kopia lustrzana https://github.com/sepandhaghighi/samila
update : main modules ins genimage and functions file updated.
Sadra Sabouri
rodzic
dc6ce73cd9
commit
90f5d6ab36
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@ -1,7 +1,13 @@
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# -*- coding: utf-8 -*-
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"""Samila functions."""
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from typing import Callable, Tuple, Dict, Generator, List
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from typing import Any, Union, Iterable
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import sys
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import matplotlib.axes
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import matplotlib.axes._subplots
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import matplotlib.colors
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import matplotlib.figure
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import matplotlib.pyplot
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import requests
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import io
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import os
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@ -11,11 +17,12 @@ import random
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import matplotlib
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from PIL import Image
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from functools import wraps
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from .params import Projection, GenerateMode, Marker, Gateway
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from .params import SAMILA_VERSION
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from .params import DEFAULT_MARKER, DEFAULT_START, DEFAULT_STOP, DEFAULT_STEP, DEFAULT_COLOR, DEFAULT_IMAGE_SIZE, DEFAULT_DEPTH
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from .params import DEFAULT_CMAP_NAME, DEFAULT_CMAP_RANGE, DEFAULT_ROTATION, DEFAULT_GENERATE_MODE
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from .params import DEFAULT_BACKGROUND_COLOR, DEFAULT_SPOT_SIZE, DEFAULT_PROJECTION, DEFAULT_ALPHA, DEFAULT_LINEWIDTH
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from .params import Projection, GenerateMode, Marker, VALID_COLORS, HEX_COLOR_PATTERN, NFT_STORAGE_API, OVERVIEW
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from .params import VALID_COLORS, HEX_COLOR_PATTERN, NFT_STORAGE_API, OVERVIEW
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from .params import DATA_TYPE_ERROR, DATA_FORMAT_ERROR, CONFIG_TYPE_ERROR, CONFIG_FORMAT_ERROR, PLOT_DATA_ERROR, CONFIG_NO_STR_FUNCTION_ERROR
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from .params import NO_FIG_ERROR_MESSAGE, FIG_SAVE_SUCCESS_MESSAGE, NFT_STORAGE_SUCCESS_MESSAGE, SAVE_NO_DATA_ERROR
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from .params import INVALID_COLOR_TYPE_ERROR, COLOR_SIZE_ERROR
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@ -27,37 +34,29 @@ from .errors import samilaDataError, samilaPlotError, samilaConfigError
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from warnings import warn
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def print_line(char="*", number=30):
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def print_line(char: str = "*", number: int = 30) -> None:
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"""
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Print line of chars.
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:param char: input character
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:type char: str
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:param number: number of characters
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:type number: int
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:return: None
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"""
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print(char * number)
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def deprecated(func):
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def deprecated(func: Callable) -> Callable:
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"""
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Decorate for deprecated functions.
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:param func: function to be deprecated
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:type func: function
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:return: deprecated function
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"""
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@wraps(func)
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def inner_func(*args, **kwargs):
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def inner_func(*args: Tuple, **kwargs: Dict) -> Callable:
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"""
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Inner function.
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:param args: arguments
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:type args: tuple
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:param kwargs: keyword arguments
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:type kwargs: dict
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:return: modified result of function
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"""
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warn(DEPRECATION_WARNING.format(func.__name__),
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category=DeprecationWarning,
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@ -66,12 +65,8 @@ def deprecated(func):
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return inner_func
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def random_equation_gen():
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"""
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Generate random equation.
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:return: equation as str
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"""
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def random_equation_gen() -> str:
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"""Generate random equation."""
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num_elements = random.randint(
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RANDOM_EQUATION_MIN_COMPLEXITY,
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RANDOM_EQUATION_MAX_COMPLEXITY)
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@ -94,42 +89,31 @@ def random_equation_gen():
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return result
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def random_hex_color_gen():
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"""
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Generate random hex color code.
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:return: color code as str
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"""
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def random_hex_color_gen() -> str:
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"""Generate random hex color code."""
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random_color = "#%06x" % random.randint(0, 0xFFFFFF)
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return random_color
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def float_range(start, stop, step):
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def float_range(start: float, stop: float, step: float) -> Generator[float, None, None]:
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"""
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Generate float range.
