, fontsize=11, fontweight='bold')
# 设置坐标轴
plt.yticks(range(len(bin_labels)), bin_labels, fontsize=12)
plt.xticks([])
plt.ylabel('方差区间', fontsize=14)
plt.title(f'不同方差区间的预测正确率 (总体准确率: {overall_accuracy * 100:.2f}%)', fontsize=16, pad=20)
# 添加网格线
plt.grid(False)
for i in range(len(bin_labels) + 1):
plt.axhline(i - 0.5, color='white', linewidth=1)
plt.tight_layout()
plt.savefig('3_heatmap.png', dpi=300, bbox_inches='tight')
plt.close()
# 方案4:动态箱线图 + 错误率趋势线
fig = go.Figure()
# 添加箱线图
fig.add_trace(go.Box(
y=df['uncertainty'],
name='方差分布',
boxpoints='outliers',
marker=dict(color='#2196f3'),
line=dict(color='#0d47a1'),
fillcolor='rgba(33, 150, 243, 0.5)'
))
# 错误率趋势线
df['error'] = 1 - df['correctness']
x_fit = np.linspace(0, df['uncertainty'].max(), 100)
z = np.polyfit(df['uncertainty'], df['error'], 3)
p = np.poly1d(z)
y_fit = p(x_fit)
fig.add_trace(go.Scatter(
x=x_fit,
y=y_fit,
name='错误率趋势',
mode='lines',
line=dict(color='#e53935', width=3),
yaxis='y2'
))
fig.update_layout(
title=dict(
text=f'预测方差分布与错误率趋势 (准确率: {overall_accuracy * 100:.2f}%)',
font=dict(size=20),
),
xaxis=dict(title='预测方差', gridcolor='lightgray'),
yaxis=dict(
title='方差值',
titlefont=dict(color='#2196f3'),
tickfont=dict(color='#2196f3'),
gridcolor='rgba(33, 150, 243, 0.1)'
),
yaxis2=dict(
title='错误率',
titlefont=dict(color='#e53935'),
tickfont=dict(color='#e53935'),
overlaying='y',
side='right',
range=[0, 1]
),
template='plotly_white',
width=1000,
height=700,
margin=dict(l=50, r=50, b=80, t=100),
legend=dict(
orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1
),
hovermode="x unified"
)
# 添加注释
fig.add_annotation(
x=0.95,
y=0.95,
xref="paper",
yref="paper",
text=f"高方差区域错误率显著增加",
showarrow=False,
font=dict(size=14, color="#e53935"),
bgcolor="rgba(255, 255, 255, 0.8)"
)
fig.write_image('4_box_trend.png', scale=3)
# 方案5:三维密度图
fig = go.Figure()
# 添加正确样本
fig.add_trace(go.Scatter3d(
x=df[df['result'] == '正确']['uncertainty'],
y=df[df['result'] == '正确']['cv'],
z=df[df['result'] == '正确']['correctness'],
mode='markers',
name='正确',
marker=dict(
size=5,
color='#4caf50',
opacity=0.7
)
))
# 添加错误样本
fig.add_trace(go.Scatter3d(
x=df[df['result'] == '错误']['uncertainty'],
y=df[df['result'] == '错误']['cv'],
z=df[df['result'] == '错误']['correctness'],
mode='markers',
name='错误',
marker=dict(
size=7,
color='#f44336',
opacity=0.8,
symbol='diamond'
)
))
fig.update_layout(
title=dict(
text=f'三维预测不确定性分析 (准确率: {overall_accuracy * 100:.2f}%)',
font=dict(size=20),
y=0.95
),
scene=dict(
xaxis_title='预测方差',
yaxis_title='峰高变异系数',
zaxis_title='预测正确(1)/错误(0)',
camera=dict(
eye=dict(x=1.5, y=1.5, z=0.8)
)
),
width=1000,
height=800,
margin=dict(l=0, r=0, b=0, t=50),
legend=dict(
yanchor="top",
y=0.99,
xanchor="left",
x=0.01
)
)
# 添加分类平面
fig.add_trace(go.Mesh3d(
x=[0, 2, 2, 0],
y=[0, 0, 1, 1],
z=[0.5, 0.5, 0.5, 0.5],
opacity=0.2,
color='gray',
name='分类平面'
))
fig.write_image('5_3d_density.png', scale=3)
print("所有图像已保存为PNG文件")
# 生成并保存所有图像
save_all_figures()
这个代码显示不出中文字体
C:\python\py\.venv\Scripts\python.exe C:\python\py\3.py
模拟数据准确率: 0.9200
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C:\python\py\3.py:117: FutureWarning:
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Traceback (most recent call last):
File "C:\python\py\3.py", line 339, in <module>
save_all_figures()
~~~~~~~~~~~~~~~~^^
File "C:\python\py\3.py", line 218, in save_all_figures
fig.update_layout(
~~~~~~~~~~~~~~~~~^
title=dict(
^^^^^^^^^^^
...<29 lines>...
