866 lines
32 KiB
Python
866 lines
32 KiB
Python
|
import datetime
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
import matplotlib.pyplot as plt
|
||
|
|
import matplotlib as mpl
|
||
|
|
|
||
|
|
|
||
|
|
class TestDatetimePlotting:
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_annotate(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, layout="constrained")
|
||
|
|
|
||
|
|
start_date = datetime.datetime(2023, 10, 1)
|
||
|
|
dates = [start_date + datetime.timedelta(days=i) for i in range(31)]
|
||
|
|
data = list(range(1, 32))
|
||
|
|
test_text = "Test Text"
|
||
|
|
|
||
|
|
ax1.plot(dates, data)
|
||
|
|
ax1.annotate(text=test_text, xy=(dates[15], data[15]))
|
||
|
|
ax2.plot(data, dates)
|
||
|
|
ax2.annotate(text=test_text, xy=(data[5], dates[26]))
|
||
|
|
ax3.plot(dates, dates)
|
||
|
|
ax3.annotate(text=test_text, xy=(dates[15], dates[3]))
|
||
|
|
ax4.plot(dates, dates)
|
||
|
|
ax4.annotate(text=test_text, xy=(dates[5], dates[30]),
|
||
|
|
xytext=(dates[1], dates[7]), arrowprops=dict(facecolor='red'))
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for arrow not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_arrow(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.arrow(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_axhline(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout='constrained')
|
||
|
|
ax1.set_ylim(bottom=datetime.datetime(2020, 4, 1),
|
||
|
|
top=datetime.datetime(2020, 8, 1))
|
||
|
|
ax2.set_ylim(bottom=np.datetime64('2005-01-01'),
|
||
|
|
top=np.datetime64('2005-04-01'))
|
||
|
|
ax3.set_ylim(bottom=datetime.datetime(2023, 9, 1),
|
||
|
|
top=datetime.datetime(2023, 11, 1))
|
||
|
|
ax1.axhline(y=datetime.datetime(2020, 6, 3), xmin=0.5, xmax=0.7)
|
||
|
|
ax2.axhline(np.datetime64('2005-02-25T03:30'), xmin=0.1, xmax=0.9)
|
||
|
|
ax3.axhline(y=datetime.datetime(2023, 10, 24), xmin=0.4, xmax=0.7)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_axhspan(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
|
||
|
|
start_date = datetime.datetime(2023, 1, 1)
|
||
|
|
dates = [start_date + datetime.timedelta(days=i) for i in range(31)]
|
||
|
|
numbers = list(range(1, 32))
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1,
|
||
|
|
constrained_layout=True,
|
||
|
|
figsize=(10, 12))
|
||
|
|
|
||
|
|
ax1.plot(dates, numbers, marker='o', color='blue')
|
||
|
|
for i in range(0, 31, 2):
|
||
|
|
ax1.axhspan(ymin=i+1, ymax=i+2, facecolor='green', alpha=0.5)
|
||
|
|
ax1.set_title('Datetime vs. Number')
|
||
|
|
ax1.set_xlabel('Date')
|
||
|
|
ax1.set_ylabel('Number')
|
||
|
|
|
||
|
|
ax2.plot(numbers, dates, marker='o', color='blue')
|
||
|
|
for i in range(0, 31, 2):
|
||
|
|
ymin = start_date + datetime.timedelta(days=i)
|
||
|
|
ymax = ymin + datetime.timedelta(days=1)
|
||
|
|
ax2.axhspan(ymin=ymin, ymax=ymax, facecolor='green', alpha=0.5)
|
||
|
|
ax2.set_title('Number vs. Datetime')
|
||
|
|
ax2.set_xlabel('Number')
|
||
|
|
ax2.set_ylabel('Date')
|
||
|
|
|
||
|
|
ax3.plot(dates, dates, marker='o', color='blue')
|
||
|
|
for i in range(0, 31, 2):
|
||
|
|
ymin = start_date + datetime.timedelta(days=i)
|
||
|
|
ymax = ymin + datetime.timedelta(days=1)
|
||
|
|
ax3.axhspan(ymin=ymin, ymax=ymax, facecolor='green', alpha=0.5)
|
||
|
|
ax3.set_title('Datetime vs. Datetime')
|
||
|
|
ax3.set_xlabel('Date')
|
||
|
|
ax3.set_ylabel('Date')
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for axline not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_axline(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.axline(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_axvline(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout='constrained')
|
||
|
|
ax1.set_xlim(left=datetime.datetime(2020, 4, 1),
|
||
|
|
right=datetime.datetime(2020, 8, 1))
|
||
|
|
ax2.set_xlim(left=np.datetime64('2005-01-01'),
|
||
|
|
right=np.datetime64('2005-04-01'))
|
||
|
|
ax3.set_xlim(left=datetime.datetime(2023, 9, 1),
|
||
|
|