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:param start: start point
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:type start: float
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:param stop: stop point
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:type step: float
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:param step: step
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:type step: float
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:return: yield result
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:param step: step size
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"""
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while start < stop:
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yield float(start)
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start += step
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def distance_calc(s1, s2):
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def distance_calc(s1: str, s2: str) -> int:
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"""
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Calculate Levenshtein distance between two words.
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:param s1: first string
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:type s1 : str
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:param s2: second string
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:type s2 : str
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:return: distance between two string
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References :
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1- https://stackoverflow.com/questions/2460177/edit-distance-in-python
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@ -151,13 +135,11 @@ def distance_calc(s1, s2):
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return distances[-1]
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def is_valid_color(color):
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def is_valid_color(color: Any) -> bool:
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"""
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Check that input color format is valid or not.
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:param color: given color
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:type color: any format
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:return: result as bool
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"""
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if color is None:
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return True
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@ -168,13 +150,11 @@ def is_valid_color(color):
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return False
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def color_complement(color):
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def color_complement(color: str) -> str:
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"""
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Calculate complement color.
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:param color: given color (hex format)
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:type color: str
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:return: complement color (hex format) as str
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"""
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color = color[1:]
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color = int(color, 16)
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@ -183,15 +163,12 @@ def color_complement(color):
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return comp_color
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def filter_color(color, bgcolor):
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def filter_color(color: Any, bgcolor: Any) -> Tuple[str, str]:
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"""
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Filter given color and bgcolor.
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:param color: given color
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:type color: any format
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:param bgcolor: given background color
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:type bgcolor: any format
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:return: filtered version of color and bgcolor
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"""
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color = select_color(color)
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bgcolor = select_color(bgcolor)
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@ -207,15 +184,12 @@ def filter_color(color, bgcolor):
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return color, bgcolor
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def get_cmap(name=DEFAULT_CMAP_NAME, lut=256):
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def get_cmap(name: str = DEFAULT_CMAP_NAME, lut: int = 256) -> matplotlib.colors.Colormap:
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"""
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Get colormap.
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:param name: colormap name
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:type name: str
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:param lut: look up table for colormap
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:type lut: int
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:return: desired colormap
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"""
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try:
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return matplotlib.colormaps.get_cmap(name)
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@ -223,13 +197,11 @@ def get_cmap(name=DEFAULT_CMAP_NAME, lut=256):
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return matplotlib.cm.get_cmap(name, lut)
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def filter_cmap(cmap):
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def filter_cmap(cmap: Union[str, matplotlib.colors.Colormap, List[str]]) -> matplotlib.colors.ListedColormap:
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"""
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Filter given cmap.
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:param cmap: color map
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:type cmap: matplotlib.colors.Colormap or list of colors
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:return: filtered version of cmap
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"""
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if isinstance(cmap, str):
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cmap = get_cmap(cmap, 256)
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@ -246,13 +218,11 @@ def filter_cmap(cmap):
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return None
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def select_color(color):
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def select_color(color: Union[str, Any]) -> str:
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"""
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Select color and return it.
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:param color: given color
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:type color: any format
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:return: color
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"""
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if isinstance(color, str):
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if color.upper() == "TRANSPARENT":
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@ -279,17 +249,14 @@ def select_color(color):
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raise samilaPlotError(INVALID_COLOR_TYPE_ERROR)
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def set_background(bgcolor, fig, ax):
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def set_background(bgcolor: Any, fig: matplotlib.figure.Figure, ax: matplotlib.axes._subplots.AxesSubplot) -> None:
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"""
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Set background for figure and axis.
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:param bgcolor: given background color
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:type bgcolor: any format
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:param fig: figure
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:type fig: matplotlib.figure.Figure
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:param ax: axis
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:type ax: matplotlib.axes._subplots.AxesSubplot
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:return: None
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"""
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if bgcolor == "TRANSPARENT":
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ax.patch.set_visible(False)
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@ -300,13 +267,11 @@ def set_background(bgcolor, fig, ax):
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return
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def filter_projection(projection):
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def filter_projection(projection: Projection) -> str:
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"""
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Filter given projection.
