def plot_gridpolicy(self, ax, mat):
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
w = self.w
d = 0.03
width = height = 1.0 / w
p2g = lambda p: (p[1]*width + width/2, 1 - p[0]*height - height/2)
for i in range(w):
for j in range(w):
s = (i, j)
if s in [(0, 0), (w-1, w-1)]:
tb.add_cell(i, j, width, height, text='', facecolor='gray')
continue
else:
tb.add_cell(i, j, width, height, text='')
m = mat[s].max()
dire = mat[s] == m
x, y = p2g(s)
if all(dire == [1, 1, 1, 1]):
ax.arrow(x, y, 0, d, head_width=d, fc='k')
ax.arrow(x, y, 0, -d, head_width=d, fc='k')
ax.arrow(x, y, d, 0, head_width=d, fc='k')
ax.arrow(x, y, -d, 0, head_width=d, fc='k')
elif all(dire == [1, 0, 0, 0]):
# up
ax.arrow(x, y - width / 2 + d, 0, width / 2, head_width=d, fc='k')
elif all(dire == [0, 1, 0, 0]):
# down
ax.arrow(x, y + width / 2 - d, 0, - width / 2, head_width=d, fc='k')
elif all(dire == [0, 0, 1, 0]):
# <-
ax.arrow(x + width / 2 - d, y, - width / 2, 0, head_width=d, fc='k')
elif all(dire == [0, 0, 0, 1]):
# ->
ax.arrow(x - width / 2 + d, y, width / 2, 0, head_width=d, fc='k')
elif all(dire == [1, 0, 0, 1]):
# ^
# |->
ax.arrow(x - width / 2 + 2*d, y - width / 2 + 2*d, 0, width / 2 - d, head_width=d, fc='k')
ax.arrow(x - width / 2 + 2*d, y - width / 2 + 2*d, width / 2 - d, 0, head_width=d, fc='k')
elif all(dire == [1, 0, 1, 0]):
# ^
# <-|
ax.arrow(x + width / 2 - 2*d, y - width / 2 + 2*d, 0, width / 2 - d, head_width=d, fc='k')
ax.arrow(x + width / 2 - 2*d, y - width / 2 + 2*d, - width / 2 + d, 0, head_width=d, fc='k')
elif all(dire == [0, 1, 1, 0]):
# <-|
# v
ax.arrow(x + width / 2 - 2*d, y + width / 2 - 2*d, - width / 2 + d, 0, head_width=d, fc='k')
ax.arrow(x + width / 2 - 2*d, y + width / 2 - 2*d, 0, - width / 2 + d, head_width=d, fc='k')
elif all(dire == [0, 1, 0, 1]):
# |->
# v
ax.arrow(x - width / 2 + 2*d, y + width / 2 - 2*d, width / 2 - d, 0, head_width=d, fc='k')
ax.arrow(x - width / 2 + 2*d, y + width / 2 - 2*d, 0, - width / 2 + d, head_width=d, fc='k')
ax.add_table(tb)
def plot_change_maze(out, data, agents, maze, change_step, xlim, ylim, xticks,
yticks):
plt.figure(figsize=(6, 6))
ax = plt.subplot()
for i in range(data.shape[0]):
ax.plot(range(data.shape[1]), data[i], 'k-', lw=1)
x = data.shape[1] // 5 * 4
ha, va = [('right', 'bottom'), ('left', 'top')][i]
ax.text(x,
data[i][x],
agents[i].method,
horizontalalignment=ha,
verticalalignment=va)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_bounds(xlim[0], xlim[1])
ax.spines['left'].set_bounds(ylim[0], ylim[1])
ax.set_xlim((xlim[0], xlim[2]))
ax.set_ylim((ylim[0], ylim[2]))
ax.set_xticks(xticks)
ax.set_yticks(yticks[0])
ax.set_yticklabels(yticks[1])
ax.set_xlabel('Time steps', fontsize=15, labelpad=15)
ax.text(-xlim[1] // 5,
ylim[1] // 2,
'Cumulative\nreward',
fontsize=15,
verticalalignment='center',
horizontalalignment='center')
ax.plot([change_step, change_step, xlim[1] // 2, xlim[1] // 2],
[ylim[0], ylim[1], ylim[2] * .75, ylim[2]],
'k--',
lw=.6)
Δh, Δw = 1 / maze.H, 1 / maze.W
tb = Table(ax,
bbox=[abs(xlim[0]) / (abs(xlim[0]) + xlim[2]), .75, .4, .25])
tb2 = Table(ax, bbox=[.6, .75, .4, .25])
for i in range(maze.H):
for j in range(maze.W):
t = ''
if (i, j) == maze.S: t = 'S'
elif (i, j) == maze.G: t = 'G'
else: t = ''
c = tb.add_cell(i, j, Δw, Δh, text=t, loc='center')
c.set_lw(.5)
c.set_fontsize(10)
c2 = tb2.add_cell(i, j, Δw, Δh, text=t, loc='center')
c2.set_lw(.5)
c2.set_fontsize(10)
if (i, j) in maze.OBSTACLE: c.set_fc('#aaaaaa')
if (i, j) in maze.OBSTACLE2: c2.set_fc('#aaaaaa')
ax.add_table(tb)
ax.add_table(tb2)
plt.savefig(out, dpi=300, bbox_inches='tight', pad_inches=.3)
plt.close()
def draw_value_image(iteration, value_image, env):
fig, ax = plt.subplots()
plt.suptitle('Policy Evaluation: Iteration:{:d}'.format(iteration))
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = value_image.shape
height, width = 1.0 / nrows, 1.0 / ncols
# Add cells
for (i, j), val in np.ndenumerate(value_image):
if env.is_terminal([i, j]):
tb.add_cell(i,
j,
height,
width,
text=' ',
loc='center',
facecolor='white')
elif env.is_on_obstacle([i, j]):
tb.add_cell(i,
j,
height,
width,
text='╳',
loc='center',
facecolor='white')
else:
tb.add_cell(i,
j,
height,
width,
text=val,
loc='center',
facecolor='white')
# Row and column labels...
for i in range(nrows):
tb.add_cell(i,
-1,
height,
width,
text=i + 1,
loc='right',
edgecolor='none',
facecolor='none')
for i in range(ncols):
tb.add_cell(nrows,
i,
height,
width / 2,
text=i + 1,
loc='center',
edgecolor='none',
facecolor='none')
ax.add_table(tb)
plt.show()
def run(self):
self.parent.clear_plots()
if self.data is None:
length, tMin, tMax, fMin, fMax, lMin, lMax, peakF, peakL, peakT = ("",) * 10
else:
length = len(self.data)
tMin = format_time(self.extent.tMin, True)
tMax = format_time(self.extent.tMax, True)
fMin = format_precision(self.settings, freq=self.extent.fMin, fancyUnits=True)
fMax = format_precision(self.settings, freq=self.extent.fMax, fancyUnits=True)
lMin = format_precision(self.settings, level=self.extent.lMin, fancyUnits=True)
lMax = format_precision(self.settings, level=self.extent.lMax, fancyUnits=True)
peak = self.extent.get_peak_flt()
peakF = format_precision(self.settings, freq=peak[0], fancyUnits=True)
peakL = format_precision(self.settings, level=peak[1], fancyUnits=True)
peakT = format_time(peak[2], True)
text = [
["Sweeps", "", length],
["Extents", "", ""],
["", "Start", tMin],
["", "End", tMax],
["", "Min frequency", fMin],
["", "Max frequency", fMax],
["", "Min level", lMin],
["", "Max level", lMax],
["Peak", "", ""],
["", "Level", peakL],
["", "Frequency", peakF],
["", "Time", peakT],
]
table = Table(self.axes, loc="center")
table.set_gid("table")
rows = len(text)
cols = len(text[0])
for row in xrange(rows):
for col in xrange(cols):
table.add_cell(row, col, text=text[row][col], width=1.0 / cols, height=1.0 / rows)
if self.settings.grid:
colour = "LightGray"
else:
colour = "w"
set_table_colour(table, colour)
for i in range(3):
table.auto_set_column_width(i)
self.axes.add_table(table)
self.parent.redraw_plot()
self.parent.threadPlot = None
def plot_gridvalue(self, ax, mat):
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = mat.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i, j), val in np.ndenumerate(mat):
tb.add_cell(i, j, width, height, text=val,
loc='center', facecolor='white')
tb.set_fontsize(20)
ax.add_table(tb)
def show_grids(value_function, time_step):
fig = plt.figure()
ax = fig.add_subplot(1, 2, 1)
ax.set_axis_off()
tb = Table(ax)
plt.title(r"$V_" + str(time_step + 1) + "$ for the random policy")
nrows, ncols = value_function.shape
width, height = 1.0 / ncols, 1.0 / nrows
for (i, j), val in np.ndenumerate(value_function):
tb.add_cell(row=i,
col=j,
width=width,
height=height,
text=val,
loc='center')
ax.add_table(tb)
ax2 = fig.add_subplot(1, 2, 2)
ax2.set_axis_off()
tb2 = Table(ax2)
plt.title(r"Greedy policy on $V_" + str(time_step + 1) + "$")
for (i, j), val in np.ndenumerate(value_function):
if (i, j) in TERMINAL_STATE:
text = ""
else: # Compute the greedy policy by using the value function
max_action = -np.inf
max_action_index = []
for index, action in enumerate(ACTIONS):
new_pos = manage_boundaries((i + action[0], j + action[1]))
if (value_function[new_pos] == max_action
): # There are multiple optimal actions
max_action_index.append(index)
elif (value_function[new_pos] > max_action):
max_action = value_function[new_pos]
max_action_index = [index]
text = "{} {} {} {}".format(
(0 in max_action_index) * "↑", (2 in max_action_index) * "←",
(3 in max_action_index) * "→", (1 in max_action_index) * "↓")
tb2.add_cell(row=i,
col=j,
width=width,
height=height,
text=text,
loc='center')
ax2.add_table(tb2)
print("Use q to close the figure")
plt.draw()
plt.show()
def plotGrid(value, title):
value = np.round(value, decimals=1)
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = value.shape
width, height = 1.0 / ncols, 1.0 / nrows
for (i, j), val in np.ndenumerate(value):
tb.add_cell(i, j, width, height, text=val, loc='center')
ax.add_table(tb)
plt.title(title)
plt.show()
def probability_plot(probabilities,
selected_sentence,
dataset,
ploting_path,
top_n_probabilities=20,
max_length=120):
# Pyplot options
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
ncols = probabilities.shape[0]
width, height = 1.0 / (ncols + 1), 1.0 / (top_n_probabilities + 1)
# Truncate the time
selected_sentence = selected_sentence[:max_length]
probabilities = probabilities[:max_length]
# Sort the frequencies
sorted_indices = np.argsort(probabilities, axis=1)
probabilities = probabilities[
np.repeat(np.arange(probabilities.shape[0])[:, None],
probabilities.shape[1],
axis=1), sorted_indices][:, ::-1]
# Truncate the probabilities
probabilities = probabilities[:, :top_n_probabilities]
for (i, j), _ in np.ndenumerate(probabilities):
tb.add_cell(j + 1,
i,
height,
width,
text=unicode(str(
conv_into_char(sorted_indices[i, j, 1], dataset)[0]),
errors='ignore'),
loc='center',
facecolor=(1, 1 - probabilities[i, j, 0],
1 - probabilities[i, j, 0]))
for i, char in enumerate(selected_sentence):
tb.add_cell(0,
i,
height,
width,
text=unicode(char, errors='ignore'),
loc='center',
facecolor='green')
ax.add_table(tb)
plt.savefig(ploting_path)
def checkerboard_table(self, data, preyPosition):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for i in range(self.boardSize[0]):
for j in range(self.boardSize[1]):
if(i == preyPosition[0] and j == preyPosition[1]):
tb.add_cell(i, j, width, height, text=str(data[i][j]),
loc='center', facecolor='yellow')
else:
tb.add_cell(i, j, width, height, text=str(data[i][j]),
loc='center', facecolor='white')
