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, orientation='horizontal')

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))