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:param projection: given projection
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:type projection: Projection enum
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:return: filtered version of projection
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"""
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if isinstance(projection, Projection):
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projection_value = projection.value
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@ -319,13 +284,11 @@ def filter_projection(projection):
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return None
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def filter_generate_mode(generate_mode):
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def filter_generate_mode(generate_mode: GenerateMode) -> str:
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"""
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Filter given generate-mode.
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:param generate_mode: given generate-mode
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:type generate_mode: GenerateMode enum
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:return: filtered version of generate-mode
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"""
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if isinstance(generate_mode, GenerateMode):
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generate_mode_value = generate_mode.value
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@ -338,13 +301,11 @@ def filter_generate_mode(generate_mode):
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return None
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def filter_marker(marker):
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def filter_marker(marker: Marker) -> str:
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"""
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Filter given marker.
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:param marker: given marker
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:type marker: Marker enum
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:return: filtered version of marker
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"""
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if isinstance(marker, Marker):
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marker_value = marker.value
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@ -357,26 +318,22 @@ def filter_marker(marker):
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return None
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def filter_float(value):
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def filter_float(value: float) -> Union[float, int, None]:
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"""
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Filter given float value.
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:param value: given value
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:type value: float
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:return: filtered version of value
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"""
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if isinstance(value, (float, int)):
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return value
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return None
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def filter_size(size):
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def filter_size(size: Tuple[float, float]) -> Tuple[float, float]:
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"""
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Filter given image size.
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:param value: given size
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:type value: tuple of float
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:return: filtered version of size
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:param size: given size
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"""
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if isinstance(size, tuple):
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if not any(map(lambda x: x != filter_float(x), size)):
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@ -384,17 +341,16 @@ def filter_size(size):
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return None
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def rotate(fig, ax, rotation):
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def rotate(
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fig: matplotlib.figure.Figure,
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ax: matplotlib.axes.Axes,
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rotation: float) -> matplotlib.axes.Axes:
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"""
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Rotate the given figure and return axis.
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:param fig: figure containing the image
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:type fig: Figure
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:param ax: axis on which rotated image is ploted
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:type ax: Axis
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:param rotation: desired rotation (in degrees)
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:type rotation: float
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:return: axis containing rotated image
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"""
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if rotation != DEFAULT_ROTATION:
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buf = io.BytesIO()
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@ -409,43 +365,31 @@ def rotate(fig, ax, rotation):
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def plot_params_filter(
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g,
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color=None,
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bgcolor=None,
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cmap=None,
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spot_size=None,
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size=None,
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projection=None,
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marker=None,
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alpha=None,
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linewidth=None,
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rotation=None):
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g: "GenerativeImage",
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color: str = None,
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bgcolor: str = None,
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cmap: Union[matplotlib.colors.Colormap, List] = None,
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spot_size: float = None,
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size: Tuple[float, float] = None,
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projection: str = None,
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marker: str = None,
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alpha: float = None,
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linewidth: float = None,
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rotation: float = None) -> None:
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"""
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Filter plot method parameters.
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:param g: generative image instance
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:type g: GenerativeImage
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:param color: point colors
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:type color: str
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:param bgcolor: background color
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:type bgcolor: str
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:param cmap: color map
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:type cmap: matplotlib.colors.Colormap or list of colors
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:param spot_size: point spot size
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:type spot_size: float
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:param size: figure size
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:type size: tuple
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:param projection: projection type
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:type projection: str
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:param marker: marker type
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:type marker: str
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:param alpha: point transparency
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:type alpha: float
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:param linewidth: width of line
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:type linewidth: float
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:param rotation: desired rotation (in degrees)
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:type rotation: float
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:return: None
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"""
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if g.data1 is None:
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raise samilaPlotError(PLOT_DATA_ERROR.format(1))
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@ -489,28 +433,21 @@ def plot_params_filter(
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def generate_params_filter(
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g,
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seed=None,
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start=None,
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step=None,
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stop=None,
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mode=None):
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g: "GenerativeImage",
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seed: int =None,
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start: float = None,
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step: float = None,
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stop: float = None,
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mode: GenerateMode = None) -> None:
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"""
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Filter generate method parameters.