# Row Labels...
for i in range(self.boardSize[0]):
tb.add_cell(i, -1, width, height, text=str(i), loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j in range(self.boardSize[1]):
tb.add_cell(-1, j, width, height/2, text=str(j), loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
def drawtable(data, rows, columns, title, folder='Table', rowname='',fmt='{:.2f}'):
nrows = len(rows)
ncols = len(columns)
fig, ax = plt.subplots(figsize=(ncols+2,nrows+2))
ax.set_axis_off()
rowlc='#F0F0F0'
collc='#F0F0F0'
cellc='#FFFFFF'
ecol='#0000FF'
font1 = FontProperties()
font1.set_size('9')
fontl = font1.copy()
fontl.set_weight('bold')
tb = Table(ax)#, bbox=[0.10,0.10,0.90,0.90])
tb.auto_set_font_size(False)
#tb.set_fontsize(100.0)
width, height = 0.95/(ncols+1), 0.95/(nrows+1)
for i in range(nrows):
tb.add_cell(i,-1, width*2, height, text=rows[i][:20], loc='right',edgecolor=ecol, facecolor=rowlc,fontproperties=fontl)
# Column Labels
for j in range(ncols):
tb.add_cell(-1, j, width, height/1.5, text=columns[j][:10], loc='center', edgecolor=ecol, facecolor=collc,fontproperties=fontl)
tb.add_cell(-1,-1, width*2, height/1.5, text=rowname[:10], loc='right',edgecolor=ecol, facecolor=rowlc,fontproperties=fontl)
# Add cells
for i in range(len(data)):
for j in range(len(data[i])):
val = data[i][j]
tb.add_cell(i,j,width, height, text=fmt.format(val), loc='center', edgecolor=ecol, facecolor=cellc, fontproperties=font1)
# Row Labels
ax.add_table(tb)
plt.savefig(folder+'/'+title+'.pdf')
#plt.show()
#sys.exit(0)
plt.close()
def task_table_plot(task_data):
"""
Plot task table, save in png file.
:param task_data: dataframe from get_task_table().
"""
groups = task_data.Group.values
task_no_group = task_data.drop('Group', axis=1)
nrows, ncols = task_no_group.shape
width, height = 1.0 / ncols, 1.0 / nrows
fig, ax = plt.subplots(figsize=(1, nrows*0.25))
ax.set_axis_off()
tbl = Table(ax)
tbl.auto_set_font_size(False)
# Columns width for non-auto-width columns
col_widths = [1, 1, 0.5, 1, 0.7, 0.7, 0.7, 0.7, 0.7]
palette = get_palette()
fontcolor = 'w'
for (i, j), val in np.ndenumerate(task_no_group):
fc = palette[groups[i]]
fontsize = 10
if j < 2:
loc = 'left'
font_family = None
if j == 0:
fontsize = 9
else:
loc = 'center'
font_family = 'DINPro'
if j > 3:
fontsize = 9
tbl.add_cell(i, j, col_widths[j], height, text=val,
loc=loc, facecolor=fc, edgecolor=fontcolor)
cell = tbl.get_celld()[(i, j)]
cell.set_linewidth(0.5)
cell.set_text_props(color=fontcolor, family=font_family, weight='bold', fontsize=fontsize)
# Column Labels...
for j, label in enumerate(task_no_group.columns):
tbl.add_cell(-1, j, col_widths[j], height*0.8, text=label, loc='center',
facecolor='gray', edgecolor='w')
cell = tbl.get_celld()[(-1, j)]
cell.set_linewidth(0.5)
cell.set_text_props(color=fontcolor, weight='bold', family='Verdana', fontsize=9)
tbl._autoColumns = [0, 1]
tbl.scale(1, 1.5) # scale y to cover blank in the bottom
ax.add_table(tbl)
ax.margins(0, 0)
fig.savefig('img/task_table', bbox_inches='tight', pad_inches=0.1, dpi=200)
def task_table_plot(task_data):
"""
Plot task table, save in png file.
:param task_data: dataframe from get_task_table().
"""
groups = task_data.Group.values
task_no_group = task_data.drop('Group', axis=1)
nrows, ncols = task_no_group.shape
width, height = 1.0 / ncols, 1.0 / nrows
fig, ax = plt.subplots(figsize=(1, nrows*0.25))
ax.set_axis_off()
tbl = Table(ax)
tbl.auto_set_font_size(False)
# Columns width for non-auto-width columns
col_widths = [1, 1, 0.5, 1, 0.7, 0.7, 0.7, 0.7, 0.7]
palette = get_palette()
fontcolor = 'w'
for (i, j), val in np.ndenumerate(task_no_group):
fc = palette[groups[i]]
fontsize = 10
if j < 2:
loc = 'left'
font_family = None
if j == 0:
fontsize = 9
else:
loc = 'center'
#font_family = 'DINPro'
if j > 3:
fontsize = 9
tbl.add_cell(i, j, col_widths[j], height, text=val,
loc=loc, facecolor=fc, edgecolor=fontcolor)
cell = tbl.get_celld()[(i, j)]
cell.set_linewidth(0.5)
cell.set_text_props(color=fontcolor, family=font_family, weight='bold', fontsize=fontsize)
# Column Labels...
for j, label in enumerate(task_no_group.columns):
tbl.add_cell(-1, j, col_widths[j], height*0.8, text=label, loc='center',
facecolor='gray', edgecolor='w')
cell = tbl.get_celld()[(-1, j)]
cell.set_linewidth(0.5)
cell.set_text_props(color=fontcolor, weight='bold', family='Verdana', fontsize=9)
tbl._autoColumns = [0, 1]
tbl.scale(1, 1.5) # scale y to cover blank in the bottom
ax.add_table(tbl)
ax.margins(0, 0)
fig.savefig('img/task_table', bbox_inches='tight', pad_inches=0.1, dpi=200)
def checkerboard_table(data, columns, rows, title, fmt='{:.2f}', logarea = 0.035):
fig, ax = plt.subplots()
plt.set_cmap('cool')
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
#plt.suptitle(title)
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
min_color = np.min(data)/logarea
max_color = np.max(data)/logarea
# Add cells
for (i,j), val in np.ndenumerate(data):
# Index either the first or second item of bkg_colors based on
# a checker board pattern
color = (val/logarea)/max_color
print val
if val > 0.0:
tb.add_cell(i, j, width, height, text=fmt.format(val),
loc='center', facecolor = str(1.0 - val/np.sum(data)))
else:
tb.add_cell(i, j, width, height)
# Row Labels...
for i in range(0,len(rows)):
tb.add_cell(i, -1, width, height, text=rows[i], loc='top',
edgecolor='none', facecolor='none')
# Column Labels...
for j in range(0,len(columns)):
tb.add_cell(-1, j, width, height/2.0, text=columns[j], loc='left',
edgecolor='none', facecolor='none')
ax.add_table(tb)
#.colorbar()
return fig
def show_grid(grid):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = grid.shape
width, height = 1.0/ncols, 1.0/nrows
for (i, j), val in np.ndenumerate(grid):
color = 'grey' if (i, j) == (0, 0) or (i, j) == (3, 3) else 'white'
tb.add_cell(i, j, width, height, text="{0:.2f}".format(val),
loc='center', facecolor=color)
ax.add_table(tb)
return ax
def draw_image(image):
plt.figure()
ax = plt.gca()
ax.set_axis_off()
table = Table(ax, bbox=[0, 0, 1, 1])
width, height = 1.0 / world_size, 1.0 / world_size
for i in range(world_size):
for j in range(world_size):
# image, i is x, j is y
table.add_cell(j, i, width, height, text=image[i, j], loc='center')
ax.add_table(table)
def probability_plot(probabilities,
selected,
vocab,
ploting_path,
top_n_probabilities=20,
max_length=120):
selected = selected[:max_length]
probabilities = probabilities[:max_length]
# target = ['a', 'b', 'c', 'd', 'e', 'f', 'a', 'b', 'c', 'd']
# probabilities = np.random.uniform(low=0, high=1, size=(10, 6)) # T x C
sorted_probabilities = np.zeros(probabilities.shape)
sorted_indices = np.zeros(probabilities.shape)
for i in range(probabilities.shape[0]):
sorted_probabilities[i, :] = np.sort(probabilities[i, :])
sorted_indices[i, :] = np.argsort(probabilities[i, :])
concatenated = np.zeros(
(probabilities.shape[0], probabilities.shape[1], 2))
concatenated[:, :, 0] = sorted_probabilities[:, ::-1]
concatenated[:, :, 1] = sorted_indices[:, ::-1]
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
ncols = concatenated.shape[0]
width, height = 1.0 / (ncols + 1), 1.0 / (top_n_probabilities + 1)
for (i, j), v in np.ndenumerate(concatenated[:, :top_n_probabilities, 0]):
tb.add_cell(j + 1,
i,
height,
width,
text=unicode(vocab[concatenated[i, j, 1].astype('int')],
errors='ignore'),
loc='center',
facecolor=(1, 1 - concatenated[i, j, 0],
1 - concatenated[i, j, 0]))
for i, char in enumerate(selected):
tb.add_cell(0,
i,
height,
width,
text=unicode(char, errors='ignore'),
loc='center',
facecolor='green')
ax.add_table(tb)
plt.savefig(ploting_path)
def _build_states(self):
self.t_ax = self.fig.add_axes([0.05, 0.05, .75, .9])
self.t_ax.set_axis_off()
nrows = max(self.data['row'])
ncols = max(self.data['column'])
width = 1.0 / ncols
height = 1.0 / nrows
tb = Table(self.t_ax)
for abb, row, col in zip(self.data['abbrev'], self.data['row'], self.data['column']):
tb.add_cell(row-1, col-1, width, height, text=abb.upper(), edgecolor='b',
loc='center')
tb.set_fontsize(20)
self.tb = self.t_ax.add_table(tb)
def _create_table(self):
"""Creates a table for displaying the entire field using matplotlib table."""