right=datetime.datetime(2023, 11, 1))
|
||
|
|
ax1.axvline(x=datetime.datetime(2020, 6, 3), ymin=0.5, ymax=0.7)
|
||
|
|
ax2.axvline(np.datetime64('2005-02-25T03:30'), ymin=0.1, ymax=0.9)
|
||
|
|
ax3.axvline(x=datetime.datetime(2023, 10, 24), ymin=0.4, ymax=0.7)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_axvspan(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
|
||
|
|
start_date = datetime.datetime(2023, 1, 1)
|
||
|
|
dates = [start_date + datetime.timedelta(days=i) for i in range(31)]
|
||
|
|
numbers = list(range(1, 32))
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1,
|
||
|
|
constrained_layout=True,
|
||
|
|
figsize=(10, 12))
|
||
|
|
|
||
|
|
ax1.plot(dates, numbers, marker='o', color='blue')
|
||
|
|
for i in range(0, 31, 2):
|
||
|
|
xmin = start_date + datetime.timedelta(days=i)
|
||
|
|
xmax = xmin + datetime.timedelta(days=1)
|
||
|
|
ax1.axvspan(xmin=xmin, xmax=xmax, facecolor='red', alpha=0.5)
|
||
|
|
ax1.set_title('Datetime vs. Number')
|
||
|
|
ax1.set_xlabel('Date')
|
||
|
|
ax1.set_ylabel('Number')
|
||
|
|
|
||
|
|
ax2.plot(numbers, dates, marker='o', color='blue')
|
||
|
|
for i in range(0, 31, 2):
|
||
|
|
ax2.axvspan(xmin=i+1, xmax=i+2, facecolor='red', alpha=0.5)
|
||
|
|
ax2.set_title('Number vs. Datetime')
|
||
|
|
ax2.set_xlabel('Number')
|
||
|
|
ax2.set_ylabel('Date')
|
||
|
|
|
||
|
|
ax3.plot(dates, dates, marker='o', color='blue')
|
||
|
|
for i in range(0, 31, 2):
|
||
|
|
xmin = start_date + datetime.timedelta(days=i)
|
||
|
|
xmax = xmin + datetime.timedelta(days=1)
|
||
|
|
ax3.axvspan(xmin=xmin, xmax=xmax, facecolor='red', alpha=0.5)
|
||
|
|
ax3.set_title('Datetime vs. Datetime')
|
||
|
|
ax3.set_xlabel('Date')
|
||
|
|
ax3.set_ylabel('Date')
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_bar(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
|
||
|
|
fig, (ax1, ax2) = plt.subplots(2, 1, layout="constrained")
|
||
|
|
|
||
|
|
x_dates = np.array(
|
||
|
|
[
|
||
|
|
datetime.datetime(2020, 6, 30),
|
||
|
|
datetime.datetime(2020, 7, 22),
|
||
|
|
datetime.datetime(2020, 8, 3),
|
||
|
|
datetime.datetime(2020, 9, 14),
|
||
|
|
],
|
||
|
|
dtype=np.datetime64,
|
||
|
|
)
|
||
|
|
x_ranges = [8800, 2600, 8500, 7400]
|
||
|
|
|
||
|
|
x = np.datetime64(datetime.datetime(2020, 6, 1))
|
||
|
|
ax1.bar(x_dates, x_ranges, width=np.timedelta64(4, "D"))
|
||
|
|
ax2.bar(np.arange(4), x_dates - x, bottom=x)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_bar_label(self):
|
||
|
|
# Generate some example data with dateTime inputs
|
||
|
|
date_list = [datetime.datetime(2023, 1, 1) +
|
||
|
|
datetime.timedelta(days=i) for i in range(5)]
|
||
|
|
values = [10, 20, 15, 25, 30]
|
||
|
|
|
||
|
|
# Creating the plot
|
||
|
|
fig, ax = plt.subplots(1, 1, figsize=(10, 8), layout='constrained')
|
||
|
|
bars = ax.bar(date_list, values)
|
||
|
|
|
||
|
|
# Add labels to the bars using bar_label
|
||
|
|
ax.bar_label(bars, labels=[f'{val}%' for val in values],
|
||
|
|
label_type='edge', color='black')
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_barbs(self):
|
||
|
|
plt.rcParams["date.converter"] = 'concise'
|
||
|
|
|
||
|
|
start_date = datetime.datetime(2022, 2, 8, 22)
|
||
|
|
dates = [start_date + datetime.timedelta(hours=i) for i in range(12)]
|
||
|
|
|
||
|
|
numbers = np.sin(np.linspace(0, 2 * np.pi, 12))
|
||
|
|
|
||
|
|
u = np.ones(12) * 10
|
||
|
|
v = np.arange(0, 120, 10)
|
||
|
|
|
||
|
|
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(12, 6))
|
||
|
|
|
||
|
|
axes[0].barbs(dates, numbers, u, v, length=7)
|
||
|
|
axes[0].set_title('Datetime vs. Numeric Data')
|
||
|
|
axes[0].set_xlabel('Datetime')
|
||
|
|
axes[0].set_ylabel('Numeric Data')
|
||
|
|
|
||
|
|
axes[1].barbs(numbers, dates, u, v, length=7)
|
||
|
|
axes[1].set_title('Numeric vs. Datetime Data')
|
||
|
|
axes[1].set_xlabel('Numeric Data')
|
||
|
|
axes[1].set_ylabel('Datetime')
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_barh(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, (ax1, ax2) = plt.subplots(2, 1, layout='constrained')
