def plots_from_samples(samples, x_attribute, ylabel="Number of txs", xlabel=None, log_axis=None, version=0.15,
comparative=False, save_fig=False, legend=None, legend_loc=1, font_size=20):
"""
Generates plots from utxo/tx samples extracted from utxo_dump.
:param samples: Samples to be printed (from get_samples)
:type: list
:param x_attribute: Attribute to plot (must be a key in the dictionary of the dumped data).
:type x_attribute: str or list
:param ylabel: Label for the y axis of the chart
:type ylabel: str or list
:param xlabel: Label on the x axis
:type xlabel: str
:param log_axis: Determines which axis are plotted using (accepted values are False, "x", "y" or "xy").
logarithmic scale
:type log_axis: str or list
:param version: Bitcoin core version, used to decide the folder in which to store the data.
:type version: str or list
:param comparative: Whether we are running a comparative analysis.
:type comparative: bool
:param save_fig: Figure's filename or False (to show the interactive plot)
:type save_fig: str or list
:param legend: List of strings with legend entries or None (if no legend is needed)
:type legend: str list
:param legend_loc: Indicates the location of the legend (if present)
:type legend_loc: int
:param font_size: Title, xlabel and ylabel font size
:type font_size: int
:return: None
:rtype: None
"""
if not (isinstance(x_attribute, list) or isinstance(x_attribute, np.ndarray)):
x_attribute = [x_attribute]
# In comparative analysis samples are passed as list of lists of samples.
if not comparative:
samples = [samples]
title = ""
if not xlabel:
xlabel = x_attribute
xs, ys = [], []
for i in range(len(x_attribute)):
for s in samples:
[xc, yc] = get_cdf(s, normalize=True)
xs.append(xc)
ys.append(yc)
if isinstance(log_axis, list) and isinstance(save_fig, list):
# If both the normal axis and the logx axis charts want to be displayed, we can take advantage of the same
# parsing to speed up the process.
for lx, sf in zip(log_axis, save_fig):
sf = str(version) + '/' + sf
plot_distribution(xs, ys, title, xlabel, ylabel, lx, sf, legend, legend_loc, font_size)
else:
# Otherwise we just print one chart.
save_fig = str(version) + '/' + save_fig
plot_distribution(xs, ys, title, xlabel, ylabel, log_axis, save_fig, legend, legend_loc, font_size)
def plot_from_file(x_attribute, y="tx", xlabel=False, log_axis=False, save_fig=False, legend=None,
legend_loc=1, font_size=20):
"""
Generates plots from utxo/tx data extracted from utxo_dump.
:param x_attribute: Attribute to plot (must be a key in the dictionary of the dumped data).
:type x_attribute: str
:param y: Either "tx" or "utxo"
:type y: str
:param xlabel: Label on the x axis
:type xlabel: str
:param log_axis: Determines which axis are plotted using (accepted values are False, "x", "y" or "xy").
logarithmic scale
:type log_axis: str
:param save_fig: Figure's filename or False (to show the interactive plot)
:type save_fig: str
:param legend: List of strings with legend entries or None (if no legend is needed)
:type legend: str list
:param legend_loc: Indicates the location of the legend (if present)
:type legend_loc: int
:param font_size: Title, xlabel and ylabel font size
:type font_size: int
:return: None
:rtype: None
"""
if y == "tx":
fin = open(CFG.data_path + 'parsed_txs.txt', 'r')
ylabel = "Number of tx."
elif y == "utxo":
fin = open(CFG.data_path + 'parsed_utxos.txt', 'r')
ylabel = "Number of UTXOs"
else:
raise ValueError('Unrecognized y value')
samples = []
for line in fin:
data = loads(line[:-1])
samples.append(data[x_attribute])
fin.close()
[xs, ys] = get_cdf(samples, normalize=True)
title = ""
if not xlabel:
xlabel = x_attribute
plot_distribution(xs, ys, title, xlabel, ylabel, log_axis, save_fig, legend, legend_loc, font_size)
def plot_dict_from_file(y="dust", disp_np=True, fin_name=None, percentage=False, xlabel=None, log_axis=None,
version=0.15, save_fig=False, legend=None, legend_loc=1, font_size=20):
"""
Loads data from a given file (stored in a dictionary) and plots it in a chart. dust.json is a perfect example of
the loaded format.