_, axis = plt.subplots()
axis.set_axis_off()
table = Table(axis, bbox=[0, 0, 1, 1])
try:
width, height = 1.0 / self.rows, 1.0 / self.cols
except ZeroDivisionError:
# No table is going to be drawn, cols or rows is 0
return
current_col = 0
while current_col < self.cols:
for current_row in range(0, self.rows):
value = self.data[current_row][current_col]
cell = table.add_cell(current_col,
current_row,
width,
height,
text=value or "",
loc='center')
if value != MINE:
text_color = self._get_color(value)
cell.get_text().set_color(text_color)
cell.get_text().set_fontsize(FONT_SIZE)
current_col += 1
title = f"Game, W: {self.rows}, H: {self.cols}, Mines: {self.mines}"
axis.set_title(title)
axis.add_table(table)
def main():
a, b, dot_num, additional_length_multiplier_x, additional_length_multiplier_y, plot_style, borders_style, \
solution_style, figsize, methods_number, solution_exact, data, target, epsilon, iter_lim \
= -0.5, 2.0, 1000, 0.0, 0.0, 'k-', 'k--', 'ro', (15.0, 7.5), 5, 0.0, [], "min", 1e-6, 1000
optimization_methods = (nlopt.dichotomy, nlopt.gsection, nlopt.fibonacci, nlopt.tangent, nlopt.parabolic)
optimization_methods_names = ("Метод дихотомии", "Метод золотого сечения", "Метод Фибоначчи", "Метод касательных",
"Метод парабол")
table_head = ("Название\nметода", "Численное\nрешение", "Значение\nцелевой\nфункции",
"Абсолютная\nпогрешность\n(аргумент)", "Абсолютная\nпогрешность\n(функция)")
fmt_a, fmt_b, fmt_solution_exact, fmt_target_value = r"%.", r"%.", r"%.", r"%."
fmt_a += r"%sf" % str(main_digits_num(a, int(-np.log10(epsilon))))
fmt_b += r"%sf" % str(main_digits_num(b, int(-np.log10(epsilon))))
fmt_solution_exact += r"%sf" % str(main_digits_num(solution_exact, int(-np.log10(epsilon))))
fmt_target_value += r"%sf" % str(main_digits_num(f(solution_exact), int(-np.log10(epsilon))))
x = np.linspace(a - additional_length_multiplier_x * (b - a), b + additional_length_multiplier_x * (b - a), dot_num)
y = f(x)
ncols, nrows = len(table_head), methods_number + 1
for i in range(methods_number):
solution_numerical = optimization_methods[i](f, a, b, target=target, epsilon=epsilon, iter_lim=iter_lim)
plt.figure(num=i + 1, figsize=figsize)
plt.title(optimization_methods_names[i])
plt.plot(x, y, plot_style, solution_numerical, f(solution_numerical), solution_style,
[a, a], [np.min(y) - additional_length_multiplier_y * (np.max(y) - np.min(y)),
np.max(y) + additional_length_multiplier_y * (np.max(y) - np.min(y))], borders_style,
[b, b], [np.min(y) - additional_length_multiplier_y * (np.max(y) - np.min(y)),
np.max(y) + additional_length_multiplier_y * (np.max(y) - np.min(y))], borders_style)
plt.grid(True)
data.append([optimization_methods_names[i], solution_numerical, f(solution_numerical),
np.abs(solution_numerical - solution_exact), np.abs(f(solution_numerical) - f(solution_exact))])
fig = plt.figure(num=methods_number + 1, figsize=figsize)
ax = plt.subplot()
ax.axis('off')
tab = Table(ax, bbox=[0, 0, 1, 1])
tab.auto_set_column_width(False)
tab.auto_set_font_size(False)
for j in range(ncols):
tab.add_cell(0, j, figsize[0] / ncols, 0.1, text=table_head[j], loc="center")
for i in range(1, nrows):
for j in range(ncols):
tab.add_cell(i, j, figsize[0] / ncols, 0.1, text=str(data[i - 1][j]), loc="center")
tab.set_fontsize(9.0)
ax.add_table(tab)
plt.title(r"$Задача: f(x) = |x| + 2x^2 \rightarrow %s, x\in[$" % target + fmt_a % a + r"; " + fmt_b % b
+ r"]%sТочное решение:" % "\n\n" + r"$x_{%s}$ = " % target + fmt_solution_exact % solution_exact +
r"; $f(x_{%s})$ = " % target + fmt_target_value % f(solution_exact))
plt.show()
plt.close()
def square_table(data, fmt='{:.0f}'):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(data):
tb.add_cell(i, j, width, height, text=fmt.format(val), loc='center')
"""
# Row and Column Labels...
for i, label in enumerate(data.columns):
tb.add_cell(i, -1, width, height, text=label, loc='right', edgecolor='none', facecolor='none')
tb.add_cell(-1, i, width, height/2, text=label, loc='center', edgecolor='none', facecolor='none')
"""
ax.add_table(tb)
return fig
def drawTable(data, rowLabels, columnLabels, max, isPositive, fmt='{:.2f}'):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i, j), val in np.ndenumerate(data):
# https://matplotlib.org/2.0.2/api/colors_api.html
if isPositive:
color = (1 - (data[i][j] / max), 1, 1 - (data[i][j] / max))
else:
color = (1, 1 - (data[i][j] / max), 1 - (data[i][j] / max))
tb.add_cell(i,
j,
width,
height,
text=fmt.format(val),
loc='center',
facecolor=color)
if j == 0:
tb.add_cell(i,
-1,
width,
height,
text=rowLabels[i],
loc='right',
edgecolor='white',
facecolor='white')
if i == 0:
tb.add_cell(-1,
j,
width,
height / 2,
text=columnLabels[j],
loc='center',
edgecolor='white',
facecolor='white')
tb.add_cell(-1,
-1,
width,
height / 2,
text="",
loc='center',
edgecolor='white',
facecolor='white')
ax.add_table(tb)
return fig
def plot_value(ax: plt.Axes):
rounded_value = np.round(learner.value, decimals=1)
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = rounded_value.shape
width, height = 1.0 / ncols, 1.0 / nrows
for (i, j), val in np.ndenumerate(rounded_value):
tb.add_cell(i,
j,
width,
height,
text=val,
loc="center",
facecolor="white")
ax.add_table(tb)
def draw_grid_world(value_array):
fig, ax = plt.subplots(1, 1)
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
num_rows, num_cols = value_array.shape
per_height, per_width = 1.0 / num_rows, 1.0 / num_cols
for (i, j), val in np.ndenumerate(value_array):
tb.add_cell(i,
j,
text=val,
width=per_width,
height=per_height,
loc='center')
tb.set_fontsize(28)
ax.add_table(tb)
def plot_param_legend(legend, plot_size, placement):
# LEGEND
rowSpan = max(plot_size[0] - 1, 1 / len(legend))
ax = plt.subplot2grid(plot_size,
placement,
colspan=plot_size[1] - placement[1],
rowspan=rowSpan)
ax.set_axis_off()
plt.title("Parametrization\nused")
tb = Table(ax, bbox=[0, 0, 1, 1])
height = 1. / len(legend)
for row, lgd in enumerate(legend):
tb.add_cell(row,
0,
1.,
height,
text=lgd,
loc='left',
edgecolor='white')
ax.add_table(tb)
def test_table_cells():
fig, ax = plt.subplots()
table = Table(ax)
cell = table.add_cell(1, 2, 1, 1)
assert isinstance(cell, CustomCell)
assert cell is table[1, 2]
cell2 = CustomCell((0, 0), 1, 2, visible_edges=None)
table[2, 1] = cell2
assert table[2, 1] is cell2
def test_table_cells():
fig, ax = plt.subplots()
table = Table(ax)
cell = table.add_cell(1, 2, 1, 1)
assert isinstance(cell, CustomCell)
assert cell is table[1, 2]
cell2 = CustomCell((0, 0), 1, 2, visible_edges=None)
table[2, 1] = cell2
assert table[2, 1] is cell2
def probability_plot(probabilities, selected_sentence, dataset, ploting_path,
top_n_probabilities=20, max_length=120):
# Pyplot options
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
ncols = probabilities.shape[0]
width, height = 1.0 / (ncols + 1), 1.0 / (top_n_probabilities + 1)
# Truncate the time
selected_sentence = selected_sentence[:max_length]
probabilities = probabilities[:max_length]
# Sort the frequencies
sorted_indices = np.argsort(probabilities, axis=1)
probabilities = probabilities[
np.repeat(np.arange(probabilities.shape[0])[
:, None], probabilities.shape[1], axis=1),
sorted_indices][:, ::-1]
# Truncate the probabilities
probabilities = probabilities[:, :top_n_probabilities]
for (i, j), _ in np.ndenumerate(probabilities):
tb.add_cell(j + 1, i, height, width,
text=unicode(str(conv_into_char(sorted_indices[i, j, 1],
dataset)[0]),
errors='ignore'),
loc='center',
facecolor=(1,
1 - probabilities[i, j, 0],
1 - probabilities[i, j, 0]))
for i, char in enumerate(selected_sentence):
tb.add_cell(0, i, height, width,
text=unicode(char, errors='ignore'),
loc='center', facecolor='green')
ax.add_table(tb)
plt.savefig(ploting_path)
def fill_table(values):
"""Fill the values in a table
:param values: state values
:type values: dict
:return: None
:rtype: None
"""
fig, ax = plt.subplots()
tb = Table(ax, bbox=[0, 0, 1, 1])
for (x, y), val in values.items():
tb.add_cell(x,
y,
1 / 5,
1 / 5,
text=round(val, 1),
loc='center',
facecolor='white')
ax.add_table(tb)
ax.set_axis_off()
def checkerboard_table(data, fmt='{:.2f}', bkg_colors=['yellow', 'white']):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
# セル追加
for (i,j), val in np.ndenumerate(data):
idx = [j % 2, (j + 1) % 2][i % 2]
color = bkg_colors[idx]
tb.add_cell(i, j, width, height, text=fmt.format(val),
loc='center', facecolor=color)
# 行ラベル
for i, label in enumerate(data.index):
tb.add_cell(i, -1, width, height, text=label, loc='right',
edgecolor='none', facecolor='none')
# 列ラベル
for j, label in enumerate(data.columns):
tb.add_cell(-1, j, width, height/2, text=label, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
return fig
def draw_q_value_image(dyna_maze, q_value, run, planning_steps, episode):