|
||
|
|
birth_date = np.array([datetime.datetime(2020, 4, 10),
|
||
|
|
datetime.datetime(2020, 5, 30),
|
||
|
|
datetime.datetime(2020, 10, 12),
|
||
|
|
datetime.datetime(2020, 11, 15)])
|
||
|
|
year_start = datetime.datetime(2020, 1, 1)
|
||
|
|
year_end = datetime.datetime(2020, 12, 31)
|
||
|
|
age = [21, 53, 20, 24]
|
||
|
|
ax1.set_xlabel('Age')
|
||
|
|
ax1.set_ylabel('Birth Date')
|
||
|
|
ax1.barh(birth_date, width=age, height=datetime.timedelta(days=10))
|
||
|
|
ax2.set_xlim(left=year_start, right=year_end)
|
||
|
|
ax2.set_xlabel('Birth Date')
|
||
|
|
ax2.set_ylabel('Order of Birth Dates')
|
||
|
|
ax2.barh(np.arange(4), birth_date-year_start, left=year_start)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for boxplot not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_boxplot(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.boxplot(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_broken_barh(self):
|
||
|
|
# Horizontal bar plot with gaps
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
|
||
|
|
ax.broken_barh([(datetime.datetime(2023, 1, 4), datetime.timedelta(days=2)),
|
||
|
|
(datetime.datetime(2023, 1, 8), datetime.timedelta(days=3))],
|
||
|
|
(10, 9), facecolors='tab:blue')
|
||
|
|
ax.broken_barh([(datetime.datetime(2023, 1, 2), datetime.timedelta(days=1)),
|
||
|
|
(datetime.datetime(2023, 1, 4), datetime.timedelta(days=4))],
|
||
|
|
(20, 9), facecolors=('tab:red'))
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_bxp(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
data = [{
|
||
|
|
"med": datetime.datetime(2020, 1, 15),
|
||
|
|
"q1": datetime.datetime(2020, 1, 10),
|
||
|
|
"q3": datetime.datetime(2020, 1, 20),
|
||
|
|
"whislo": datetime.datetime(2020, 1, 5),
|
||
|
|
"whishi": datetime.datetime(2020, 1, 25),
|
||
|
|
"fliers": [
|
||
|
|
datetime.datetime(2020, 1, 3),
|
||
|
|
datetime.datetime(2020, 1, 27)
|
||
|
|
]
|
||
|
|
}]
|
||
|
|
ax.bxp(data, vert=False)
|
||
|
|
ax.xaxis.set_major_formatter(mpl.dates.DateFormatter("%Y-%m-%d"))
|
||
|
|
ax.set_title('Box plot with datetime data')
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for clabel not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_clabel(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.clabel(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_contour(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
range_threshold = 10
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout="constrained")
|
||
|
|
|
||
|
|
x_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, delta) for delta in range(1, range_threshold)]
|
||
|
|
)
|
||
|
|
y_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, delta) for delta in range(1, range_threshold)]
|
||
|
|
)
|
||
|
|
x_ranges = np.array(range(1, range_threshold))
|
||
|
|
y_ranges = np.array(range(1, range_threshold))
|
||
|
|
|
||
|
|
X_dates, Y_dates = np.meshgrid(x_dates, y_dates)
|
||
|
|
X_ranges, Y_ranges = np.meshgrid(x_ranges, y_ranges)
|
||
|
|
|
||
|
|
Z_ranges = np.cos(X_ranges / 4) + np.sin(Y_ranges / 4)
|
||
|
|
|
||
|
|
ax1.contour(X_dates, Y_dates, Z_ranges)
|
||
|
|
ax2.contour(X_dates, Y_ranges, Z_ranges)
|
||
|
|
ax3.contour(X_ranges, Y_dates, Z_ranges)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_contourf(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
range_threshold = 10
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout="constrained")
|
||
|
|
|
||
|
|
x_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, delta) for delta in range(1, range_threshold)]
|
||
|
|
)
|
||
|
|
y_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, delta) for delta in range(1, range_threshold)]
|
||
|
|
)
|
||
|
|
x_ranges = np.array(range(1, range_threshold))
|
||
|
|
y_ranges = np.array(range(1, range_threshold))
|
||
|
|
|
||
|
|
X_dates, Y_dates = np.meshgrid(x_dates, y_dates)
|
||
|
|
X_ranges, Y_ranges = np.meshgrid(x_ranges, y_ranges)
|