hovermode="x unified"
^^^^^^^^^^^^^^^^^^^^^
)
^
File "C:\python\py\.venv\Lib\site-packages\plotly\graph_objs\_figure.py", line 218, in update_layout
return super().update_layout(dict1, overwrite, **kwargs)
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\python\py\.venv\Lib\site-packages\plotly\basedatatypes.py", line 1415, in update_layout
self.layout.update(dict1, overwrite=overwrite, **kwargs)
~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\python\py\.venv\Lib\site-packages\plotly\basedatatypes.py", line 5195, in update
BaseFigure._perform_update(self, kwargs, overwrite=overwrite)
~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\python\py\.venv\Lib\site-packages\plotly\basedatatypes.py", line 3971, in _perform_update
BaseFigure._perform_update(plotly_obj[key], val)
~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
File "C:\python\py\.venv\Lib\site-packages\plotly\basedatatypes.py", line 3949, in _perform_update
raise err
ValueError: Invalid property specified for object of type plotly.graph_objs.layout.YAxis: 'titlefont'
Did you mean "tickfont"?
Valid properties:
anchor
If set to an opposite-letter axis id (e.g. `x2`, `y`),
this axis is bound to the corresponding opposite-letter
axis. If set to "free", this axis' position is
determined by `position`.
automargin
Determines whether long tick labels automatically grow
the figure margins.
autorange
Determines whether or not the range of this axis is
computed in relation to the input data. See `rangemode`
for more info. If `range` is provided and it has a
value for both the lower and upper bound, `autorange`
is set to False. Using "min" applies autorange only to
set the minimum. Using "max" applies autorange only to
set the maximum. Using *min reversed* applies autorange
only to set the minimum on a reversed axis. Using *max
reversed* applies autorange only to set the maximum on
a reversed axis. Using "reversed" applies autorange on
both ends and reverses the axis direction.
autorangeoptions
:class:`plotly.graph_objects.layout.yaxis.Autorangeopti
ons` instance or dict with compatible properties
autoshift
Automatically reposition the axis to avoid overlap with
other axes with the same `overlaying` value. This
repositioning will account for any `shift` amount
applied to other axes on the same side with `autoshift`
is set to true. Only has an effect if `anchor` is set
to "free".
autotickangles
When `tickangle` is set to "auto", it will be set to
the first angle in this array that is large enough to
prevent label overlap.
autotypenumbers
Using "strict" a numeric string in trace data is not
converted to a number. Using *convert types* a numeric
string in trace data may be treated as a number during
automatic axis `type` detection. Defaults to
layout.autotypenumbers.
calendar
Sets the calendar system to use for `range` and `tick0`
if this is a date axis. This does not set the calendar
for interpreting data on this axis, that's specified in
the trace or via the global `layout.calendar`
categoryarray
Sets the order in which categories on this axis appear.
Only has an effect if `categoryorder` is set to
"array". Used with `categoryorder`.
categoryarraysrc
Sets the source reference on Chart Studio Cloud for
`categoryarray`.
categoryorder
Specifies the ordering logic for the case of
categorical variables. By default, plotly uses "trace",
which specifies the order that is present in the data
supplied. Set `categoryorder` to *category ascending*
or *category descending* if order should be determined
by the alphanumerical order of the category names. Set
`categoryorder` to "array" to derive the ordering from
the attribute `categoryarray`. If a category is not
found in the `categoryarray` array, the sorting
behavior for that attribute will be identical to the
"trace" mode. The unspecified categories will follow
the categories in `categoryarray`. Set `categoryorder`
to *total ascending* or *total descending* if order
should be determined by the numerical order of the
values. Similarly, the order can be determined by the
min, max, sum, mean, geometric mean or median of all
the values.