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:param g: generative image instance
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:type g: GenerativeImage
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:param seed: random seed
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:type seed: int
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:param start: range start point
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:type start: float
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:param step: range step size
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:type step: float
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:param stop: range stop point
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:type stop: float
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:param mode: generate mode
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:type mode: GenerateMode enum
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:return: None
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"""
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start, step, stop = map(filter_float, [start, step, stop])
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generate_mode = filter_generate_mode(mode)
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@ -529,30 +466,24 @@ def generate_params_filter(
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g.seed, g.start, g.step, g.stop, g.generate_mode = seed, start, step, stop, generate_mode
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def save_params_filter(g, depth=None):
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def save_params_filter(g: "GenerativeImage", depth: float = None) -> None:
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"""
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Filter save_image method parameters.
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:param depth: depth of image
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:type depth: float
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:return: None
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"""
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if depth is None:
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depth = g.depth
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g.depth = depth
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def _GI_initializer(g, function1, function2):
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def _GI_initializer(g: "GenerativeImage", function1: Callable, function2: Callable) -> None:
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"""
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Initialize the generative image.
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:param g: generative image instance
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:type g: GenerativeImage
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:param function1: function 1
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:type function1: python or lambda function
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:param function2: function 2
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:type function2: python or lambda function
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:return: None
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"""
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g.__version__ = SAMILA_VERSION
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g.matplotlib_version = matplotlib.__version__
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|
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@ -583,19 +514,18 @@ def _GI_initializer(g, function1, function2):
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g.missed_points_number = 0
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def nft_storage_upload(api_key, data, timeout, gateway):
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def nft_storage_upload(
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api_key: str,
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data: bytes,
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timeout: int,
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gateway: Gateway) -> Dict[str, Any]:
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"""
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Upload file to nft.storage.
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:param api_key: API key
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:type api_key: str
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:param data: image data
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:type data: binary
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:param timeout: upload timeout (in seconds)
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:type timeout: int
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:param gateway: IPFS gateway
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:type gateway: Gateway enum
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:return: result as dict
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"""
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result = {"status": True, "message": NFT_STORAGE_SUCCESS_MESSAGE}
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try:
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|
|
@ -619,15 +549,12 @@ def nft_storage_upload(api_key, data, timeout, gateway):
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return result
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def save_data_file(g, file_adr):
|
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def save_data_file(g: "GenerativeImage", file_adr: str) -> Dict[str, Any]:
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"""
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Save data as file.
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:param g: generative image instance
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:type g: GenerativeImage
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:param file_adr: file address
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:type file_adr: str
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:return: result as dict
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"""
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data = get_data(g)
|
||||
result = {"status": True, "message": DATA_SAVE_SUCCESS_MESSAGE}
|
||||
|
|
@ -641,25 +568,19 @@ def save_data_file(g, file_adr):
|
|||
return result
|
||||
|
||||
|
||||
def get_python_version():
|
||||
"""
|
||||
Get Python's version.
|
||||
|
||||
:return: python's version as 'major.minor'
|
||||
"""
|
||||
def get_python_version() -> str:
|
||||
"""Get Python's version as 'major.minor'."""
|
||||
return "{}.{}".format(
|
||||
sys.version_info.major,
|
||||
sys.version_info.minor
|
||||
)
|
||||
|
||||
|
||||
def get_data(g):
|
||||
def get_data(g: "GenerativeImage") -> Dict[str, Any]:
|
||||
"""
|
||||
Return data.
|
||||
|
||||
:param g: generative image instance
|
||||
:type g: GenerativeImage
|
||||
:return: data as a dict
|
||||
"""
|
||||
data = {}
|
||||
if g.data1 is None or g.data2 is None:
|
||||
|
|
@ -684,13 +605,11 @@ def get_data(g):
|
|||
return data
|
||||
|
||||
|
||||
def get_config(g):
|
||||
def get_config(g: "GenerativeImage") -> Dict[str, Any]:
|
||||
"""
|
||||
Return config.
|
||||
|
||||
:param g: generative image instance
|
||||
:type g: GenerativeImage
|
||||
:return: config as a dict
|
||||
"""
|
||||
config = {}
|
||||
if g.function1_str is None or g.function2_str is None:
|
||||
|
|
@ -722,7 +641,7 @@ def get_config(g):
|
|||
return config
|
||||
|
||||
|
||||
def save_config_file(g, file_adr):
|
||||
def save_config_file(g: "GenerativeImage", file_adr: str) -> Dict[str, Any]:
|
||||
"""
|
||||
Save config as file.