||
|
|
|
||
|
|
Z_ranges = np.cos(X_ranges / 4) + np.sin(Y_ranges / 4)
|
||
|
|
|
||
|
|
ax1.contourf(X_dates, Y_dates, Z_ranges)
|
||
|
|
ax2.contourf(X_dates, Y_ranges, Z_ranges)
|
||
|
|
ax3.contourf(X_ranges, Y_dates, Z_ranges)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_errorbar(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, layout="constrained")
|
||
|
|
limit = 7
|
||
|
|
start_date = datetime.datetime(2023, 1, 1)
|
||
|
|
|
||
|
|
x_dates = np.array([datetime.datetime(2023, 10, d) for d in range(1, limit)])
|
||
|
|
y_dates = np.array([datetime.datetime(2023, 10, d) for d in range(1, limit)])
|
||
|
|
x_date_error = datetime.timedelta(days=1)
|
||
|
|
y_date_error = datetime.timedelta(days=1)
|
||
|
|
|
||
|
|
x_values = list(range(1, limit))
|
||
|
|
y_values = list(range(1, limit))
|
||
|
|
x_value_error = 0.5
|
||
|
|
y_value_error = 0.5
|
||
|
|
|
||
|
|
ax1.errorbar(x_dates, y_values,
|
||
|
|
yerr=y_value_error,
|
||
|
|
capsize=10,
|
||
|
|
barsabove=True,
|
||
|
|
label='Data')
|
||
|
|
ax2.errorbar(x_values, y_dates,
|
||
|
|
xerr=x_value_error, yerr=y_date_error,
|
||
|
|
errorevery=(1, 2),
|
||
|
|
fmt='-o', label='Data')
|
||
|
|
ax3.errorbar(x_dates, y_dates,
|
||
|
|
xerr=x_date_error, yerr=y_date_error,
|
||
|
|
lolims=True, xlolims=True,
|
||
|
|
label='Data')
|
||
|
|
ax4.errorbar(x_dates, y_values,
|
||
|
|
xerr=x_date_error, yerr=y_value_error,
|
||
|
|
uplims=True, xuplims=True,
|
||
|
|
label='Data')
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_eventplot(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout="constrained")
|
||
|
|
|
||
|
|
x_dates1 = np.array([datetime.datetime(2020, 6, 30),
|
||
|
|
datetime.datetime(2020, 7, 22),
|
||
|
|
datetime.datetime(2020, 8, 3),
|
||
|
|
datetime.datetime(2020, 9, 14),],
|
||
|
|
dtype=np.datetime64,
|
||
|
|
)
|
||
|
|
|
||
|
|
ax1.eventplot(x_dates1)
|
||
|
|
|
||
|
|
np.random.seed(19680801)
|
||
|
|
|
||
|
|
start_date = datetime.datetime(2020, 7, 1)
|
||
|
|
end_date = datetime.datetime(2020, 10, 15)
|
||
|
|
date_range = end_date - start_date
|
||
|
|
|
||
|
|
dates1 = start_date + np.random.rand(30) * date_range
|
||
|
|
dates2 = start_date + np.random.rand(10) * date_range
|
||
|
|
dates3 = start_date + np.random.rand(50) * date_range
|
||
|
|
|
||
|
|
colors1 = ['C1', 'C2', 'C3']
|
||
|
|
lineoffsets1 = np.array([1, 6, 8])
|
||
|
|
linelengths1 = [5, 2, 3]
|
||
|
|
|
||
|
|
ax2.eventplot([dates1, dates2, dates3],
|
||
|
|
colors=colors1,
|
||
|
|
lineoffsets=lineoffsets1,
|
||
|
|
linelengths=linelengths1)
|
||
|
|
|
||
|
|
lineoffsets2 = np.array([
|
||
|
|
datetime.datetime(2020, 7, 1),
|
||
|
|
datetime.datetime(2020, 7, 15),
|
||
|
|
datetime.datetime(2020, 8, 1)
|
||
|
|
], dtype=np.datetime64)
|
||
|
|
|
||
|
|
ax3.eventplot([dates1, dates2, dates3],
|
||
|
|
colors=colors1,
|
||
|
|
lineoffsets=lineoffsets2,
|
||
|
|
linelengths=linelengths1)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_fill(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, layout="constrained")
|
||
|
|
|
||
|
|
np.random.seed(19680801)
|
||
|
|
|
||
|
|
x_base_date = datetime.datetime(2023, 1, 1)
|
||
|
|
x_dates = [x_base_date]
|
||
|
|
for _ in range(1, 5):
|
||
|
|
x_base_date += datetime.timedelta(days=np.random.randint(1, 5))
|
||
|
|
x_dates.append(x_base_date)
|
||
|
|
|
||
|
|
y_base_date = datetime.datetime(2023, 1, 1)
|
||
|
|
y_dates = [y_base_date]
|
||
|
|
for _ in range(1, 5):
|
||
|
|
y_base_date += datetime.timedelta(days=np.random.randint(1, 5))
|
||
|
|
y_dates.append(y_base_date)
|
||
|
|
|
||
|
|
x_values = np.random.rand(5) * 5
|
||
|
|
y_values = np.random.rand(5) * 5 - 2
|
||
|
|
|
||
|
|
ax1.fill(x_dates, y_values)
|
||
|
|
ax2.fill(x_values, y_dates)
|
||
|
|
ax3.fill(x_values, y_values)
|
||
|
|
ax4.fill(x_dates, y_dates)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_fill_between(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
np.random.seed(19680801)
|
||
|
|
|
||
|
|