:param y: Either "tx" or "utxo"
:type y: str
disp_np: Whether to display non_profitable in the same chart as dust or not.
:type disp_np: bool
:param fin_name: Name of the file containing the data to be plotted.
:type fin_name: str or list
:param percentage: Whether the data is plot as percentage or not.
:type percentage: bool
:param xlabel: Label on the x axis
:type xlabel: str
:param log_axis: Determines which axis are plotted using (accepted values are False, "x", "y" or "xy").
logarithmic scale
:type log_axis: str
:param version: Bitcoin core version, used to decide the folder in which to store the data.
:type version: float
:param save_fig: Figure's filename or False (to show the interactive plot)
:type save_fig: str
:param legend: List of strings with legend entries or None (if no legend is needed)
:type legend: str list
:param legend_loc: Indicates the location of the legend (if present)
:type legend_loc: int
:param font_size: Title, xlabel and ylabel font size
:type font_size: int
:return: None
:rtype: None
"""
if not isinstance(fin_name, list):
fin_name = [fin_name]
data = []
for f in fin_name:
fin = open(CFG.data_path + f, 'r')
data.append(loads(fin.read()))
fin.close()
# Decides the type of chart to be plot.
if y == "dust":
data_type = ["dust_utxos"]
if disp_np:
data_type.append("np_utxos")
if not percentage:
ylabel = "Number of UTXOs"
else:
ylabel = "Percentage of UTXOs"
total = "total_utxos"
elif y == "value":
data_type = ["dust_value"]
if disp_np:
data_type.append("np_value")
if not percentage:
ylabel = "Value (Satoshi)"
else:
ylabel = "Percentage of total value"
total = "total_value"
elif y == "data_len":
data_type = ["dust_data_len"]
if disp_np:
data_type.append("np_data_len")
if not percentage:
ylabel = "UTXOs' size (bytes)"
else:
ylabel = "Percentage of total UTXOs' size"
total = "total_data_len"
else:
raise ValueError('Unrecognized y value')
# Adds the folder in which the data will be stored
save_fig = str(version) + '/' + save_fig
xs = []
ys = []
# Sort the data
for i in data_type:
for d in data:
xs.append(sorted(d[i].keys(), key=int))
ys.append(sorted(d[i].values(), key=int))
title = ""
if not xlabel:
xlabel = "fee_per_byte"
# If percentage is set, a chart with y axis as a percentage (dividing every single y value by the
# corresponding total value) is created.
if percentage:
# ToDo: Check this!!
for i in range(len(ys)):
d = data[i] if len(data) > 1 else data[0]
if isinstance(ys[i], list):
ys[i] = [j / float(d[total]) * 100 for j in ys[i]]
elif isinstance(ys[i], int):
ys[i] = ys[i] / float(data[i][total]) * 100
# And finally plots the chart.
plot_distribution(xs, ys, title, xlabel, ylabel, log_axis, save_fig, legend, legend_loc, font_size)
def plot_from_file_dict(x_attribute,
y="dust",
fin_name=None,
percentage=False,
xlabel=False,
log_axis=False,
version=0.15,
save_fig=False,
legend=None,
legend_loc=1,
font_size=20):
"""
Generate plots from files in which the loaded data is a dictionary, such as dust.json.
:param x_attribute: Attribute to plot (must be a key in the dictionary of the dumped data).
:type x_attribute: str
:param y: Either "tx" or "utxo"
:type y: str
:param fin_name: Name of the file containing the data to be plotted.
:type fin_name: str
:param percentage: Whether the data is plot as percentage or not.
:type percentage: bool
:param xlabel: Label on the x axis
:type xlabel: str
:param log_axis: Determines which axis are plotted using (accepted values are False, "x", "y" or "xy").
logarithmic scale
:type log_axis: str
:param version: Bitcoin core version, used to decide the folder in which to store the data.
