Python results_prompt示例

示例#1

import matplotlib.pyplot as plt
import re
import tools

from tools import get_array, dags, defines, names

path = tools.results_prompt("copy_compdecomp")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=24)

# Setup
fig = plt.figure(dpi=100, figsize=(6, 6))
ax = fig.add_subplot(111)

# Do stuff
for i in range(len(dags)):
    data = dags[i]
    label_index = 0
    time = get_array(data, "edits")
    num_voxels = get_array(data, "num voxels")

示例#2

文件： plot_fig_copy_edits_voxels.py 项目： zimokernel/HashDAG

import matplotlib.pyplot as plt
import re
import tools

from tools import get_array, dags, defines, names, indices

path = tools.results_prompt("copy_edit_voxels")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=24)

# Setup
fig = plt.figure(dpi=100, figsize=(6, 6))
ax = fig.add_subplot(111)

# Do stuff
for i in range(len(dags)):
    data = dags[i]
    label_index = 0
    time = get_array(data, "copied voxels")
    num_voxels = get_array(data, "num voxels")

示例#3

import matplotlib.pyplot as plt
import re
import tools

from tools import get_array, dags, defines, names

path = tools.results_prompt("edits")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=24)

# Setup
fig = plt.figure(dpi=100, figsize=(6, 10))
ax = fig.add_subplot(111)

# Do stuff
for i in range(len(dags)):
    data = dags[i]
    label_index = 0
    time = get_array(data, "edits")
    num_voxels = get_array(data, "num voxels")

示例#4

文件： plot_fig_pagesize.py 项目： zimokernel/HashDAG

import matplotlib.pyplot as plt
import re
import tools

from tools import get_array, dags, defines, names

path = tools.results_prompt("page_size")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=27)

# Setup
fig = plt.figure(dpi=100, figsize=(6, 10))
ax = fig.add_subplot(111)

# Do stuff
for i in range(len(dags)):
    data = dags[i]
    label_index = 0
    time = get_array(data, "edits")
    num_voxels = get_array(data, "num voxels")

示例#5

from tools import get_array, dags, results_prompt, defines

results_prompt("bucket_count_memory_overhead")

for i in range(len(dags)):
    data = dags[i]
    virtual_size = get_array(data, "virtual_size")
    allocated_size = get_array(data, "allocated_size")
    print("buckets bits: {}; used: {}; allocated: {}; wasted: {}".format(
        defines[i]["BUCKETS_BITS_FOR_LOW_LEVELS"], virtual_size[0],
        allocated_size[0], allocated_size[0] - virtual_size[0]))

示例#6

文件： print_page_size_memory_overhead.py 项目： zimokernel/HashDAG

from tools import get_array, dags, results_prompt, defines

results_prompt("page_size_memory_overhead")

for i in range(len(dags)):
    data = dags[i]
    virtual_size = get_array(data, "virtual_size")
    allocated_size = get_array(data, "allocated_size")
    print("page size: {}; used: {}; allocated: {}; wasted: {}".format(
        defines[i]["PAGE_SIZE"], virtual_size[0], allocated_size[0],
        allocated_size[0] - virtual_size[0]))

示例#7

import numpy as np

from tools import get_array, dags, results_prompt, get_custom_array
import matplotlib.pyplot as plt

path = results_prompt("color_memory")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=24)

# Setup
fig = plt.figure(dpi=120, figsize=(10, 6))
ax = fig.add_subplot(111)

# Plot
data = dags[0]

plt.xlabel("Cumulative #edited voxels")
plt.ylabel("Memory usage (MB)")

kwargs = {"marker": "", "markersize": 5}

示例#8

import numpy as np

import tools
from tools import get_array, dags, results_prompt, get_custom_array
import matplotlib.pyplot as plt
#import seaborn as sns

path = results_prompt("memory")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=24)

# Setup
fig = plt.figure(dpi=120, figsize=(10, 6))
ax = fig.add_subplot(111)

# Plot
data = dags[0]

plt.xlabel("Cumulative #edited voxels")
plt.ylabel("Memory usage (MB)")

示例#9

文件： plot_fig_bucketcount.py 项目： zimokernel/HashDAG

import matplotlib.pyplot as plt
import re
import tools

from tools import get_array, dags, defines, names

path = tools.results_prompt("bucket_count")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=27)

# Setup
fig = plt.figure(dpi=100, figsize=(6, 10))
ax = fig.add_subplot(111)

# Do stuff
for i in range(len(dags)):
    data = dags[i]
    label_index = 0
    time = get_array(data, "edits")
    num_voxels = get_array(data, "num voxels")

示例#10

文件： plot_fig_copy_edits.py 项目： zimokernel/HashDAG

import matplotlib.pyplot as plt
import re
import tools

from tools import get_array, dags, defines, names

path = tools.results_prompt("copy_edits")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=24)

# Setup
fig = plt.figure(dpi=100, figsize=(6, 6))
ax = fig.add_subplot(111)

# Do stuff
for i in range(len(dags)):
    data = dags[i]
    label_index = 0
    time = get_array(data, "edits")
    num_voxels = get_array(data, "num voxels")

示例#11

文件： plot_fig_rt.py 项目： zimokernel/HashDAG

import matplotlib.pyplot as plt
import numpy as np
import tools
from tools import get_array, dags, defines

path = tools.results_prompt("rt")

# Styling
plt.style.use("seaborn")

#plt.rc("font", family="serif", size=56)
#plt.rc("axes", labelsize=18)
#plt.rc("legend", fontsize=12)

plt.rc("font", family="serif", size=14)
plt.rc("axes", labelsize=32)
plt.rc("xtick", labelsize=20)
plt.rc("ytick", labelsize=20)
plt.rc("legend", fontsize=22)

# Setup
fig = plt.figure(dpi=120, figsize=(10, 8))
ax = fig.add_subplot(111)

# Labels
labels_geo = ["Geometry (HashDAG)", "Geometry (original)"]
labels_col = ["Colors (HashDAG)", "Colors (original)"]

times = [None, None]

# Do stuff