y_base_date = datetime.datetime(2023, 1, 1)
|
||
|
|
y_dates1 = [y_base_date]
|
||
|
|
for i in range(1, 10):
|
||
|
|
y_base_date += datetime.timedelta(days=np.random.randint(1, 5))
|
||
|
|
y_dates1.append(y_base_date)
|
||
|
|
|
||
|
|
y_dates2 = [y_base_date]
|
||
|
|
for i in range(1, 10):
|
||
|
|
y_base_date += datetime.timedelta(days=np.random.randint(1, 5))
|
||
|
|
y_dates2.append(y_base_date)
|
||
|
|
x_values = np.random.rand(10) * 10
|
||
|
|
x_values.sort()
|
||
|
|
|
||
|
|
y_values1 = np.random.rand(10) * 10
|
||
|
|
y_values2 = y_values1 + np.random.rand(10) * 10
|
||
|
|
y_values1.sort()
|
||
|
|
y_values2.sort()
|
||
|
|
|
||
|
|
x_base_date = datetime.datetime(2023, 1, 1)
|
||
|
|
x_dates = [x_base_date]
|
||
|
|
for i in range(1, 10):
|
||
|
|
x_base_date += datetime.timedelta(days=np.random.randint(1, 10))
|
||
|
|
x_dates.append(x_base_date)
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout="constrained")
|
||
|
|
|
||
|
|
ax1.fill_between(x_values, y_dates1, y_dates2)
|
||
|
|
ax2.fill_between(x_dates, y_values1, y_values2)
|
||
|
|
ax3.fill_between(x_dates, y_dates1, y_dates2)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_fill_betweenx(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
np.random.seed(19680801)
|
||
|
|
|
||
|
|
x_base_date = datetime.datetime(2023, 1, 1)
|
||
|
|
x_dates1 = [x_base_date]
|
||
|
|
for i in range(1, 10):
|
||
|
|
x_base_date += datetime.timedelta(days=np.random.randint(1, 5))
|
||
|
|
x_dates1.append(x_base_date)
|
||
|
|
|
||
|
|
x_dates2 = [x_base_date]
|
||
|
|
for i in range(1, 10):
|
||
|
|
x_base_date += datetime.timedelta(days=np.random.randint(1, 5))
|
||
|
|
x_dates2.append(x_base_date)
|
||
|
|
y_values = np.random.rand(10) * 10
|
||
|
|
y_values.sort()
|
||
|
|
|
||
|
|
x_values1 = np.random.rand(10) * 10
|
||
|
|
x_values2 = x_values1 + np.random.rand(10) * 10
|
||
|
|
x_values1.sort()
|
||
|
|
x_values2.sort()
|
||
|
|
|
||
|
|
y_base_date = datetime.datetime(2023, 1, 1)
|
||
|
|
y_dates = [y_base_date]
|
||
|
|
for i in range(1, 10):
|
||
|
|
y_base_date += datetime.timedelta(days=np.random.randint(1, 10))
|
||
|
|
y_dates.append(y_base_date)
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(1, 3, layout="constrained")
|
||
|
|
|
||
|
|
ax1.fill_betweenx(y_values, x_dates1, x_dates2)
|
||
|
|
ax2.fill_betweenx(y_dates, x_values1, x_values2)
|
||
|
|
ax3.fill_betweenx(y_dates, x_dates1, x_dates2)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for hexbin not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_hexbin(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.hexbin(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_hist(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
|
||
|
|
start_date = datetime.datetime(2023, 10, 1)
|
||
|
|
time_delta = datetime.timedelta(days=1)
|
||
|
|
|
||
|
|
values1 = np.random.randint(1, 10, 30)
|
||
|
|
values2 = np.random.randint(1, 10, 30)
|
||
|
|
values3 = np.random.randint(1, 10, 30)
|
||
|
|
|
||
|
|
bin_edges = [start_date + i * time_delta for i in range(31)]
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, constrained_layout=True)
|
||
|
|
ax1.hist(
|
||
|
|
[start_date + i * time_delta for i in range(30)],
|
||
|
|
bins=10,
|
||
|
|
weights=values1
|
||
|
|
)
|
||
|
|
ax2.hist(
|
||
|
|
[start_date + i * time_delta for i in range(30)],
|
||
|
|
bins=10,
|
||
|
|
weights=values2
|
||
|
|
)
|
||
|
|
ax3.hist(
|
||
|
|
[start_date + i * time_delta for i in range(30)],
|
||
|
|
bins=10,
|
||
|
|
weights=values3
|
||
|
|
)
|
||
|
|
|
||
|
|
fig, (ax4, ax5, ax6) = plt.subplots(3, 1, constrained_layout=True)
|
||
|
|
ax4.hist(
|
||
|
|
[start_date + i * time_delta for i in range(30)],
|
||
|
|
bins=bin_edges,
|
||
|
|
weights=values1
|
||
|
|
)
|
||
|
|
ax5.hist(
|
||
|
|
[start_date + i * time_delta for i in range(30)],
|
||
|
|
bins=bin_edges,
|
||
|
|
weights=values2
|
||
|
|
)
|
||
|
|
ax6.hist(
|
||
|
|
[start_date + i * time_delta for i in range(30)],
|
||
|
|
bins=bin_edges,