color
Sets default for all colors associated with this axis
all at once: line, font, tick, and grid colors. Grid
color is lightened by blending this with the plot
background Individual pieces can override this.
constrain
If this axis needs to be compressed (either due to its
own `scaleanchor` and `scaleratio` or those of the
other axis), determines how that happens: by increasing
the "range", or by decreasing the "domain". Default is
"domain" for axes containing image traces, "range"
otherwise.
constraintoward
If this axis needs to be compressed (either due to its
own `scaleanchor` and `scaleratio` or those of the
other axis), determines which direction we push the
originally specified plot area. Options are "left",
"center" (default), and "right" for x axes, and "top",
"middle" (default), and "bottom" for y axes.
dividercolor
Sets the color of the dividers Only has an effect on
"multicategory" axes.
dividerwidth
Sets the width (in px) of the dividers Only has an
effect on "multicategory" axes.
domain
Sets the domain of this axis (in plot fraction).
dtick
Sets the step in-between ticks on this axis. Use with
`tick0`. Must be a positive number, or special strings
available to "log" and "date" axes. If the axis `type`
is "log", then ticks are set every 10^(n*dtick) where n
is the tick number. For example, to set a tick mark at
1, 10, 100, 1000, ... set dtick to 1. To set tick marks
at 1, 100, 10000, ... set dtick to 2. To set tick marks
at 1, 5, 25, 125, 625, 3125, ... set dtick to
log_10(5), or 0.69897000433. "log" has several special
values; "L<f>", where `f` is a positive number, gives
ticks linearly spaced in value (but not position). For
example `tick0` = 0.1, `dtick` = "L0.5" will put ticks
at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus
small digits between, use "D1" (all digits) or "D2"
(only 2 and 5). `tick0` is ignored for "D1" and "D2".
If the axis `type` is "date", then you must convert the
time to milliseconds. For example, to set the interval
between ticks to one day, set `dtick` to 86400000.0.
"date" also has special values "M<n>" gives ticks
spaced by a number of months. `n` must be a positive
integer. To set ticks on the 15th of every third month,
set `tick0` to "2000-01-15" and `dtick` to "M3". To set
ticks every 4 years, set `dtick` to "M48"
exponentformat
Determines a formatting rule for the tick exponents.
For example, consider the number 1,000,000,000. If
"none", it appears as 1,000,000,000. If "e", 1e+9. If
"E", 1E+9. If "power", 1x10^9 (with 9 in a super
script). If "SI", 1G. If "B", 1B.
fixedrange
Determines whether or not this axis is zoom-able. If
true, then zoom is disabled.
gridcolor
Sets the color of the grid lines.
griddash
Sets the dash style of lines. Set to a dash type string
("solid", "dot", "dash", "longdash", "dashdot", or
"longdashdot") or a dash length list in px (eg
"5px,10px,2px,2px").
gridwidth
Sets the width (in px) of the grid lines.
hoverformat
Sets the hover text formatting rule using d3 formatting
mini-languages which are very similar to those in
Python. For numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format.
And for dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to
d3's date formatter: "%h" for half of the year as a
decimal number as well as "%{n}f" for fractional
seconds with n digits. For example, *2016-10-13
09:15:23.456* with tickformat "%H~%M~%S.%2f" would
display "09~15~23.46"
insiderange
Could be used to set the desired inside range of this
axis (excluding the labels) when `ticklabelposition` of
the anchored axis has "inside". Not implemented for
axes with `type` "log". This would be ignored when
`range` is provided.
labelalias
Replacement text for specific tick or hover labels. For
example using {US: 'USA', CA: 'Canada'} changes US to
USA and CA to Canada. The labels we would have shown
must match the keys exactly, after adding any
tickprefix or ticksuffix. For negative numbers the
minus sign symbol used (U+2212) is wider than the
regular ascii dash. That means you need to use −1
instead of -1. labelalias can be used with any axis
type, and both keys (if needed) and values (if desired)
can include html-like tags or MathJax.