# 축 표시 제거, 크기 조절 등 이미지 그리기 이전 설정 작업
fig, axis = plt.subplots()
axis.set_axis_off()
table = Table(axis, bbox=[0, 0, 1, 1])
num_rows, num_cols = dyna_maze.MAZE_HEIGHT, dyna_maze.MAZE_WIDTH
width, height = 1.0 / num_cols, 1.0 / num_rows
for i in range(dyna_maze.MAZE_HEIGHT):
for j in range(dyna_maze.MAZE_WIDTH):
if np.sum(q_value[i][j]) == 0.0:
symbol = " "
else:
action_idx = np.argmax(q_value[i][j])
symbol = dyna_maze.ACTION_SYMBOLS[action_idx]
table.add_cell(i, j, width, height, text=symbol, loc='center', facecolor='white')
# 행, 열 라벨 추가
for i in range(dyna_maze.MAZE_HEIGHT):
table.add_cell(i, -1, width, height, text=i, loc='right', edgecolor='none', facecolor='none')
for j in range(dyna_maze.MAZE_WIDTH):
table.add_cell(-1, j, width, height/2, text=j, loc='center', edgecolor='none', facecolor='none')
for key, cell in table.get_celld().items():
cell.get_text().set_fontsize(20)
axis.add_table(table)
plt.savefig('images/maze_action_values_{0}_{1}_{2}.png'.format(run, planning_steps, episode))
plt.close()
def draw_lat_matrix(fname,
data,
title="",
lat_type=None,
lat_types=None,
columns=[],
rows=[]):
bkg_colors = ['#CCFFFF', 'white']
fmt = '{:.3f}'
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = data.shape
assert nrows == len(rows)
assert ncols == len(columns)
width, height = 1.0 / ncols * 2, 1.0 / nrows * 2
for (i, j), val in np.ndenumerate(data):
idx = [j % 2, (j + 1) % 2][i % 2]
color = bkg_colors[idx]
if val:
if lat_type:
txt = fmt.format(ls.exec_fn(val, lat_type))
else:
assert lat_types
txt = fmt.format(ls.exec_fn(val, lat_types[i]))
else:
txt = "-"
tb.add_cell(i,
j,
width,
height,
text=txt,
loc='center',
facecolor=color)
# Row Labels...
for i, label in enumerate(rows):
tb.add_cell(i,
-1,
width,
height,
text=label,
loc='right',
edgecolor='none',
facecolor='none')
# Column Labels...
for j, label in enumerate(columns):
tb.add_cell(-1,
j,
width,
height / 2,
text=label,
loc='center',
edgecolor='none',
facecolor='none')
ax.add_table(tb)
if title:
ax.set_title("\n".join(wrap(title)), y=1.08)
savefig('../figs/' + fname + '.pdf', bbox_inches='tight')
plt.close()
def display(self, agent):
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.set_axis_off()
tb = Table(ax)
nrows, ncols = self.world.shape
width, height = 1.0 / ncols, 1.0 / nrows
for (i, j), val in np.ndenumerate(self.world):
if (i, j) == (agent.pos_y, agent.pos_x):
tb.add_cell(row=i,
col=j,
width=width,
height=height,
facecolor=agent.color)
elif (i, j) == self.ending_point:
tb.add_cell(row=i,
col=j,
width=width,
height=height,
facecolor="red")
else:
tb.add_cell(row=i,
col=j,
width=width,
height=height,
text=self.dict_world_to_text[val],
facecolor=self.dict_world_to_color[val],
loc="center")
ax.add_table(tb)
plt.plot()
plt.show()
def plot_gridworld(self, ax):
fs = 20
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
w = self.w
width = height = 1.0 / w
# Add cells
for i in range(w):
for j in range(w):
val = ''
if (i, j) == self.A:
val = 'A'
elif (i, j) == self.B:
val = 'B'
elif (i, j) == self.A_:
val = 'A\''
elif (i, j) == self.B_:
val = 'B\''
tb.add_cell(i,
j,
width,
height,
text=val,
loc='center',
facecolor='white')
tb.set_fontsize(fs)
ax.add_table(tb)
p2g = lambda p: (p[1] * width + width / 2 + 0.05, 1 - p[0] * height -
height / 2)
for x, y, t in [(p2g(self.A), p2g(self.A_), '+10'),
(p2g(self.B), p2g(self.B_), '+5')]:
arrow = patches.FancyArrowPatch(
x,
y,
connectionstyle="arc3,rad=-.5",
arrowstyle="Simple,tail_width=0.5,head_width=4,head_length=8",
color="k")
ax.add_artist(arrow)
plt.text((x[0] + y[0]) / 2, (x[1] + y[1]) / 2, t, fontsize=fs - 2)
def checkerboard_table(data, fmt='{:.2f}', bkg_colors=['yellow', 'white']):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(data):
# Index either the first or second item of bkg_colors based on
# a checker board pattern
idx = [j % 2, (j + 1) % 2][i % 2]
color = bkg_colors[idx]
tb.add_cell(i, j, width, height, text=val,
loc='center', facecolor=color)
# Row Labels...
for i, label in enumerate(data.index):
tb.add_cell(i, -1, width, height, text=label, loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j, label in enumerate(data.columns):
tb.add_cell(-1, j, width, height/2, text=label, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
return fig
def draw_image(image):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = image.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(image):
# Index either the first or second item of bkg_colors based on
# a checker board pattern
idx = [j % 2, (j + 1) % 2][i % 2]
color = 'white'
tb.add_cell(i, j, width, height, text=val,
loc='center', facecolor=color)
# Row Labels...
for i, label in enumerate(range(len(image))):
tb.add_cell(i, -1, width, height, text=label+1, loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j, label in enumerate(range(len(image))):
tb.add_cell(-1, j, width, height/2, text=label+1, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
plt.show()
def plot_show(sample_count):
fig, ax = plt.subplots(figsize=(25,25))
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
all_cards = get_all_cards()
# nrows, ncols = len(label), len(label)
nrows, ncols = len(all_cards), len(all_cards)
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for i in range(len(all_cards)):
for j in range(len(all_cards)):
if all_cards[i] == all_cards[j]:
EHS_value = 0.0
else:
EHS_value = computer_EHS([all_cards[i], all_cards[j]], sample_count) * 100
color = get_color(EHS_value)
tb.add_cell(i+1, j, width, height, text=str(int(EHS_value)),
loc='center', facecolor=color)
# Row Labels...
for i in range(len(all_cards)):
tb.add_cell(i + 1, -1, width, height, text=all_cards[i], loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j in range(len(all_cards)):
tb.add_cell(0, j, width, height / 2, text=all_cards[j], loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
plt.title("EHS")
plt.show()
def draw_image(image):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = image.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(image):
# Index either the first or second item of bkg_colors based on
# a checker board pattern
idx = [j % 2, (j + 1) % 2][i % 2]
color = 'white'
tb.add_cell(i, j, width, height, text=val,
loc='center', facecolor=color)
# Row Labels...
for i, label in enumerate(range(len(image))):
tb.add_cell(i, -1, width, height, text=label+1, loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j, label in enumerate(range(len(image))):
tb.add_cell(-1, j, width, height/2, text=label+1, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
def checkerboard_table(data,nc,npop,indexname, fmt='{:.0f}', bkg_colors=['yellow', 'white']):
fig, ax = plt.subplots(figsize=(nc*1.5,npop*1.5))
ax.set_axis_off()
ax.set_xlabel('Population')
tb = Table(ax)
tb.auto_set_font_size(False)
tb.set_fontsize(14)
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(data):
# Index either the first or second item of bkg_colors based on
# a checker board pattern
idx = 0 if val ==1 else 1
color = bkg_colors[idx]
tb.add_cell(i, j, width, height, text=fmt.format(val),
loc='center', facecolor=color)
# Row Labels...
for i, label in enumerate(data.index):
tb.add_cell(i, -1, width, height, text= indexname + ' ' + str(label + 1), loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j, label in enumerate(data.columns):
tb.add_cell(-1, j, width, height/2, text=label, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
#plt.savefig("hk.pdf")
return fig
def visualize_results_plate_class_membership(data, fmt='{:.2f}', bkg_colors=['cyan', 'white']):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = data.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(data):
# Index either the first or second item of bkg_colors based on a checker board pattern
#idx = [j % 2, (j + 1) % 2][i % 2]
#color = bkg_colors[idx]
if (val > 0.5):
color = bkg_colors[0]
else:
color = bkg_colors[1]
tb.add_cell(i, j, width, height, text=fmt.format(val), loc='center', facecolor=color)
# axis labels for rows ...
for i, label in enumerate(string.ascii_uppercase[:nrows:]):
tb.add_cell(i, -1, width, height, text=label, loc='right', edgecolor='none', facecolor='none')
# axis labels for cols ...
for j, label in enumerate(data.columns):
tb.add_cell(-1, j, width, height/2, text=label+1, loc='center', edgecolor='none', facecolor='none')
ax.add_table(tb)
fig.suptitle("Visualize classification results - Plate with class memberships")
return fig
def draw_image(image):
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
nrows, ncols = image.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i, j), val in np.ndenumerate(image):
# add state labels
if [i, j] == A_POS:
val = str(val) + " (A)"
if [i, j] == A_PRIME_POS:
val = str(val) + " (A')"
tb.add_cell(i, j, width, height, text=val,
loc='center', facecolor='white')