|
||||
|
||||
|
|
@ -744,17 +663,13 @@ def save_config_file(g, file_adr):
|
|||
return result
|
||||
|
||||
|
||||
def save_fig_file(figure, file_adr, depth):
|
||||
def save_fig_file(figure: matplotlib.figure.Figure, file_adr: str, depth: float) -> Dict[str, Any]:
|
||||
"""
|
||||
Save figure as file.
|
||||
|
||||
:param figure: matplotlib figure
|
||||
:type figure: matplotlib.figure.Figure
|
||||
:param file_adr: file address
|
||||
:type file_adr: str
|
||||
:param depth: image depth
|
||||
:type depth: float
|
||||
:return: result as dict
|
||||
"""
|
||||
if figure is None:
|
||||
return {"status": False, "message": NO_FIG_ERROR_MESSAGE}
|
||||
|
|
@ -773,15 +688,12 @@ def save_fig_file(figure, file_adr, depth):
|
|||
return result
|
||||
|
||||
|
||||
def save_fig_buf(figure, depth):
|
||||
def save_fig_buf(figure: matplotlib.figure.Figure, depth: float) -> Dict[str, Any]:
|
||||
"""
|
||||
Save figure as buffer.
|
||||
|
||||
:param figure: matplotlib figure
|
||||
:type figure: matplotlib.figure.Figure
|
||||
:param depth: image depth
|
||||
:type depth: float
|
||||
:return: result as dict
|
||||
"""
|
||||
if figure is None:
|
||||
return {"status": False, "message": NO_FIG_ERROR_MESSAGE}
|
||||
|
|
@ -805,28 +717,20 @@ def save_fig_buf(figure, depth):
|
|||
return result
|
||||
|
||||
|
||||
def samila_help():
|
||||
"""
|
||||
Print samila details.
|
||||
|
||||
:return: None
|
||||
"""
|
||||
def samila_help() -> None:
|
||||
"""Print samila details."""
|
||||
print(OVERVIEW)
|
||||
print("Website : https://www.samila.site")
|
||||
print("Repo : https://github.com/sepandhaghighi/samila")
|
||||
|
||||
|
||||
def is_same_data(data1, data2, precision=10**-5):
|
||||
def is_same_data(data1: List[float], data2: List[float], precision: float = 10**-5) -> bool:
|
||||
"""
|
||||
Compare two data to be the same.
|
||||
Compare two data to be the same, return True if they are.
|
||||
|
||||
:param data1: given data1
|
||||
:type data1: list
|
||||
:param data2: given data2
|
||||
:type data2: list
|
||||
:param precision: comparing precision
|
||||
:type precision: float
|
||||
:return: True if they are the same
|
||||
"""
|
||||
if len(data1) != len(data2):
|
||||
return False
|
||||
|
|
@ -834,37 +738,31 @@ def is_same_data(data1, data2, precision=10**-5):
|
|||
return all(is_same)
|
||||
|
||||
|
||||
def _serialize_color(color):
|
||||
def _serialize_color(color: Union[str, Iterable[str]]) -> Union[str, List[str]]:
|
||||
"""
|
||||
Serialize the given color to a json serializable object.
|
||||
|
||||
:param color: given color
|
||||
:type color: str or nd.array
|
||||
:return: the serializable version of the color
|
||||
"""
|
||||
if isinstance(color, str):
|
||||
return color
|
||||
return list(color)
|
||||
|
||||
|
||||
def _serialize_cmap(cmap):
|
||||
def _serialize_cmap(cmap: matplotlib.colors.Colormap) -> List[str]:
|
||||
"""
|
||||
Serialize the cmap for saving.
|
||||
|
||||
:param cmap: color map
|
||||
:type cmap: matplotlib.colors.Colormap
|
||||
:return: list of colors
|
||||
"""
|
||||
return list(map(_serialize_color, cmap.colors))
|
||||
|
||||
|
||||
def _load_cmap(config):
|
||||
def _load_cmap(config: Dict[str, Any]) -> matplotlib.colors.ListedColormap:
|
||||
"""
|
||||
Load the cmap from config.