layer
Sets the layer on which this axis is displayed. If
*above traces*, this axis is displayed above all the
subplot's traces If *below traces*, this axis is
displayed below all the subplot's traces, but above the
grid lines. Useful when used together with scatter-like
traces with `cliponaxis` set to False to show markers
and/or text nodes above this axis.
linecolor
Sets the axis line color.
linewidth
Sets the width (in px) of the axis line.
matches
If set to another axis id (e.g. `x2`, `y`), the range
of this axis will match the range of the corresponding
axis in data-coordinates space. Moreover, matching axes
share auto-range values, category lists and histogram
auto-bins. Note that setting axes simultaneously in
both a `scaleanchor` and a `matches` constraint is
currently forbidden. Moreover, note that matching axes
must have the same `type`.
maxallowed
Determines the maximum range of this axis.
minallowed
Determines the minimum range of this axis.
minexponent
Hide SI prefix for 10^n if |n| is below this number.
This only has an effect when `tickformat` is "SI" or
"B".
minor
:class:`plotly.graph_objects.layout.yaxis.Minor`
instance or dict with compatible properties
mirror
Determines if the axis lines or/and ticks are mirrored
to the opposite side of the plotting area. If True, the
axis lines are mirrored. If "ticks", the axis lines and
ticks are mirrored. If False, mirroring is disable. If
"all", axis lines are mirrored on all shared-axes
subplots. If "allticks", axis lines and ticks are
mirrored on all shared-axes subplots.
nticks
Specifies the maximum number of ticks for the
particular axis. The actual number of ticks will be
chosen automatically to be less than or equal to
`nticks`. Has an effect only if `tickmode` is set to
"auto".
overlaying
If set a same-letter axis id, this axis is overlaid on
top of the corresponding same-letter axis, with traces
and axes visible for both axes. If False, this axis
does not overlay any same-letter axes. In this case,
for axes with overlapping domains only the highest-
numbered axis will be visible.
position
Sets the position of this axis in the plotting space
(in normalized coordinates). Only has an effect if
`anchor` is set to "free".
range
Sets the range of this axis. If the axis `type` is
"log", then you must take the log of your desired range
(e.g. to set the range from 1 to 100, set the range
from 0 to 2). If the axis `type` is "date", it should
be date strings, like date data, though Date objects
and unix milliseconds will be accepted and converted to
strings. If the axis `type` is "category", it should be
numbers, using the scale where each category is
assigned a serial number from zero in the order it
appears. Leaving either or both elements `null` impacts
the default `autorange`.
rangebreaks
A tuple of
:class:`plotly.graph_objects.layout.yaxis.Rangebreak`
instances or dicts with compatible properties
rangebreakdefaults
When used in a template (as
layout.template.layout.yaxis.rangebreakdefaults), sets
the default property values to use for elements of
layout.yaxis.rangebreaks
rangemode
If "normal", the range is computed in relation to the
extrema of the input data. If "tozero", the range
extends to 0, regardless of the input data If
"nonnegative", the range is non-negative, regardless of
the input data. Applies only to linear axes.
scaleanchor
If set to another axis id (e.g. `x2`, `y`), the range
of this axis changes together with the range of the
corresponding axis such that the scale of pixels per
unit is in a constant ratio. Both axes are still
zoomable, but when you zoom one, the other will zoom
the same amount, keeping a fixed midpoint. `constrain`
and `constraintoward` determine how we enforce the
constraint. You can chain these, ie `yaxis:
{scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you
can only link axes of the same `type`. The linked axis
can have the opposite letter (to constrain the aspect
ratio) or the same letter (to match scales across
subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis:
{scaleanchor: *y*}` or longer) are redundant and the
last constraint encountered will be ignored to avoid
possible inconsistent constraints via `scaleratio`.
Note that setting axes simultaneously in both a
`scaleanchor` and a `matches` constraint is currently
forbidden. Setting `false` allows to remove a default
constraint (occasionally, you may need to prevent a
default `scaleanchor` constraint from being applied,
eg. when having an image trace `yaxis: {scaleanchor:
"x"}` is set automatically in order for pixels to be
rendered as squares, setting `yaxis: {scaleanchor:
false}` allows to remove the constraint).
scaleratio
If this axis is linked to another by `scaleanchor`,
this determines the pixel to unit scale ratio. For
example, if this value is 10, then every unit on this
axis spans 10 times the number of pixels as a unit on
the linked axis. Use this for example to create an
elevation profile where the vertical scale is
exaggerated a fixed amount with respect to the
horizontal.
separatethousands
If "true", even 4-digit integers are separated
shift
Moves the axis a given number of pixels from where it
would have been otherwise. Accepts both positive and
negative values, which will shift the axis either right
or left, respectively. If `autoshift` is set to true,
then this defaults to a padding of -3 if `side` is set
to "left". and defaults to +3 if `side` is set to
"right". Defaults to 0 if `autoshift` is set to false.