# Row and column labels...
for i in range(len(image)):
tb.add_cell(i, -1, width, height, text=i+1, loc='right',
edgecolor='none', facecolor='none')
for i in range(len(image[0])):
tb.add_cell(-1, i, width, height/2, text=i+1, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
def sort_fellows_table_pdf(names, jobs, companies, projects, subjects, unis, degs, name_plot):
table = OrderedDict((
('Name',names),
('Job',jobs),
('Company',companies),
('Project',projects),
('Subject',subjects),
('University', unis),
('Degree',degs)))
Headn = ['Name','Job','Company','Project','Subject','University','Degree']
data = pandas.DataFrame(table)
#print data
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = data.shape
wcell = 1
hcell = 1
wpad = 0.5
hpad = 0.5
print "Making table"
#fig = plt.figure(figsize=(5, 20))
width, height = 1.0 / (ncols*1.0), 1.0 / (nrows*2.0)
matplotlib.rcParams.update({'font.size': 50})
print nrows, ncols
# Add cells
print data[Headn[1]].iloc[0]
for i in range(0,ncols):
for j in range(0,nrows-1):
# Index either the first or second item of bkg_colors based on
# a checker board pattern
#idx = [j % 2, (j + 1) % 2][i % 2]
txt = "\n".join(wrap(data[Headn[i]].iloc[j], 40))
nmrows = len(txt)/20.0
print len(txt), nmrows
#raw_input('check')
color = "white"
tb.add_cell(j, i, width, height*2.0, text=txt,
loc='center', facecolor="white")
# Row Labels...
for i in range(0,nrows-1):
label = str(i)
tb.add_cell(i, -1, width, height*2.0, text=label, loc='right',
edgecolor='black', facecolor='lightblue')
# Column Labels...
for j, label in enumerate(data.columns):
tb.add_cell(-1, j, width, height, text=label, loc='center',
edgecolor='black', facecolor='lightcoral')
ax.add_table(tb)
plt.savefig(name_plot+'.pdf', bbox_inches = "tight")
return ''
def probability_plot(probabilities, selected, vocab, ploting_path,
top_n_probabilities=20, max_length=120):
selected = selected[:max_length]
probabilities = probabilities[:max_length]
# target = ['a', 'b', 'c', 'd', 'e', 'f', 'a', 'b', 'c', 'd']
# probabilities = np.random.uniform(low=0, high=1, size=(10, 6)) # T x C
sorted_probabilities = np.zeros(probabilities.shape)
sorted_indices = np.zeros(probabilities.shape)
for i in range(probabilities.shape[0]):
sorted_probabilities[i, :] = np.sort(probabilities[i, :])
sorted_indices[i, :] = np.argsort(probabilities[i, :])
concatenated = np.zeros((
probabilities.shape[0], probabilities.shape[1], 2))
concatenated[:, :, 0] = sorted_probabilities[:, ::-1]
concatenated[:, :, 1] = sorted_indices[:, ::-1]
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
ncols = concatenated.shape[0]
width, height = 1.0 / (ncols + 1), 1.0 / (top_n_probabilities + 1)
for (i, j), v in np.ndenumerate(concatenated[:, :top_n_probabilities, 0]):
tb.add_cell(j + 1, i, height, width,
text=unicode(vocab[concatenated[i, j, 1].astype('int')],
errors='ignore'),
loc='center', facecolor=(1,
1 - concatenated[i, j, 0],
1 - concatenated[i, j, 0]))
for i, char in enumerate(selected):
tb.add_cell(0, i, height, width,
text=unicode(char, errors='ignore'),
loc='center', facecolor='green')
ax.add_table(tb)
plt.savefig(ploting_path)
def test_table_cells():
fig, ax = plt.subplots()
table = Table(ax)
cell = table.add_cell(1, 2, 1, 1)
assert isinstance(cell, CustomCell)
assert cell is table[1, 2]
cell2 = CustomCell((0, 0), 1, 2, visible_edges=None)
table[2, 1] = cell2
assert table[2, 1] is cell2
# make sure gettitem support has not broken
# properties and setp
table.properties()
plt.setp(table)
def show_interface(result,A,startPos,endPos):
colors=['white','grey']
fig=plt.figure(figsize=(10,10))
ax=plt.subplot(111)
ax.set_ylim([0,A.shape[0]])
ax.set_xlim([0,A.shape[1]])
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = A.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j),val in np.ndenumerate(A):
color=colors[val]
tb.add_cell(i, j, width, height,loc='center', facecolor=color)
# Row Labels...
for i in range(A.shape[0]):
tb.add_cell(i, -1, width, height, text=i, loc='right',
edgecolor='none', facecolor='none')
# Column Labels
for j in range(A.shape[1]):
tb.add_cell(-1, j, width, height/2, text=j, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
#Ajout Chemin
for i,j in result[2]:
ax.add_line(lines.Line2D((i[1],j[1]),(i[0],j[0]),linewidth=3,zorder=1))
#Ajout Depart
start=startPos[:2][::-1]
start_circle=Circle(start,radius=0.2,alpha=0.8, color='g',zorder=2,label='Position de Depart')
ax.add_patch(start_circle)
#Ajout Direction de Depart
start_dir=startPos[2]
start_posA=start
if(start_dir==1):
start_posB=(start_posA[0],start_posA[1]-1)
if(start_dir==2):
start_posB=(start_posA[0]+1,start_posA[1])
if(start_dir==3):
start_posB=(start_posA[0],start_posA[1]+1)
if(start_dir==4):
start_posB=(start_posA[0]-1,start_posA[1])
arrow=FancyArrowPatch(start_posA,start_posB,arrowstyle='->',color='m',mutation_scale=15.0,lw=2,zorder=3,label='Sens de Depart')
ax.add_patch(arrow)
#Ajout Arrivee
end=endPos[:2][::-1]
end_circle=Circle(end,radius=0.2,alpha=0.9, color='r',zorder=2,label='Position d\'arrivee')
ax.add_patch(end_circle)
ax.invert_yaxis()
ax.legend(bbox_to_anchor=(1.1, 1.05))
plt.show()
def sort_fellows_table_nproj_pdf(names, jobs, companies, subjects, unis, degs, name_plot):
table = OrderedDict((
('Name',names),
('Job',jobs),
('Company',companies),
('Subject',subjects),
('University', unis),
('Degree',degs)))
Headn = ['Name','Job','Company', 'Subject','University','Degree']
data = pandas.DataFrame(table)
#print data
fig, ax = plt.subplots()
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = data.shape
#fig = plt.figure(figsize=(5, 20))
width, height = 1.0 / (ncols), 1.0 / (nrows)
matplotlib.rcParams.update({'font.size': 20})
print nrows, ncols
# Add cells
print data[Headn[1]].iloc[0]
for i in range(0,ncols):
for j in range(0,nrows-1):
txt = "\n".join(wrap(data[Headn[i]].iloc[j], 40))
color = "white"
tb.add_cell(j, i, width, height, text=txt,
loc='center', facecolor="white")
# Row Labels...
for i in range(0,nrows-1):
label = str(i)
tb.add_cell(i, -1, width, height, text=label, loc='right',
edgecolor='black', facecolor='lightblue')
# Column Labels...
for j, label in enumerate(data.columns):
tb.add_cell(-1, j, width, height/2.0, text=label, loc='center',
edgecolor='black', facecolor='lightcoral')
ax.add_table(tb)
plt.savefig(name_plot+'.pdf', bbox_inches = "tight")
return ''
def draw_lat_matrix(fname,data,title="",lat_type=None,lat_types=None,columns=[],rows=[]):
bkg_colors=['#CCFFFF','white']
fmt='{:.3f}'
fig,ax=plt.subplots()
ax.set_axis_off()
tb=Table(ax,bbox=[0,0,1,1])
nrows,ncols=data.shape
assert nrows==len(rows)
assert ncols==len(columns)
width, height = 1.0 / ncols * 2, 1.0 / nrows * 2
for (i,j),val in np.ndenumerate(data):
idx = [j % 2, (j + 1) % 2][i % 2]
color = bkg_colors[idx]
if val:
if lat_type:
txt=fmt.format(ls.exec_fn(val,lat_type))
else:
assert lat_types
txt=fmt.format(ls.exec_fn(val,lat_types[i]))
else:
txt="-"
tb.add_cell(i, j, width, height, text=txt,
loc='center', facecolor=color)
# Row Labels...
for i, label in enumerate(rows):
tb.add_cell(i, -1, width, height, text=label, loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j, label in enumerate(columns):
tb.add_cell(-1, j, width, height/2, text=label, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
if title:
ax.set_title("\n".join(wrap(title)), y=1.08)
savefig('../figs/' + fname +'.pdf', bbox_inches='tight')
plt.close()
class Interface():
def __init__(self,figsize=(6,6)):
self.figsize=figsize
self.size_slider=IntSlider(description='Grid Size',min=4,max=50)
display(self.size_slider)
self.nb_ob_slider=IntSlider(description='Obstacles',min=0,max=7)
display(self.nb_ob_slider)
self.gen_inst_button=Button(description='Generate Instance',margin=10)
self.gen_pos_button=Button(description='Generate Start/End Positions',margin=10)
self.gen_path_button=Button(description='Generate Path',margin=10)
self.inst_but_container=HBox(children=[self.gen_inst_button,self.gen_pos_button,self.gen_path_button])
self.inst_but_container.width = '100%'
display(self.inst_but_container)
self.show_path_button=Latex(value='Path: Value: Actions:',margin=10)
display(self.show_path_button)
self.size_slider.on_trait_change(self._on_size_slider_change,'value')
self.gen_inst_button.on_click(self._on_gen_inst_button_click)
self.gen_pos_button.on_click(self._on_pos_button_click)
self.gen_path_button.on_click(self._on_gen_path_button_click)
self.gen_path_button.disabled=True
self.gen_pos_button.disabled=True
plt.close()
plt.axis('off')
self.fig=plt.figure(figsize=self.figsize)
self.ax=self.fig.add_subplot(111)
def _on_size_slider_change(self,name,value):
self.nb_ob_slider.max=int(value)**2/2-4 #Constrain on number of obstacles
def _on_gen_inst_button_click(self,b):
self.gen_path_button.disabled=True
self.gen_pos_button.disabled=False
self.show_path_button.value='Path: Value: Actions:'
for line in self.ax.lines:
line.set_visible(False)
del(line)
#Instance Generation
self.M=self.size_slider.value
self.nb_ob=self.nb_ob_slider.value
self.A=gen_rand_instance(self.M,self.M,self.nb_ob)
self.G=gen_graph(self.A)
if hasattr(self, 'ax'):
# print self.ax
self.ax.cla()
if hasattr(self, 'start_circle'):
del(self.start_circle)
del(self.end_circle)
del(self.arrow)
colors=['white','grey']
self.ax.set_ylim([0,self.A.shape[0]])
self.ax.set_xlim([0,self.A.shape[1]])
self.ax.set_axis_off()
self.tb = Table(self.ax, bbox=[0,0,1,1])
nrows, ncols = self.A.shape
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j),val in np.ndenumerate(self.A):
color=colors[val]
self.tb.add_cell(i, j, width, height,loc='center', facecolor=color)
