# -----------------------------------------------------------------------------
# Matplotlib cheat sheet
# Released under the BSD License
# -----------------------------------------------------------------------------

# Scripts to generate all the basic plots 
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

fig = plt.figure(figsize=(0.4,0.4))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])


# Step plot
# -----------------------------------------------------------------------------
X = np.linspace(0, 10, 16)
Y = 4+2*np.sin(2*X)
ax.step(X, Y, color="C1", linewidth=0.75)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-step.pdf")
ax.clear()

# Violin plot
# -----------------------------------------------------------------------------
np.random.seed(10)
D = np.random.normal((3,5,4), (0.75, 1.00, 0.75), (200,3))
VP = ax.violinplot(D, [2,4,6], widths=1.5,
                   showmeans=False, showmedians=False, showextrema=False)
for body in VP['bodies']:
    body.set_facecolor('C1')
    body.set_alpha(1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-violin.pdf")
ax.clear()


# Boxplot
# -----------------------------------------------------------------------------
np.random.seed(10)
D = np.random.normal((3,5,4), (1.25, 1.00, 1.25), (100,3))
VP = ax.boxplot(D, positions=[2,4,6], widths=1.5, patch_artist=True,
                showmeans=False, showfliers=False,
                medianprops = {"color": "white",
                               "linewidth": 0.25},
                boxprops = {"facecolor": "C1",
                            "edgecolor": "white",
                            "linewidth": 0.25},
                whiskerprops = {"color": "C1",
                                "linewidth": 0.75},
                capprops = {"color": "C1",
                            "linewidth": 0.75})
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-boxplot.pdf")
ax.clear()

# Barbs plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [[2,4,6]]
Y = [[1.5,3,2]]
U = -np.ones((1,3))*0
V = -np.ones((1,3))*np.linspace(50,100,3)
ax.barbs(X,Y,U,V, barbcolor="C1", flagcolor="C1", length=5, linewidth=0.5)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-barbs.pdf")
ax.clear()

# Event plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [2,4,6]
D = np.random.gamma(4, size=(3, 50))
ax.eventplot(D, colors="C1", orientation="vertical", lineoffsets=X, linewidth=0.25)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-event.pdf")
ax.clear()

# Errorbar plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [2,4,6]
Y = [4,5,4]
E = np.random.uniform(0.5, 1.5, 3)
ax.errorbar(X, Y, E, color="C1", linewidth=0.75, capsize=1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-errorbar.pdf")
ax.clear()


# Hexbin plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = np.random.uniform(1.5,6.5,100)
Y = np.random.uniform(1.5,6.5,100)
C = np.random.uniform(0,1,10000)
ax.hexbin(X, Y, C, gridsize=4, linewidth=0.25, edgecolor="white",
          cmap=plt.get_cmap("Wistia"), alpha=1.0)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-hexbin.pdf")
ax.clear()

# Hist plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = 4 + np.random.normal(0,1.5,200)
ax.hist(X, bins=8, facecolor="C1", linewidth=0.25, edgecolor="white",)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 80), ax.set_yticks(np.arange(1,80,10))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-hist.pdf")
ax.clear()

# Xcorr plot
# -----------------------------------------------------------------------------
np.random.seed(3)
Y = np.random.uniform(-4, 4, 250)
X = np.random.uniform(-4, 4, 250)
ax.xcorr(X, Y, usevlines=True, maxlags=6, normed=True, lw=1,
         color="C1")
ax.set_xlim(-8, 8), ax.set_xticks(np.arange(-8,8,2))
ax.set_ylim(-.25, .25), ax.set_yticks(np.linspace(-.25,.25,9))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-xcorr.pdf")
ax.clear()


# -----------------------------------------------------------------------------
# Matplotlib cheat sheet
# Released under the BSD License
# -----------------------------------------------------------------------------

# Scripts to generate all the basic plots 
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

fig = plt.figure(figsize=(0.4,0.4))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])


# Step plot
# -----------------------------------------------------------------------------
X = np.linspace(0, 10, 16)
Y = 4+2*np.sin(2*X)
ax.step(X, Y, color="C1", linewidth=0.75)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-step.pdf")
ax.clear()