|
||
|
|
weights=values3
|
||
|
|
)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for hist2d not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_hist2d(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.hist2d(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_hlines(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, axs = plt.subplots(2, 4, layout='constrained')
|
||
|
|
dateStrs = ['2023-03-08',
|
||
|
|
'2023-04-09',
|
||
|
|
'2023-05-13',
|
||
|
|
'2023-07-28',
|
||
|
|
'2023-12-24']
|
||
|
|
dates = [datetime.datetime(2023, m*2, 10) for m in range(1, 6)]
|
||
|
|
date_start = [datetime.datetime(2023, 6, d) for d in range(5, 30, 5)]
|
||
|
|
date_end = [datetime.datetime(2023, 7, d) for d in range(5, 30, 5)]
|
||
|
|
npDates = [np.datetime64(s) for s in dateStrs]
|
||
|
|
axs[0, 0].hlines(y=dates,
|
||
|
|
xmin=[0.1, 0.2, 0.3, 0.4, 0.5],
|
||
|
|
xmax=[0.5, 0.6, 0.7, 0.8, 0.9])
|
||
|
|
axs[0, 1].hlines(dates,
|
||
|
|
xmin=datetime.datetime(2020, 5, 10),
|
||
|
|
xmax=datetime.datetime(2020, 5, 31))
|
||
|
|
axs[0, 2].hlines(dates,
|
||
|
|
xmin=date_start,
|
||
|
|
xmax=date_end)
|
||
|
|
axs[0, 3].hlines(dates,
|
||
|
|
xmin=0.45,
|
||
|
|
xmax=0.65)
|
||
|
|
axs[1, 0].hlines(y=npDates,
|
||
|
|
xmin=[0.5, 0.6, 0.7, 0.8, 0.9],
|
||
|
|
xmax=[0.1, 0.2, 0.3, 0.4, 0.5])
|
||
|
|
axs[1, 2].hlines(y=npDates,
|
||
|
|
xmin=date_start,
|
||
|
|
xmax=date_end)
|
||
|
|
axs[1, 1].hlines(npDates,
|
||
|
|
xmin=datetime.datetime(2020, 5, 10),
|
||
|
|
xmax=datetime.datetime(2020, 5, 31))
|
||
|
|
axs[1, 3].hlines(npDates,
|
||
|
|
xmin=0.45,
|
||
|
|
xmax=0.65)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_imshow(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
a = np.diag(range(5))
|
||
|
|
dt_start = datetime.datetime(2010, 11, 1)
|
||
|
|
dt_end = datetime.datetime(2010, 11, 11)
|
||
|
|
extent = (dt_start, dt_end, dt_start, dt_end)
|
||
|
|
ax.imshow(a, extent=extent)
|
||
|
|
ax.tick_params(axis="x", labelrotation=90)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for loglog not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_loglog(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.loglog(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_matshow(self):
|
||
|
|
a = np.diag(range(5))
|
||
|
|
dt_start = datetime.datetime(1980, 4, 15)
|
||
|
|
dt_end = datetime.datetime(2020, 11, 11)
|
||
|
|
extent = (dt_start, dt_end, dt_start, dt_end)
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.matshow(a, extent=extent)
|
||
|
|
for label in ax.get_xticklabels():
|
||
|
|
label.set_rotation(90)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for pcolor not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_pcolor(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.pcolor(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for pcolorfast not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_pcolorfast(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.pcolorfast(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for pcolormesh not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_pcolormesh(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.pcolormesh(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_plot(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
N = 6
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout='constrained')
|
||
|
|
x = np.array([datetime.datetime(2023, 9, n) for n in range(1, N)])
|
||
|
|
ax1.plot(x, range(1, N))
|
||
|
|
ax2.plot(range(1, N), x)
|
||
|
|
ax3.plot(x, x)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_plot_date(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
range_threshold = 10
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout="constrained")
|
||
|
|
|
||
|
|
x_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, delta) for delta in range(1, range_threshold)]
|
||
|
|
)
|
||
|
|
y_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, delta) for delta in range(1, range_threshold)]