# Row Labels...
for i in range(self.A.shape[0]):
self.tb.add_cell(i, -1, width, height, text=i, loc='right',
edgecolor='none', facecolor='none')
# Column Labels
for j in range(self.A.shape[1]):
self.tb.add_cell(-1, j, width, height/2, text=j, loc='center',
edgecolor='none', facecolor='none')
self.ax.add_table(self.tb)
self.ax.invert_yaxis()
#self.leg=self.ax.legend(bbox_to_anchor=(1.3, 1.05),fancybox=True)
#self.leg.get_frame().set_alpha(0.5)
#self.ax.legend()
plt.show()
def _on_pos_button_click(self,b):
for line in self.ax.lines:
line.set_visible(False)
del(line)
self.gen_path_button.disabled=False
self.start,self.end=gen_rand_positions(self.G)
#Ajout Depart
start_inst=self.start[:2][::-1]
#Ajout Direction de Depart
start_dir=self.start[2]
start_posA=start_inst
end_inst=self.end[:2][::-1]
if(start_dir==1):
start_posB=(start_posA[0],start_posA[1]-1)
if(start_dir==2):
start_posB=(start_posA[0]+1,start_posA[1])
if(start_dir==3):
start_posB=(start_posA[0],start_posA[1]+1)
if(start_dir==4):
start_posB=(start_posA[0]-1,start_posA[1])
if hasattr(self, 'start_circle'): #deja trace
self.start_circle.set_visible(True)
self.end_circle.set_visible(True)
self.arrow.set_visible(True)
self.start_circle.center=start_inst
self.arrow.set_positions(start_posA,start_posB)
self.end_circle.center=end_inst
self.show_path_button.value='Path: Value: Actions:'
else: #jamais trace encore
#Position de Depart
self.start_circle=Circle(start_inst,radius=0.5,alpha=0.8, color='g',zorder=2,label='Depart',clip_on=False)
self.ax.add_patch(self.start_circle)
#Direction de Depart
self.arrow=FancyArrowPatch(start_posA,start_posB,arrowstyle='->',color='m',mutation_scale=15.0,lw=2,zorder=3,clip_on=False)
self.ax.add_patch(self.arrow)
#Ajout Arrivee
self.end_circle=Circle(end_inst,radius=0.5,alpha=0.8, color='r',zorder=2,label='Arrivee',clip_on=False)
self.ax.add_patch(self.end_circle)
self.leg=self.ax.legend(bbox_to_anchor=(1.1, 1.05),fancybox=True)
self.leg.get_frame().set_alpha(0.5)
plt.show()
def _on_gen_path_button_click(self,b):
self.gen_path_button.disabled=True
self.result=gen_shortest_path(self.start,self.end,self.G)
self.show_path_button.value='Path: Value: '+str(self.result[0])+' Actions: '+' '.join(e for e in self.result[1])
#Ajout Chemin
for i,j in self.result[2]:
self.ax.add_line(lines.Line2D((i[1],j[1]),(i[0],j[0]),linewidth=3,zorder=1,clip_on=False))
plt.draw()
def shmoo_plotting(self):
''' pixel register shmoo plot '''
shmoopdf = PdfPages('shmoo.pdf')
shmoonp = np.array(self.shmoo_errors)
data = shmoonp.reshape(len(self.voltages),-1,order='F')
fig, ax = plt.subplots()
plt.title('Pixel registers errors')
ax.set_axis_off()
fig.text(0.70, 0.05, 'SPI clock (MHz)', fontsize=14)
fig.text(0.02, 0.90, 'Supply voltage (V)', fontsize=14, rotation=90)
tb = Table(ax, bbox=[0.01,0.01,0.99,0.99])
ncols = len(self.bitfiles)
nrows = len(self.voltages)
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(data):
color = ''
if val == 0: color = 'green'
if (val > 0 & val < 10): color = 'yellow'
if val > 10: color = 'red'
tb.add_cell(i, j, width, height, text=str(val),
loc='center', facecolor=color)
# Row Labels...
for i in range(len(self.voltages)):
tb.add_cell(i, -1, width, height, text=str(self.voltages[i]), loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j in range(len(self.bitfiles)):
newlabel1 = str(self.bitfiles[j][-9:-7]).replace("_","")
tb.add_cell(nrows+1, j, width, height/2, text=newlabel1, loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
shmoopdf.savefig()
''' global register shmoo plot '''
shmoo_glob_np = np.array(self.shmoo_global_errors)
data_g = shmoo_glob_np.reshape(len(self.voltages),-1,order='F')
fig_g, ax_g = plt.subplots()
ax_g.set_axis_off()
fig_g.text(0.70, 0.05, 'SPI clock (MHz)', fontsize=14)
fig_g.text(0.02, 0.90, 'Supply voltage (V)', fontsize=14, rotation=90)
tb_g = Table(ax_g, bbox=[0.01,0.01,0.99,0.99])
plt.title('Global registers errors')
# Add cells
for (i,j), val_g in np.ndenumerate(data_g):
color = ''
if val_g == 0: color = 'green'
if val_g > 0: color = 'red'
tb_g.add_cell(i, j, width, height, text=str(val_g),
loc='center', facecolor=color)
# Row Labels...
for i in range(len(self.voltages)):
tb_g.add_cell(i, -1, width, height, text=str(self.voltages[i]), loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j in range(len(self.bitfiles)):
newlabel = str(self.bitfiles[j][-9:-7]).replace("_","")
tb_g.add_cell(nrows+1, j, width, height/2, text=newlabel, loc='center',
edgecolor='none', facecolor='none')
ax_g.add_table(tb_g)
shmoopdf.savefig()
shmoopdf.close()
def run(self):
self.parent.clear_plots()
if self.data is None:
self.parent.threadPlot = None
return
tMin = format_time(self.extent.tMin, True)
tMax = format_time(self.extent.tMax, True)
fMin = format_precision(self.settings, freq=self.extent.fMin,
fancyUnits=True)
fMax = format_precision(self.settings, freq=self.extent.fMax,
fancyUnits=True)
lMin = format_precision(self.settings, level=self.extent.lMin,
fancyUnits=True)
lMax = format_precision(self.settings, level=self.extent.lMax,
fancyUnits=True)
peak = self.extent.get_peak_flt()
peakF = format_precision(self.settings, freq=peak[0],
fancyUnits=True)
peakL = format_precision(self.settings, level=peak[1],
fancyUnits=True)
peakT = format_time(peak[2], True)
text = [['Sweeps', '', len(self.data)],
['Extents', '', ''],
['', 'Start', tMin],
['', 'End', tMax],
['', 'Min frequency', fMin],
['', 'Max frequency', fMax],
['', 'Min level', lMin],
['', 'Max level', lMax],
['Peak', '', ''],
['', 'Level', peakL],
['', 'Frequency', peakF],
['', 'Time', peakT],
]
table = Table(self.axes, loc='center', gid='table')
rows = len(text)
cols = len(text[0])
for row in xrange(rows):
for col in xrange(cols):
table.add_cell(row, col,
text=text[row][col],
width=1.0 / cols, height=1.0 / rows)
if self.settings.grid:
colour = 'LightGray'
else:
colour = 'w'
set_table_colour(table, colour)
for i in range(3):
table.auto_set_column_width(i)
self.axes.add_table(table)
noData = find_artists(self.axes, 'noData')
noData[0].set_alpha(0)
self.parent.redraw_plot()
self.parent.threadPlot = None
def table_plot(df, figsize=(12, 9), value_format='text', fontsize=None,
positive_color=None, negative_color=None, header_color=None, index_color=None,
fill_color=None, positive_fill_color=None, negative_fill_color=None,
header_fill_color=None, index_fill_color=None, title=None, decimals=2, **kwargs):
"""
Plot DataFrame as a table
Parameters
----------
df : DataFrame
Data to be plotted as a table
figsize : tuple, optional
2-ple of (x, y) dimensions for figures in inches
value_format : string, optional
Format of the table values. Options supported are 'text' and 'numeric'.