# Violin plot
# -----------------------------------------------------------------------------
np.random.seed(10)
D = np.random.normal((3,5,4), (0.75, 1.00, 0.75), (200,3))
VP = ax.violinplot(D, [2,4,6], widths=1.5,
                   showmeans=False, showmedians=False, showextrema=False)
for body in VP['bodies']:
    body.set_facecolor('C1')
    body.set_alpha(1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-violin.pdf")
ax.clear()


# Boxplot
# -----------------------------------------------------------------------------
np.random.seed(10)
D = np.random.normal((3,5,4), (1.25, 1.00, 1.25), (100,3))
VP = ax.boxplot(D, positions=[2,4,6], widths=1.5, patch_artist=True,
                showmeans=False, showfliers=False,
                medianprops = {"color": "white",
                               "linewidth": 0.25},
                boxprops = {"facecolor": "C1",
                            "edgecolor": "white",
                            "linewidth": 0.25},
                whiskerprops = {"color": "C1",
                                "linewidth": 0.75},
                capprops = {"color": "C1",
                            "linewidth": 0.75})
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-boxplot.pdf")
ax.clear()

# Barbs plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [[2,4,6]]
Y = [[1.5,3,2]]
U = -np.ones((1,3))*0
V = -np.ones((1,3))*np.linspace(50,100,3)
ax.barbs(X,Y,U,V, barbcolor="C1", flagcolor="C1", length=5, linewidth=0.5)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-barbs.pdf")
ax.clear()

# Event plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [2,4,6]
D = np.random.gamma(4, size=(3, 50))
ax.eventplot(D, colors="C1", orientation="vertical", lineoffsets=X, linewidth=0.25)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-event.pdf")
ax.clear()

# Errorbar plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = [2,4,6]
Y = [4,5,4]
E = np.random.uniform(0.5, 1.5, 3)
ax.errorbar(X, Y, E, color="C1", linewidth=0.75, capsize=1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-errorbar.pdf")
ax.clear()


# Hexbin plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = np.random.uniform(1.5,6.5,100)
Y = np.random.uniform(1.5,6.5,100)
C = np.random.uniform(0,1,10000)
ax.hexbin(X, Y, C, gridsize=4, linewidth=0.25, edgecolor="white",
          cmap=plt.get_cmap("Wistia"), alpha=1.0)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-hexbin.pdf")
ax.clear()

# Hist plot
# -----------------------------------------------------------------------------
np.random.seed(1)
X = 4 + np.random.normal(0,1.5,200)
ax.hist(X, bins=8, facecolor="C1", linewidth=0.25, edgecolor="white",)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 80), ax.set_yticks(np.arange(1,80,10))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-hist.pdf")
ax.clear()

# Xcorr plot
# -----------------------------------------------------------------------------
np.random.seed(3)
Y = np.random.uniform(-4, 4, 250)
X = np.random.uniform(-4, 4, 250)
ax.xcorr(X, Y, usevlines=True, maxlags=6, normed=True, lw=1,
         color="C1")
ax.set_xlim(-8, 8), ax.set_xticks(np.arange(-8,8,2))
ax.set_ylim(-.25, .25), ax.set_yticks(np.linspace(-.25,.25,9))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.savefig("../figures/advanced-xcorr.pdf")
ax.clear()


# ----------------------------------------------------------------------------- # Matplotlib cheat sheet # Released under the BSD License # ----------------------------------------------------------------------------- # Scripts to generate all the basic plots # Step plot # ----------------------------------------------------------------------------- # Violin plot # ----------------------------------------------------------------------------- # Boxplot # ----------------------------------------------------------------------------- # Barbs plot # ----------------------------------------------------------------------------- # Event plot # ----------------------------------------------------------------------------- # Errorbar plot # ----------------------------------------------------------------------------- # Hexbin plot # ----------------------------------------------------------------------------- # Hist plot # ----------------------------------------------------------------------------- # Xcorr plot # -----------------------------------------------------------------------------