|
||||
|
||||
:param config: plot part configuration
|
||||
:type config: dict or json
|
||||
:return: ListedColormap from cmap
|
||||
"""
|
||||
if "cmap" not in config:
|
||||
return get_cmap()
|
||||
|
|
@ -872,15 +770,12 @@ def _load_cmap(config):
|
|||
return matplotlib.colors.ListedColormap(cmap)
|
||||
|
||||
|
||||
def load_data(g, data):
|
||||
def load_data(g: "GenerativeImage", data: io.IOBase) -> None:
|
||||
"""
|
||||
Load data file.
|
||||
|
||||
:param g: generative image instance
|
||||
:type g: GenerativeImage
|
||||
:param data: prior generated data
|
||||
:type data: (io.IOBase & file)
|
||||
:return: None
|
||||
"""
|
||||
if isinstance(data, io.IOBase):
|
||||
data = json.load(data)
|
||||
|
|
@ -910,15 +805,12 @@ def load_data(g, data):
|
|||
raise samilaDataError(DATA_TYPE_ERROR)
|
||||
|
||||
|
||||
def load_config(g, config):
|
||||
def load_config(g: "GenerativeImage", config: io.IOBase) -> None:
|
||||
"""
|
||||
Load config file.
|
||||
|
||||
:param g: generative image instance
|
||||
:type g: GenerativeImage
|
||||
:param config: config JSON file
|
||||
:type config: (io.IOBase & file)
|
||||
:return: None
|
||||
"""
|
||||
if isinstance(config, io.IOBase):
|
||||
config = json.load(config)
|
||||
|
|
|
|||
|
|
@ -1,7 +1,11 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""Samila generative image."""
|
||||
from typing import List, Tuple, Dict, Callable
|
||||
from typing import Union, Iterable
|
||||
from typing import Any
|
||||
import json
|
||||
import random
|
||||
import io
|
||||
import gc
|
||||
import itertools
|
||||
import matplotlib
|
||||
|
|
@ -28,24 +32,19 @@ class GenerativeImage:
|
|||
|
||||
def __init__(
|
||||
self,
|
||||
function1=None,
|
||||
function2=None,
|
||||
data=None,
|
||||
config=None,
|
||||
func_seed=None):
|
||||
function1: Callable = None,
|
||||
function2: Callable = None,
|
||||
data: io.IOBase = None,
|
||||
config: io.IOBase = None,
|
||||
func_seed: Any = None) -> None:
|
||||
"""
|
||||
Init method.
|
||||
|
||||
:param function1: function 1
|
||||
:type function1: python or lambda function
|
||||
:param function2: function 2
|
||||
:type function2: python or lambda function
|
||||
:param data: prior generated data
|
||||
:type data: (io.IOBase & file)
|
||||
:param config: generative image config
|
||||
:type config: (io.IOBase & file)
|
||||
:param func_seed: random seed for function generation
|
||||
:type func_seed: Any
|
||||
"""
|
||||
_GI_initializer(self, function1, function2)
|
||||
if config is not None:
|
||||
|
|
@ -74,25 +73,19 @@ class GenerativeImage:
|
|||
|
||||
def generate(
|
||||
self,
|
||||
seed=None,
|
||||
start=None,
|
||||
step=None,
|
||||
stop=None,
|
||||
mode=None):
|
||||
seed: int = None,
|
||||
start: float = None,
|
||||
step: float = None,
|
||||
stop: float = None,
|
||||
mode: GenerateMode = None) -> None:
|
||||
"""
|
||||
Generate a raw format of art.
|
||||
|
||||
:param seed: random seed
|
||||
:type seed: int
|
||||
:param start: range start point
|
||||
:type start: float
|
||||
:param step: range step size
|
||||
:type step: float
|
||||
:param stop: range stop point
|
||||
:type stop: float
|
||||
:param mode: generate mode
|
||||
:type mode: GenerateMode enum
|
||||
:return: None
|
||||
"""
|
||||
generate_params_filter(self, seed, start, step, stop, mode)
|
||||
self.data1 = []
|
||||
|
|
@ -166,40 +159,29 @@ class GenerativeImage:
|
|||
|
||||
def plot(
|
||||
self,
|
||||
color=None,
|
||||
bgcolor=None,
|
||||
cmap=None,
|
||||
spot_size=None,
|
||||
size=None,
|
||||
projection=None,
|
||||
marker=None,
|
||||
alpha=None,
|
||||
linewidth=None,
|
||||
rotation=None):
|
||||
color: Union[str, Iterable[str]] = None,
|
||||
bgcolor: Union[str, Iterable[str]] = None,
|
||||
cmap: Union[matplotlib.colors.Colormap, List]=None,
|
||||
spot_size: float=None,
|
||||
size: Tuple[float, float]=None,
|
||||
projection: Projection = None,
|
||||
marker: Marker = None,
|
||||
alpha: float = None,
|
||||
linewidth: float = None,
|
||||
rotation: float = None) -> None:
|
||||
"""
|
||||
Plot the generated art.