|
||
|
|
)
|
||
|
|
x_ranges = np.array(range(1, range_threshold))
|
||
|
|
y_ranges = np.array(range(1, range_threshold))
|
||
|
|
|
||
|
|
with pytest.warns(mpl.MatplotlibDeprecationWarning):
|
||
|
|
ax1.plot_date(x_dates, y_dates)
|
||
|
|
ax2.plot_date(x_dates, y_ranges)
|
||
|
|
ax3.plot_date(x_ranges, y_dates)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for quiver not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_quiver(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.quiver(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_scatter(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
base = datetime.datetime(2005, 2, 1)
|
||
|
|
dates = [base + datetime.timedelta(hours=(2 * i)) for i in range(10)]
|
||
|
|
N = len(dates)
|
||
|
|
np.random.seed(19680801)
|
||
|
|
y = np.cumsum(np.random.randn(N))
|
||
|
|
fig, axs = plt.subplots(3, 1, layout='constrained', figsize=(6, 6))
|
||
|
|
# datetime array on x axis
|
||
|
|
axs[0].scatter(dates, y)
|
||
|
|
for label in axs[0].get_xticklabels():
|
||
|
|
label.set_rotation(40)
|
||
|
|
label.set_horizontalalignment('right')
|
||
|
|
# datetime on y axis
|
||
|
|
axs[1].scatter(y, dates)
|
||
|
|
# datetime on both x, y axes
|
||
|
|
axs[2].scatter(dates, dates)
|
||
|
|
for label in axs[2].get_xticklabels():
|
||
|
|
label.set_rotation(40)
|
||
|
|
label.set_horizontalalignment('right')
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for semilogx not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_semilogx(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.semilogx(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for semilogy not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_semilogy(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.semilogy(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_stackplot(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
N = 10
|
||
|
|
stacked_nums = np.tile(np.arange(1, N), (4, 1))
|
||
|
|
dates = np.array([datetime.datetime(2020 + i, 1, 1) for i in range(N - 1)])
|
||
|
|
|
||
|
|
fig, ax = plt.subplots(layout='constrained')
|
||
|
|
ax.stackplot(dates, stacked_nums)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_stairs(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
|
||
|
|
start_date = datetime.datetime(2023, 12, 1)
|
||
|
|
time_delta = datetime.timedelta(days=1)
|
||
|
|
baseline_date = datetime.datetime(1980, 1, 1)
|
||
|
|
|
||
|
|
bin_edges = [start_date + i * time_delta for i in range(31)]
|
||
|
|
edge_int = np.arange(31)
|
||
|
|
np.random.seed(123456)
|
||
|
|
values1 = np.random.randint(1, 100, 30)
|
||
|
|
values2 = [start_date + datetime.timedelta(days=int(i))
|
||
|
|
for i in np.random.randint(1, 10000, 30)]
|
||
|
|
values3 = [start_date + datetime.timedelta(days=int(i))
|
||
|
|
for i in np.random.randint(-10000, 10000, 30)]
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, constrained_layout=True)
|
||
|
|
ax1.stairs(values1, edges=bin_edges)
|
||
|
|
ax2.stairs(values2, edges=edge_int, baseline=baseline_date)
|
||
|
|
ax3.stairs(values3, edges=bin_edges, baseline=baseline_date)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_stem(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
|
||
|
|
fig, (ax1, ax2, ax3, ax4, ax5, ax6) = plt.subplots(6, 1, layout="constrained")
|
||
|
|
|
||
|
|
limit_value = 10
|
||
|
|
above = datetime.datetime(2023, 9, 18)
|
||
|
|
below = datetime.datetime(2023, 11, 18)
|
||
|
|
|
||
|
|
x_ranges = np.arange(1, limit_value)
|
||
|
|
y_ranges = np.arange(1, limit_value)
|
||
|
|
|
||
|
|
x_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, n) for n in range(1, limit_value)]
|
||
|
|
)
|
||
|
|
y_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, n) for n in range(1, limit_value)]
|
||
|
|
)
|
||
|
|
|
||
|
|
ax1.stem(x_dates, y_dates, bottom=above)
|
||
|
|
ax2.stem(x_dates, y_ranges, bottom=5)
|
||
|
|
ax3.stem(x_ranges, y_dates, bottom=below)
|
||
|
|
|
||
|
|
ax4.stem(x_ranges, y_dates, orientation="horizontal", bottom=above)