fontsize : int, optional
Font size
positive_color : string, optional
Color to print positive values
negative_color : string, optional
Color to print negative cells
header_color : string, optional
Color to print header values
index_color : string, optional
Color to print index values
fill_color : string, optional
Color to fill table cells
positive_fill_color : string, optional
Color to fill cells with positive values
negative_fill_color : string, optional
Color to fill cells with negative values
header_fill_color : string, optional
Color to fill header cells
index_fill_color : string, optional
Color to fill index cells
title : string, optional
Table title
decimals : int, optional
If value_format is numeric, the number of decimal places used to round values
Returns
-------
fig : Figure
Figure containing the table plot
"""
if not isinstance(df, pd.DataFrame):
raise TypeError('df should be a DataFrame object')
if value_format not in ['text', 'numeric']:
raise ValueError('%s is not a valid format' % value_format)
# draw table
fig, ax = plt.subplots(figsize=figsize)
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
num_cols, num_rows = len(df.columns), len(df.index)
width, height = 1.0 / num_cols, 1.0 / num_rows
# add table cells
loc='center'
for (i, j), val in np.ndenumerate(df):
value = df.iloc[i, j]
text_color = 'black'
cell_color = 'none'
if fill_color is not None:
cell_color = fill_color
if isinstance(value, int) or isinstance(value, float):
if np.isnan(value):
continue
if positive_color is not None and value >= 0:
text_color = positive_color
if positive_fill_color is not None and value >= 0:
cell_color = positive_fill_color
if negative_color is not None and value < 0:
text_color = negative_color
if negative_fill_color is not None and value < 0:
cell_color = negative_fill_color
if value_format == 'text':
tb.add_cell(i + 1, j + 1, width, height, text=str(val), loc=loc, facecolor=cell_color)
elif value_format == 'numeric':
value_str = str(round(val, decimals))
tb.add_cell(i + 1, j + 1, width, height, text=value_str, loc=loc, facecolor=cell_color)
tb._cells[(i+1, j+1)]._text.set_color(text_color)
elif isinstance(value, pd.tslib.Timestamp):
tb.add_cell(i + 1, j + 1, width, height, text=val.strftime('%d-%b-%Y'), loc=loc, facecolor=cell_color)
tb._cells[(i+1, j+1)]._text.set_color(text_color)
else:
tb.add_cell(i + 1, j + 1, width, height, text=str(val), loc=loc, facecolor=cell_color)
tb._cells[(i+1, j+1)]._text.set_color(text_color)
if index_color is None:
index_color='black'
if index_fill_color is not None:
cell_color = index_fill_color
else:
cell_color = 'none'
# row labels
for i, label in enumerate(df.index):
tb.add_cell(i + 1, 0, width, height, text=label, loc=loc, edgecolor='none', facecolor=cell_color)
tb._cells[(i+1, 0)]._text.set_color(index_color)
if header_color is None:
header_color='black'
if header_fill_color is not None:
cell_color = header_fill_color
else:
cell_color = 'none'
# column labels
for j, label in enumerate(df.columns):
tb.add_cell(0, j + 1, width, height, text=label, loc=loc, edgecolor='none', facecolor=cell_color)
tb._cells[(i+1, 0)]._text.set_color(header_color)
# set font size
if fontsize is not None:
tb_cells = tb.properties()['child_artists']
for cell in tb_cells:
cell.set_fontsize(fontsize)
# add table to figure
ax.add_table(tb)
# set title
if title is not None:
if fontsize is not None:
ax.set_title(title, fontsize=fontsize)
else:
ax.set_title(title)
plt.tight_layout()
return fig
def shmoo_plotting(self):
''' pixel register shmoo plot '''
shmoopdf = PdfPages('shmoo.pdf')
shmoonp = np.array(self.shmoo_errors)
data = shmoonp.reshape(len(self.voltages),-1,order='F')
fig, ax = plt.subplots()
plt.title('Pixel registers errors')
ax.set_axis_off()
tb = Table(ax, bbox=[0,0,1,1])
ncols = len(self.bitfiles)
nrows = len(self.voltages)
width, height = 1.0 / ncols, 1.0 / nrows
# Add cells
for (i,j), val in np.ndenumerate(data):
color = ''
if val == 0: color = 'green'
if (val > 0 & val < 10): color = 'yellow'
if val > 10: color = 'red'
tb.add_cell(i, j, width, height, text=str(val),
loc='center', facecolor=color)
# Row Labels...
for i in range(len(self.voltages)):
tb.add_cell(i, -1, width, height, text=str(self.voltages[i])+'V', loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j in range(len(self.bitfiles)):
freq_label = self.bitfiles[j][-9:-7].translate(None, '_')
tb.add_cell(nrows+1, j, width, height/2, text=freq_label+' MHz', loc='center',
edgecolor='none', facecolor='none')
ax.add_table(tb)
shmoopdf.savefig()
''' global register shmoo plot '''
shmoo_glob_np = np.array(self.shmoo_global_errors)
data_g = shmoo_glob_np.reshape(len(self.voltages),-1,order='F')
fig_g, ax_g = plt.subplots()
ax_g.set_axis_off()
tb_g = Table(ax_g, bbox=[0,0,1,1])
plt.title('Global registers errors')
# Add cells
for (i,j), val_g in np.ndenumerate(data_g):
color = ''
if val_g == 0: color = 'green'
if val_g > 0: color = 'red'
tb_g.add_cell(i, j, width, height, text=str(val_g),
loc='center', facecolor=color)
# Row Labels...
for i in range(len(self.voltages)):
tb_g.add_cell(i, -1, width, height, text=str(self.voltages[i])+'V', loc='right',
edgecolor='none', facecolor='none')
# Column Labels...
for j in range(len(self.bitfiles)):
freq_label = self.bitfiles[j][-9:-7].translate(None, '_')
tb_g.add_cell(nrows+1, j, width, height/2, text=freq_label+' MHz', loc='center',
edgecolor='none', facecolor='none')
ax_g.add_table(tb_g)
shmoopdf.savefig()
shmoopdf.close()
def plot(self, experiment, **kwargs):
"""Plot a table"""
if not experiment:
raise util.CytoflowViewError("No experiment specified")
if not self.channel or self.channel not in experiment.data:
raise util.CytoflowViewError("Must set a channel")
if not (self.row_facet or self.column_facet):
raise util.CytoflowViewError("Must set at least one of row_facet "
"or column_facet")
if self.subrow_facet and not self.row_facet:
raise util.CytoflowViewError("Must set row_facet before using "
"subrow_facet")
if self.subcolumn_facet and not self.column_facet:
raise util.CytoflowViewError("Must set column_facet before using "
"subcolumn_facet")
if self.row_facet and self.row_facet not in experiment.conditions:
raise util.CytoflowViewError("Row facet {0} not in the experiment"
.format(self.row_facet))
if self.subrow_facet and self.subrow_facet not in experiment.conditions:
raise util.CytoflowViewError("Subrow facet {0} not in the experiment"
.format(self.subrow_facet))
if self.column_facet and self.column_facet not in experiment.conditions:
raise util.CytoflowViewError("Column facet {0} not in the experiment"
.format(self.column_facet))
if self.subcolumn_facet and self.subcolumn_facet not in experiment.conditions:
raise util.CytoflowViewError("Subcolumn facet {0} not in the experiment"
.format(self.subcolumn_facet))
if not self.function:
raise util.CytoflowViewError("Summary function isn't set")
row_groups = np.sort(pd.unique(experiment[self.row_facet])) \
if self.row_facet else [None]
subrow_groups = np.sort(pd.unique(experiment[self.subrow_facet])) \
if self.subrow_facet else [None]
col_groups = np.sort(pd.unique(experiment[self.column_facet])) \
if self.column_facet else [None]
subcol_groups = np.sort(pd.unique(experiment[self.subcolumn_facet])) \
if self.subcolumn_facet else [None]
if self.subset:
try:
data = experiment.query(self.subset).data.reset_index()
except:
raise util.CytoflowViewError("Subset string '{0}' isn't valid"
.format(self.subset))
if len(data.index) == 0:
raise util.CytoflowViewError("Subset string '{0}' returned no events"
.format(self.subset))
else:
data = experiment.data
group_vars = []
if self.row_facet: group_vars.append(self.row_facet)
if self.subrow_facet: group_vars.append(self.subrow_facet)
if self.column_facet: group_vars.append(self.column_facet)
if self.subcolumn_facet: group_vars.append(self.subcolumn_facet)
agg = data.groupby(by = group_vars)[self.channel].aggregate(self.function)
# agg is a multi-index series; we can get a particular value from it
# with get(idx1, idx2...)
row_offset = (self.column_facet != "") + (self.subcolumn_facet != "")
col_offset = (self.row_facet != "") + (self.subrow_facet != "")
num_cols = len(col_groups) * len(subcol_groups) + col_offset
fig = plt.figure()
ax = fig.add_subplot(111)
# hide the plot axes that matplotlib tries to make
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
for sp in ax.spines.itervalues():
sp.set_color('w')
sp.set_zorder(0)
loc = 'best'
bbox = None
t = Table(ax, loc, bbox, **kwargs)
width = [1.0 / num_cols] * num_cols
height = t._approx_text_height() * 1.8
# make the main table
for (ri, r) in enumerate(row_groups):
for (rri, rr) in enumerate(subrow_groups):
for (ci, c) in enumerate(col_groups):
for (cci, cc) in enumerate(subcol_groups):
row_idx = ri * len(subrow_groups) + rri + row_offset
col_idx = ci * len(subcol_groups) + cci + col_offset
agg_idx = [x for x in (r, rr, c, cc) if x is not None]
agg_idx = tuple(agg_idx)
if len(agg_idx) == 1:
agg_idx = agg_idx[0]
t.add_cell(row_idx,
col_idx,
width = width[col_idx],
height = height,
text = agg.get(agg_idx))
# row headers
if self.row_facet:
for (ri, r) in enumerate(row_groups):
row_idx = ri * len(subrow_groups) + row_offset
text = "{0} = {1}".format(self.row_facet, r)
t.add_cell(row_idx,
0,
width = width[0],
height = height,
text = text)
# subrow headers
if self.subrow_facet:
for (ri, r) in enumerate(row_groups):
for (rri, rr) in enumerate(subrow_groups):
row_idx = ri * len(subrow_groups) + rri + row_offset
text = "{0} = {1}".format(self.subrow_facet, rr)
t.add_cell(row_idx,
1,
width = width[1],
height = height,
text = text)
# column headers
if self.column_facet:
for (ci, c) in enumerate(col_groups):
col_idx = ci * len(subcol_groups) + col_offset
text = "{0} = {1}".format(self.column_facet, c)
t.add_cell(0,
col_idx,
width = width[col_idx],
height = height,
text = text)
# column headers
if self.subcolumn_facet:
for (ci, c) in enumerate(col_groups):
for (cci, cc) in enumerate(subcol_groups):
col_idx = ci * len(subcol_groups) + cci + col_offset
text = "{0} = {1}".format(self.subcolumn_facet, c)
t.add_cell(1,
col_idx,
width = width[col_idx],
height = height,
text = text)
ax.add_table(t)
def checkerboard_plot(ary,
cell_colors=('white', 'black'),
font_colors=('black', 'white'),
fmt='%.1f',
figsize=None,
row_labels=None,
col_labels=None,
fontsize=None):
"""
Plot a checkerboard table / heatmap via matplotlib.
Parameters
-----------
ary : array-like, shape = [n, m]
A 2D Nnumpy array.
cell_colors : tuple or list (default: ('white', 'black'))
Tuple or list containing the two colors of the
checkerboard pattern.
font_colors : tuple or list (default: ('black', 'white'))
Font colors corresponding to the cell colors.
figsize : tuple (default: (2.5, 2.5))
Height and width of the figure
fmt : str (default: '%.1f')
Python string formatter for cell values.
