def init_plotting():
sns.set_style('whitegrid')
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (12, 8)
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'OfficinaSanITCBoo'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
python类set_style()的实例源码
def init_plotting(w,h):
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (w,h)
plt.rcParams['font.size'] = 8
plt.rcParams['font.family'] = 'Source Sans Pro'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
def init_plotting(w,h):
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (w,h)
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'OfficinaSanITCBoo'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
# init_plotting(7,4)
def init_plotting(w,h):
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (w,h)
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'OfficinaSanITCBoo'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
def init_plotting(w,h):
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (w,h)
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'OfficinaSanITCBoo'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
def init_plotting(w,h):
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (w,h)
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'OfficinaSanITCBoo'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
def init_plotting(w,h):
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (w,h)
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'OfficinaSanITCBoo'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
# init_plotting(7,4)
def init_plotting(w,h):
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = (w,h)
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'OfficinaSanITCBoo'
# plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelsize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.1*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
def plot_frequencies(flu, gene, mutation=None, plot_regions=None, all_muts=False, ax=None, **kwargs):
import seaborn as sns
sns.set_style('whitegrid')
cols = sns.color_palette()
linestyles = ['-', '--', '-.', ':']
if plot_regions is None:
plot_regions=regions
pivots = flu.pivots
if ax is None:
plt.figure()
ax=plt.subplot(111)
if type(mutation)==int:
mutations = [x for x,freq in flu.mutation_frequencies[('global', gene)].iteritems()
if (x[0]==mutation)&(freq[0]<0.5 or all_muts)]
elif mutation is not None:
mutations = [mutation]
else:
mutations=None
if mutations is None:
for ri, region in enumerate(plot_regions):
count=flu.mutation_frequency_counts[region]
plt.plot(pivots, count, c=cols[ri%len(cols)], label=region)
else:
print("plotting mutations", mutations)
for ri,region in enumerate(plot_regions):
for mi,mut in enumerate(mutations):
if mut in flu.mutation_frequencies[(region, gene)]:
freq = flu.mutation_frequencies[(region, gene)][mut]
err = flu.mutation_frequency_confidence[(region, gene)][mut]
c=cols[ri%len(cols)]
label_str = str(mut[0]+1)+mut[1]+', '+region
plot_trace(ax, pivots, freq, err, c=c,
ls=linestyles[mi%len(linestyles)],label=label_str, **kwargs)
else:
print(mut, 'not found in region',region)
ax.ticklabel_format(useOffset=False)
ax.legend(loc=2)
def plot_sequence_count(flu, fname=None, fs=12):
# make figure with region counts
import seaborn as sns
date_bins = pivots_to_dates(flu.pivots)
sns.set_style('ticks')
region_label = {'global': 'Global', 'NA': 'N America', 'AS': 'Asia', 'EU': 'Europe', 'OC': 'Oceania'}
regions_abbr = ['global', 'NA', 'AS', 'EU', 'OC']
region_colors = {r:col for r, col in zip(regions_abbr,
sns.color_palette(n_colors=len(regions_abbr)))}
fig, ax = plt.subplots(figsize=(8, 3))
count_by_region = flu.mutation_frequency_counts
drop = 3
tmpcounts = np.zeros(len(flu.pivots[drop:]))
plt.bar(date_bins[drop:], count_by_region['global'][drop:], width=18, \
linewidth=0, label="Other", color="#bbbbbb", clip_on=False)
for region in region_groups:
if region!='global':
plt.bar(date_bins[drop:], count_by_region[region][drop:],
bottom=tmpcounts, width=18, linewidth=0,
label=region_label[region], color=region_colors[region], clip_on=False)
tmpcounts += count_by_region[region][drop:]
make_date_ticks(ax, fs=fs)
ax.set_ylabel('Sample count')
ax.legend(loc=3, ncol=1, bbox_to_anchor=(1.02, 0.53))
plt.subplots_adjust(left=0.1, right=0.82, top=0.94, bottom=0.22)
sns.despine()
if fname is not None:
plt.savefig(fname)
figure.healthy_vs_disease_classifier.py 文件源码
项目:microbiomeHD
作者: cduvallet
项目源码
文件源码
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def plot_aucs(aucs, x_col, y_col, groupby_col, colors):
"""
Scatter plot aucs[x_col] vs aucs[y_col], colored by colors[groupby_col]
Parameters
----------
aucs : pandas DataFrame