Only has an effect if `anchor` is set to "free".
showdividers
Determines whether or not a dividers are drawn between
the category levels of this axis. Only has an effect on
"multicategory" axes.
showexponent
If "all", all exponents are shown besides their
significands. If "first", only the exponent of the
first tick is shown. If "last", only the exponent of
the last tick is shown. If "none", no exponents appear.
showgrid
Determines whether or not grid lines are drawn. If
True, the grid lines are drawn at every tick mark.
showline
Determines whether or not a line bounding this axis is
drawn.
showspikes
Determines whether or not spikes (aka droplines) are
drawn for this axis. Note: This only takes affect when
hovermode = closest
showticklabels
Determines whether or not the tick labels are drawn.
showtickprefix
If "all", all tick labels are displayed with a prefix.
If "first", only the first tick is displayed with a
prefix. If "last", only the last tick is displayed with
a suffix. If "none", tick prefixes are hidden.
showticksuffix
Same as `showtickprefix` but for tick suffixes.
side
Determines whether a x (y) axis is positioned at the
"bottom" ("left") or "top" ("right") of the plotting
area.
spikecolor
Sets the spike color. If undefined, will use the series
color
spikedash
Sets the dash style of lines. Set to a dash type string
("solid", "dot", "dash", "longdash", "dashdot", or
"longdashdot") or a dash length list in px (eg
"5px,10px,2px,2px").
spikemode
Determines the drawing mode for the spike line If
"toaxis", the line is drawn from the data point to the
axis the series is plotted on. If "across", the line
is drawn across the entire plot area, and supercedes
"toaxis". If "marker", then a marker dot is drawn on
the axis the series is plotted on
spikesnap
Determines whether spikelines are stuck to the cursor
or to the closest datapoints.
spikethickness
Sets the width (in px) of the zero line.
tick0
Sets the placement of the first tick on this axis. Use
with `dtick`. If the axis `type` is "log", then you
must take the log of your starting tick (e.g. to set
the starting tick to 100, set the `tick0` to 2) except
when `dtick`=*L<f>* (see `dtick` for more info). If the
axis `type` is "date", it should be a date string, like
date data. If the axis `type` is "category", it should
be a number, using the scale where each category is
assigned a serial number from zero in the order it
appears.
tickangle
Sets the angle of the tick labels with respect to the
horizontal. For example, a `tickangle` of -90 draws the
tick labels vertically.
tickcolor
Sets the tick color.
tickfont
Sets the tick font.
tickformat
Sets the tick label formatting rule using d3 formatting
mini-languages which are very similar to those in
Python. For numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format.
And for dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to
d3's date formatter: "%h" for half of the year as a
decimal number as well as "%{n}f" for fractional
seconds with n digits. For example, *2016-10-13
09:15:23.456* with tickformat "%H~%M~%S.%2f" would
display "09~15~23.46"
tickformatstops
A tuple of :class:`plotly.graph_objects.layout.yaxis.Ti
ckformatstop` instances or dicts with compatible
properties
tickformatstopdefaults
When used in a template (as
layout.template.layout.yaxis.tickformatstopdefaults),
sets the default property values to use for elements of
layout.yaxis.tickformatstops
ticklabelindex
Only for axes with `type` "date" or "linear". Instead
of drawing the major tick label, draw the label for the
minor tick that is n positions away from the major
tick. E.g. to always draw the label for the minor tick
before each major tick, choose `ticklabelindex` -1.