|
||
|
|
ax5.stem(x_dates, y_ranges, orientation="horizontal", bottom=5)
|
||
|
|
ax6.stem(x_ranges, y_dates, orientation="horizontal", bottom=below)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_step(self):
|
||
|
|
mpl.rcParams["date.converter"] = "concise"
|
||
|
|
N = 6
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout='constrained')
|
||
|
|
x = np.array([datetime.datetime(2023, 9, n) for n in range(1, N)])
|
||
|
|
ax1.step(x, range(1, N))
|
||
|
|
ax2.step(range(1, N), x)
|
||
|
|
ax3.step(x, x)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for streamplot not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_streamplot(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.streamplot(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_text(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout="constrained")
|
||
|
|
|
||
|
|
limit_value = 10
|
||
|
|
font_properties = {'family': 'serif', 'size': 12, 'weight': 'bold'}
|
||
|
|
test_date = datetime.datetime(2023, 10, 1)
|
||
|
|
|
||
|
|
x_data = np.array(range(1, limit_value))
|
||
|
|
y_data = np.array(range(1, limit_value))
|
||
|
|
|
||
|
|
x_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, n) for n in range(1, limit_value)]
|
||
|
|
)
|
||
|
|
y_dates = np.array(
|
||
|
|
[datetime.datetime(2023, 10, n) for n in range(1, limit_value)]
|
||
|
|
)
|
||
|
|
|
||
|
|
ax1.plot(x_dates, y_data)
|
||
|
|
ax1.text(test_date, 5, "Inserted Text", **font_properties)
|
||
|
|
|
||
|
|
ax2.plot(x_data, y_dates)
|
||
|
|
ax2.text(7, test_date, "Inserted Text", **font_properties)
|
||
|
|
|
||
|
|
ax3.plot(x_dates, y_dates)
|
||
|
|
ax3.text(test_date, test_date, "Inserted Text", **font_properties)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for tricontour not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_tricontour(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.tricontour(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for tricontourf not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_tricontourf(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.tricontourf(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for tripcolor not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_tripcolor(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.tripcolor(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for triplot not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_triplot(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.triplot(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for violin not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_violin(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.violin(...)
|
||
|
|
|
||
|
|
@pytest.mark.xfail(reason="Test for violinplot not written yet")
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_violinplot(self):
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
ax.violinplot(...)
|
||
|
|
|
||
|
|
@mpl.style.context("default")
|
||
|
|
def test_vlines(self):
|
||
|
|
mpl.rcParams["date.converter"] = 'concise'
|
||
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, layout='constrained')
|
||
|
|
ax1.set_xlim(left=datetime.datetime(2023, 1, 1),
|
||
|
|
right=datetime.datetime(2023, 6, 30))
|
||
|
|
ax1.vlines(x=[datetime.datetime(2023, 2, 10),
|
||
|
|
datetime.datetime(2023, 5, 18),
|
||
|
|
datetime.datetime(2023, 6, 6)],
|
||
|
|
ymin=[0, 0.25, 0.5],
|
||
|
|
ymax=[0.25, 0.5, 0.75])
|
||
|
|
ax2.set_xlim(left=0,
|
||
|
|
right=0.5)
|
||
|
|
ax2.vlines(x=[0.3, 0.35],
|
||
|
|
ymin=[np.datetime64('2023-03-20'), np.datetime64('2023-03-31')],
|
||
|
|
ymax=[np.datetime64('2023-05-01'), np.datetime64('2023-05-16')])
|
||
|
|
ax3.set_xlim(left=datetime.datetime(2023, 7, 1),
|
||
|
|
right=datetime.datetime(2023, 12, 31))
|
||
|
|
ax3.vlines(x=[datetime.datetime(2023, 9, 1), datetime.datetime(2023, 12, 10)],
|
||
|
|
ymin=datetime.datetime(2023, 1, 15),
|
||
|
|
ymax=datetime.datetime(2023, 1, 30))
|