The default '%.1f' results in floats with 1 digit after
the decimal point. Use '%d' to show numbers as integers.
row_labels : list (default: None)
List of the row labels. Uses the array row
indices 0 to n by default.
col_labels : list (default: None)
List of the column labels. Uses the array column
indices 0 to m by default.
fontsize : int (default: None)
Specifies the font size of the checkerboard table.
Uses matplotlib's default if None.
Returns
-----------
fig : matplotlib Figure object.
"""
fig, ax = subplots(figsize=figsize)
ax.set_axis_off()
tb = Table(ax, bbox=[0, 0, 1, 1])
n_rows, n_cols = ary.shape
if row_labels is None:
row_labels = np.arange(n_rows)
if col_labels is None:
col_labels = np.arange(n_cols)
width, height = 1.0 / n_cols, 1.0 / n_rows
for (row_idx, col_idx), cell_val in np.ndenumerate(ary):
idx = (col_idx + row_idx) % 2
tb.add_cell(row_idx, col_idx, width, height,
text=fmt % cell_val,
loc='center',
facecolor=cell_colors[idx])
for row_idx, label in enumerate(row_labels):
tb.add_cell(row_idx, -1,
width, height,
text=label, loc='right',
edgecolor='none', facecolor='none')
for col_idx, label in enumerate(col_labels):
tb.add_cell(-1, col_idx,
width, height / 2.,
text=label, loc='center',
edgecolor='none', facecolor='none')
for (row_idx, col_idx), cell_val in np.ndenumerate(ary):
idx = (col_idx + row_idx) % 2
tb._cells[(row_idx, col_idx)]._text.set_color(font_colors[idx])
ax.add_table(tb)
tb.set_fontsize(fontsize)
return fig
def mytable(ax, csize=0.04,
cellText=None, cellColours=None,
cellLoc='right', colWidths=None,
rowLabels=None, rowColours=None, rowLoc='left',
colLabels=None, colColours=None, colLoc='center',
loc='bottom', bbox=None):
# Check we have some cellText
if cellText is None:
# assume just colours are needed
rows = len(cellColours)
cols = len(cellColours[0])
cellText = [[''] * rows] * cols
rows = len(cellText)
cols = len(cellText[0])
for row in cellText:
assert len(row) == cols
if cellColours is not None:
assert len(cellColours) == rows
for row in cellColours:
assert len(row) == cols
else:
cellColours = ['w' * cols] * rows
# Set colwidths if not given
if colWidths is None:
colWidths = [1.0/cols] * cols
# Check row and column labels
rowLabelWidth = 0
if rowLabels is None:
if rowColours is not None:
rowLabels = [''] * cols
rowLabelWidth = colWidths[0]
elif rowColours is None:
rowColours = 'w' * rows
if rowLabels is not None:
assert len(rowLabels) == rows
offset = 0
if colLabels is None:
if colColours is not None:
colLabels = [''] * rows
offset = 1
elif colColours is None:
colColours = 'w' * cols
offset = 1
if rowLabels is not None:
assert len(rowLabels) == rows
# Set up cell colours if not given
if cellColours is None:
cellColours = ['w' * cols] * rows
# Now create the table
table = Table(ax, loc, bbox)
height = csize
# Add the cells
for row in xrange(rows):
for col in xrange(cols):
table.add_cell(row+offset, col,
width=height, height=height,
text=cellText[row][col],
facecolor=cellColours[row][col],
loc=cellLoc)
ax.add_table(table)
return table
def run(self):
self.parent.clear_plots()
if self.data is None:
length, tMin, tMax, fMin, fMax, lMin, lMax, peakF, peakL, peakT = ('-',) * 10
else:
length = len(self.data)
tMin = format_time(self.extent.tMin, True)
tMax = format_time(self.extent.tMax, True)
fMin = format_precision(self.settings, freq=self.extent.fMin,
fancyUnits=True)
fMax = format_precision(self.settings, freq=self.extent.fMax,
fancyUnits=True)
lMin = format_precision(self.settings, level=self.extent.lMin,
fancyUnits=True)
lMax = format_precision(self.settings, level=self.extent.lMax,
fancyUnits=True)
peak = self.extent.get_peak_flt()
peakF = format_precision(self.settings, freq=peak[0],
fancyUnits=True)
peakL = format_precision(self.settings, level=peak[1],
fancyUnits=True)
peakT = format_time(peak[2], True)
text = [['Sweeps', '', length],
['Extent', '', ''],
['', 'Start', tMin],
['', 'End', tMax],
['', 'Min frequency', fMin],
['', 'Max frequency', fMax],
['', 'Min level', lMin],
['', 'Max level', lMax],
['Peak', '', ''],
['', 'Level', peakL],
['', 'Frequency', peakF],
['', 'Time', peakT],
]
table = Table(self.axes, loc='center')
table.set_gid('table')
rows = len(text)
cols = len(text[0])
fontProperties = FontProperties()
fontProperties.set_weight('semibold')
for row in xrange(rows):
for col in xrange(cols):
fp = fontProperties if col == 0 else None
table.add_cell(row, col,
text=text[row][col],
fontproperties=fp,
width=1.0 / cols, height=1.0 / rows)
if self.settings.grid:
colour = 'LightGray'
else:
colour = 'w'
set_table_colour(table, colour)
for i in range(2):
table.auto_set_column_width(i)
self.axes.add_table(table)
self.parent.redraw_plot()
self.parent.threadPlot = None
def make_tab_big(value_tab, col_tab, format_type = "cost", \
cmap = ["#4575b4", "#ffffbf", "#d73027"], figsize = (10,10)):
"""
"""
measures = list(value_tab.columns)
# User-defined colormap from blue to red, going through a darker colour
cm2 = mcol.LinearSegmentedColormap.from_list("new", \
cmap)
cnorm = mcol.Normalize(vmin = 0, vmax = 1)
cpick = cm.ScalarMappable(norm = cnorm, cmap = cm2)
fig, ax = plt.subplots()
ax.set_axis_off()
# Create the table (so that you can avoid colouring the ranks manually)
tb = Table(ax, bbox=[0,0,1,1])
nrows, ncols = value_tab.shape
width, height = 1.0 / (ncols+1), 1.0 / (nrows+1)
for (i, j), val in np.ndenumerate(value_tab):
colour = cpick.to_rgba(col_tab.ix[i, j])
alpha = 0.7
colour = (colour[0], colour[1], colour[2], alpha)
text_colour = "White" #cpick.to_rgba(1 - col_tab.ix[i, j])
# Find the best text colour.
# If green is greater than 190/255 then use black.
# unless blue is greater than 150/255.
#[a < 0.9 for (r, g, b, a) in colour]
if (colour[1] > 190./255) & (colour[2] > 150./255):
text_colour = "Black"
if np.isnan(val):
colour = "White"
text_colour = "Black"
#if measures[j] == "Livestock culled":
# format_type = "culled"
#else:
# format_type = "cost"
# Format value string
formatted_val = formatval(val, measures[j], format_type)
# Add cell to the table
tb.add_cell(i, j+1, width, height, text = formatted_val,
loc = 'right', facecolor = colour, edgecolor = 'none')
# Set the font colour
tb._cells[(i, j+1)]._text.set_color(text_colour)
# Columns
for j, label in enumerate(measures):
tb.add_cell(-1, j+1, width, height, text=label, loc='center',
edgecolor='none', facecolor='none')
tb._cells[(-1, j+1)]._text.set_weight('bold')
# 'Control' and 'Model' labels
tb.add_cell(-1, 0, width, height, text='Model', loc='center',
edgecolor='none', facecolor='none')
tb._cells[(-1, 0)]._text.set_weight('bold')
tb.add_cell(-1, -1, width, height, text=' Control', loc='center',
edgecolor='none', facecolor='none')
tb._cells[(-1, -1)]._text.set_weight('bold')
# Rows
for i, label in enumerate(value_tab.index.labels[1]):
tb.add_cell(i, 0, width, height, \
text = value_tab.index.levels[1][label], \
loc='center', edgecolor='none', facecolor='none')
# Add table to the current axes
ax.add_table(tb)
# Bigger rows
controls = [
"Infected\npremises\nculling\n(IP)",
"Dangerous\ncontacts\nculling\n(DC)",
"Ring culling\nat 3km\n(RC)",
"",
"",
"",
""]
incr = float(len(controls))
for k, label in enumerate(controls):
ax.text(-0.05, 1 - (k+1)/incr + 1./15., label, fontsize = 10, \
horizontalalignment = 'center', verticalalignment = 'center')
if k < 4:
pass
else:
ax.axhline(k/incr, -0.15, 1,c = "Black", clip_on = False)
ax.axhline(2./incr, -0.15, 1,c = "Black", clip_on = False)
ax.axhline(0./incr, -0.15, 1,c = "Black", clip_on = False)
ax.axhline(1, -0.15, 1, c = "Black", clip_on = False)
ax.axhline(3./incr, -0.02, 1,c = "Black", clip_on = False)
ax.axhline(1./incr, -0.02, 1,c = "Black", clip_on = False)
ax.text(-0.1, 1 - 4./incr, "Vaccinate\n at 3km", \
fontsize = 10, horizontalalignment = 'center', \
verticalalignment = 'center')
ax.text(0.01, 1 - 4./incr + 1./15., "to live\n(V3L)", \
fontsize = 10, horizontalalignment = 'center', \
verticalalignment = 'center')
ax.text(0.01, 1 - 5./incr + 1./15., "to kill\n(V3K)", \
fontsize = 10, horizontalalignment = 'center', \
verticalalignment = 'center')
ax.text(-0.1, 1 - 6./incr, "Vaccinate\n at 10km", \
fontsize = 10, horizontalalignment = 'center', \
verticalalignment = 'center')
ax.text(0.01, 1 - 6./incr + 1./15., "to live\n(V10L)", \
fontsize = 10, horizontalalignment = 'center', \
verticalalignment = 'center')
ax.text(0.01, 1 - 7./incr + 1./15., "to kill\n(V10K)", \
fontsize = 10, horizontalalignment = 'center', \
verticalalignment = 'center')
# Add the extra lines
#ax.axhline(k/incr, -0.15, 1,c = "Black", clip_on = False)
#ax.text(-0.05, 1 + 1./70 , 'Control', fontsize = 12, fontweight = 'bold',\
# horizontalalignment = 'center', verticalalignment = 'center')
fig.set_size_inches(figsize)
return fig, ax