This is useful for date axes with `ticklabelmode`
"period" if you want to label the period that ends with
each major tick instead of the period that begins
there.
ticklabelindexsrc
Sets the source reference on Chart Studio Cloud for
`ticklabelindex`.
ticklabelmode
Determines where tick labels are drawn with respect to
their corresponding ticks and grid lines. Only has an
effect for axes of `type` "date" When set to "period",
tick labels are drawn in the middle of the period
between ticks.
ticklabeloverflow
Determines how we handle tick labels that would
overflow either the graph div or the domain of the
axis. The default value for inside tick labels is *hide
past domain*. Otherwise on "category" and
"multicategory" axes the default is "allow". In other
cases the default is *hide past div*.
ticklabelposition
Determines where tick labels are drawn with respect to
the axis Please note that top or bottom has no effect
on x axes or when `ticklabelmode` is set to "period".
Similarly left or right has no effect on y axes or when
`ticklabelmode` is set to "period". Has no effect on
"multicategory" axes or when `tickson` is set to
"boundaries". When used on axes linked by `matches` or
`scaleanchor`, no extra padding for inside labels would
be added by autorange, so that the scales could match.
ticklabelshift
Shifts the tick labels by the specified number of
pixels in parallel to the axis. Positive values move
the labels in the positive direction of the axis.
ticklabelstandoff
Sets the standoff distance (in px) between the axis
tick labels and their default position. A positive
`ticklabelstandoff` moves the labels farther away from
the plot area if `ticklabelposition` is "outside", and
deeper into the plot area if `ticklabelposition` is
"inside". A negative `ticklabelstandoff` works in the
opposite direction, moving outside ticks towards the
plot area and inside ticks towards the outside. If the
negative value is large enough, inside ticks can even
end up outside and vice versa.
ticklabelstep
Sets the spacing between tick labels as compared to the
spacing between ticks. A value of 1 (default) means
each tick gets a label. A value of 2 means shows every
2nd label. A larger value n means only every nth tick
is labeled. `tick0` determines which labels are shown.
Not implemented for axes with `type` "log" or
"multicategory", or when `tickmode` is "array".
ticklen
Sets the tick length (in px).
tickmode
Sets the tick mode for this axis. If "auto", the number
of ticks is set via `nticks`. If "linear", the
placement of the ticks is determined by a starting
position `tick0` and a tick step `dtick` ("linear" is
the default value if `tick0` and `dtick` are provided).
If "array", the placement of the ticks is set via
`tickvals` and the tick text is `ticktext`. ("array" is
the default value if `tickvals` is provided). If
"sync", the number of ticks will sync with the
overlayed axis set by `overlaying` property.
tickprefix
Sets a tick label prefix.
ticks
Determines whether ticks are drawn or not. If "", this
axis' ticks are not drawn. If "outside" ("inside"),
this axis' are drawn outside (inside) the axis lines.
tickson
Determines where ticks and grid lines are drawn with
respect to their corresponding tick labels. Only has an
effect for axes of `type` "category" or
"multicategory". When set to "boundaries", ticks and
grid lines are drawn half a category to the left/bottom
of labels.
ticksuffix
Sets a tick label suffix.
ticktext
Sets the text displayed at the ticks position via
`tickvals`. Only has an effect if `tickmode` is set to
"array". Used with `tickvals`.
ticktextsrc
Sets the source reference on Chart Studio Cloud for
`ticktext`.
tickvals
Sets the values at which ticks on this axis appear.
Only has an effect if `tickmode` is set to "array".
Used with `ticktext`.
tickvalssrc
Sets the source reference on Chart Studio Cloud for
`tickvals`.
tickwidth
Sets the tick width (in px).
title
:class:`plotly.graph_objects.layout.yaxis.Title`
instance or dict with compatible properties
type
Sets the axis type. By default, plotly attempts to
determined the axis type by looking into the data of
the traces that referenced the axis in question.
uirevision
Controls persistence of user-driven changes in axis
`range`, `autorange`, and `title` if in `editable:
true` configuration. Defaults to `layout.uirevision`.
visible
A single toggle to hide the axis while preserving
interaction like dragging. Default is true when a
cheater plot is present on the axis, otherwise false
zeroline
Determines whether or not a line is drawn at along the
0 value of this axis. If True, the zero line is drawn
on top of the grid lines.
zerolinecolor
Sets the line color of the zero line.
zerolinewidth
Sets the width (in px) of the zero line.
Did you mean "tickfont"?
Bad property path:
titlefont
^^^^^^^^^
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