:type version: float
:param save_fig: Figure's filename or False (to show the interactive plot)
:type save_fig: str
:param legend: List of strings with legend entries or None (if no legend is needed)
:type legend: str list
:param legend_loc: Indicates the location of the legend (if present)
:type legend_loc: int
:param font_size: Title, xlabel and ylabel font size
:type font_size: int
:return: None
:rtype: None
"""
fin = open(CFG.data_path + fin_name, 'r')
data = loads(fin.read())
# Decides the type of chart to be plot.
if y == "dust":
data_type = ["dust_utxos", "lm_utxos"]
if not percentage:
ylabel = "Number of utxos"
else:
ylabel = "Percentage of utxos"
total = "total_utxos"
elif y == "value":
data_type = ["dust_value", "lm_value"]
if not percentage:
ylabel = "Value (Satoshi)"
else:
ylabel = "Percentage of total value"
total = "total_value"
elif y == "data_len":
data_type = ["dust_data_len", "lm_data_len"]
if not percentage:
ylabel = "Utxos' size (bytes)"
else:
ylabel = "Percentage of total utxos' size"
total = "total_data_len"
else:
raise ValueError('Unrecognized y value')
# Adds the folder in which the data will be stored
save_fig = str(version) + '/' + save_fig
xs = []
ys = []
# Sort the data
for i in data_type:
xs.append(sorted(data[i].keys(), key=int))
ys.append(sorted(data[i].values(), key=int))
title = ""
if not xlabel:
xlabel = x_attribute
# If percentage is set, a chart with y axis as a percentage (dividing every single y value by the
# corresponding total value) is created.
if percentage:
for i in range(len(ys)):
if isinstance(ys[i], list):
ys[i] = [j / float(data[total]) * 100 for j in ys[i]]
elif isinstance(ys[i], int):
ys[i] = ys[i] / float(data[total]) * 100
# And finally plots the chart.
plot_distribution(xs, ys, title, xlabel, ylabel, log_axis, save_fig,
legend, legend_loc, font_size)
def plots_from_file(x_attribute,
y=["tx"],
xlabel=False,
log_axis=False,
version=[0.15],
save_fig=False,
legend=None,
legend_loc=1,
font_size=20,
filtr=[lambda x: True]):
"""
Generates plots from utxo/tx data extracted from utxo_dump.
:param x_attribute: Attribute to plot (must be a key in the dictionary of the dumped data).
:type x_attribute: str or list
:param y: Either "tx" or "utxo"
:type y: str or list
:param xlabel: Label on the x axis
:type xlabel: str
:param log_axis: Determines which axis are plotted using (accepted values are False, "x", "y" or "xy").
logarithmic scale
:type log_axis: str
:param version: Bitcoin core version, used to decide the folder in which to store the data.
:type version: float or list
:param save_fig: Figure's filename or False (to show the interactive plot)
:type save_fig: str
:param legend: List of strings with legend entries or None (if no legend is needed)
:type legend: str list
:param legend_loc: Indicates the location of the legend (if present)
:type legend_loc: int
:param font_size: Title, xlabel and ylabel font size
:type font_size: int
:param filtr: Function to filter samples (returns a boolean value for a given sample)
:type filtr: function or list of functions
:return: None
:rtype: None
"""
if not (isinstance(x_attribute, list)
or isinstance(x_attribute, np.ndarray)):
x_attribute = [x_attribute]
if not (isinstance(y, list) or isinstance(y, np.ndarray)):
y = [y]
if not (isinstance(version, list) or isinstance(version, np.ndarray)):
version = [version]
if not (isinstance(filtr, list) or isinstance(filtr, np.ndarray)):
filtr = [filtr]
assert len(x_attribute) == len(y) == len(version) == len(filtr), \
"There is a mismatch on the list length of some of the parameters"
if y[0] == "tx":
ylabel = "Number of tx."
elif y[0] == "utxo":
ylabel = "Number of UTXOs"
title = ""
if not xlabel:
xlabel = x_attribute
xs, ys = [], []
for i in range(len(x_attribute)):
samples = get_samples(x_attribute[i],
y=y[i],
version=version[i],
filtr=filtr[i])
[xc, yc] = get_cdf(samples, normalize=True)
xs.append(xc)
ys.append(yc)
# Adds the folder in which the data will be stored (if multiple versions are involved, store it
# in the first one folder)
save_fig = str(version[0]) + '/' + save_fig
plot_distribution(xs, ys, title, xlabel, ylabel, log_axis, save_fig,
legend, legend_loc, font_size)