has x_col, y_col, and groupby_col
x_col, y_col, groupby_col : str
colors : dict
values in groupby_col: color to plot
"""
sns.set_style('white')
fig, ax = plt.subplots(figsize=(4,3))
ax.plot([0, 1], [0, 1], '--', c='0.95')
ax.plot([0.5, 0.5], [0, 1], '--', c='0.95')
ax.plot([0, 1], [0.5, 0.5], '--', c='0.95')
for g, subdf in aucs.groupby(groupby_col):
if g == 'cdi':
label = 'diarrhea'
else:
label = g.upper()
ax.scatter(subdf[x_col], subdf[y_col], c=colors[g], label=label)
ax.set_xlim([0, 1])
ax.set_ylim([0, 1])
fig.tight_layout()
# Shrink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
# Put a legend to the right of the current axis
lgd = ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
return fig, ax, lgd
def save_bar_graph(x, y, file_name):
plt.clf()
sns.set_style("whitegrid")
ax = sns.barplot(x=x, y=y)
for item in ax.get_xticklabels():
item.set_rotation(15)
plt.savefig(file_name)
def save_graph_with_icon(x, y, images, file_name):
plt.clf()
sns.set_style("whitegrid")
ax = sns.barplot(x=x, y=y, ci=None)
# erase ticks
ax.get_xaxis().set_ticklabels([], fontsize=45) # expand label size by fontsize parameter
TICK_POS = -0.25
SIZE_IN_TICK = 1
scale = ax.transData.transform((1, 1)) - ax.transData.transform((0, 0))
x_scale = scale[0] / scale[1]
for i, _x in enumerate(x):
label_x = _x # adjustment is not needed in saved file
left = label_x - (SIZE_IN_TICK / x_scale / 2)
down = TICK_POS - SIZE_IN_TICK
right = label_x + (SIZE_IN_TICK / x_scale / 2)
top = TICK_POS
leftDown = ax.transData.transform((left, down))
rightUpper = ax.transData.transform((right, top))
bbox_image = BboxImage(Bbox([leftDown, rightUpper]),
norm=None,
origin=None,
clip_on=False
)
bbox_image.set_data(images[i])
ax.add_artist(bbox_image)
plt.savefig(file_name)
def kde(x,y,title='',color='YlGnBu',xscale='linear',yscale='linear'):
sns.set_style('white')
sns.set_context('notebook', font_scale=1, rc={"lines.linewidth": 0.5})
g = sns.kdeplot(x,y,shade=True, cut=2, cmap=color, shade_lowest=False, legend=True, set_title="test")
plt.tick_params(axis='both', which='major', pad=10)
sns.plt.title(title)
g.set(xscale=xscale)
g.set(yscale=yscale)
sns.despine()
def regression(data,x,y,xscale='linear',yscale='linear'):
sns.set_context("notebook", font_scale=.8, rc={"lines.linewidth": 0})
sns.set_style('white')
g = sns.regplot(x=x, y=y, data=data)
plt.tick_params(axis='both', which='major', pad=10)
g.set(xscale=xscale)
g.set(yscale=yscale)
sns.despine()
def update_graph(dff):
sns.set_style("white")
sns.set_style("ticks")
sns.set_context("talk")
dff.ix[::10].plot("date", "overdue", figsize=(7, 4), lw=3)
onemonth = datetime.timedelta(30)
plt.xlim(dff.date.min(), dff.date.max()+onemonth)
plt.ylabel("Overdue dataset")
plt.xlabel("Date")
plt.savefig("docs/graph.png")
def setupPlot(context="talk", style="white", font_scale=1.0):
sns.set_context(context, font_scale=font_scale)
sns.set_style(style)
def show_image(self):
"""
Method to plot the image and attributes.
Input: None
Output: None
"""
print self.__str__()
sns.set_style("whitegrid", {'axes.grid': False})
plt.imshow(self.image)
plt.show()
def set_style(style="darkgrid"):
sns.set_style(style)
def make_probes_ba_traj_fig(models1, models2=None, palette=None): # TODO ylim
"""
Returns fig showing trajectory of probes balanced accuracy
"""
start = time.time()
sns.set_style('white')
# load data
xys = []
model_groups = [models1] if models2 is None else [models1, models2]
for n, models in enumerate(model_groups):
model_probes_ba_trajs = []
for nn, model in enumerate(models):
model_probes_ba_trajs.append(model.get_traj('probes_ba'))
x = models[0].get_data_step_axis()
traj_mat = np.asarray([traj[:len(x)] for traj in model_probes_ba_trajs]) # all trajs are truncated to shortest
y = np.mean(traj_mat, axis=0)
sem = [stats.sem(model_probes_bas) for model_probes_bas in traj_mat.T]
xys.append((x, y, sem))
# fig
fig, ax = plt.subplots(figsize=(FigsConfigs.MAX_FIG_WIDTH, 3))
ax.set_ylim([50, 75])
ax.set_xlabel('Mini Batch', fontsize=FigsConfigs.AXLABEL_FONT_SIZE)
ax.set_ylabel('Probes Balanced Accuracy', fontsize=FigsConfigs.AXLABEL_FONT_SIZE)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.tick_params(axis='both', which='both', top='off', right='off')
ax.xaxis.set_major_formatter(FuncFormatter(human_format))
ax.yaxis.grid(True)
# plot
for (x, y, sem) in xys:
color = next(palette) if palette is not None else 'black'
ax.plot(x, y, '-', linewidth=FigsConfigs.LINEWIDTH, color=color)
ax.fill_between(x, np.add(y, sem), np.subtract(y, sem), alpha=FigsConfigs.FILL_ALPHA, color='grey')
plt.tight_layout()
print('{} completed in {:.1f} secs'.format(sys._getframe().f_code.co_name, time.time() - start))
return fig