|
||||
|
||||
:param color: point colors
|
||||
:type color: str
|
||||
:param bgcolor: background color
|
||||
:type bgcolor: str
|
||||
:param cmap: color map
|
||||
:type cmap: matplotlib.colors.Colormap or list of colors
|
||||
:param spot_size: point spot size
|
||||
:type spot_size: float
|
||||
:param size: figure size
|
||||
:type size: tuple
|
||||
:param projection: projection type
|
||||
:type projection: str
|
||||
:param marker: marker type
|
||||
:type marker: str
|
||||
:param alpha: point transparency
|
||||
:type alpha: float
|
||||
:param linewidth: width of line
|
||||
:type linewidth: float
|
||||
:param rotation: desired rotation (in degrees)
|
||||
:type rotation: float
|
||||
:return: None
|
||||
"""
|
||||
plot_params_filter(
|
||||
self,
|
||||
|
|
@ -237,28 +219,21 @@ class GenerativeImage:
|
|||
@deprecated
|
||||
def nft_storage(
|
||||
self,
|
||||
api_key,
|
||||
upload_data=False,
|
||||
upload_config=False,
|
||||
depth=None,
|
||||
timeout=3000,
|
||||
gateway=Gateway.IPFS_IO):
|
||||
api_key: str,
|
||||
upload_data: bool = False,
|
||||
upload_config: bool = False,
|
||||
depth: float = None,
|
||||
timeout: int = 3000,
|
||||
gateway: Gateway = Gateway.IPFS_IO) -> Dict[str, Any]:
|
||||
"""
|
||||
Upload image to nft.storage.
|
||||
|
||||
:param api_key: API key
|
||||
:type api_key: str
|
||||
:param upload_data: upload data flag
|
||||
:type upload_data: bool
|
||||
:param upload_config: upload config flag
|
||||
:type upload_config: bool
|
||||
:param depth: image depth
|
||||
:type depth: float
|
||||
:param timeout: upload timeout (in seconds)
|
||||
:type timeout: int
|
||||
:param gateway: IPFS gateway
|
||||
:type gateway: Gateway enum
|
||||
:return: result as dict
|
||||
"""
|
||||
save_params_filter(self, depth)
|
||||
response = save_fig_buf(self.fig, self.depth)
|
||||
|
|
@ -291,45 +266,34 @@ class GenerativeImage:
|
|||
result[key]['data'] = value
|
||||
return result
|
||||
|
||||
def save_image(self, file_adr, depth=None):
|
||||
def save_image(self, file_adr: str, depth: float = None) -> Dict[str, Any]:
|
||||
"""
|
||||
Save generated image.
|
||||
|
||||
:param file_adr: file address
|
||||
:type file_adr: str
|
||||
:param depth: image depth
|
||||
:type depth: float
|
||||
:return: result as dict
|
||||
"""
|
||||
save_params_filter(self, depth)
|
||||
return save_fig_file(self.fig, file_adr, self.depth)
|
||||
|
||||
def save_data(self, file_adr='data.json'):
|
||||
def save_data(self, file_adr: str = 'data.json') -> Dict[str, Any]:
|
||||
"""
|
||||
Save data into a file.
|
||||
|
||||
:param file_adr: file address
|
||||
:type file_adr: str
|
||||
:return: result as dict
|
||||
"""
|
||||
return save_data_file(self, file_adr)
|
||||
|
||||
def save_config(self, file_adr='config.json'):
|
||||
def save_config(self, file_adr: str = 'config.json') -> Dict[str, Any]:
|
||||
"""
|
||||
Save config into a file.
|
||||
|
||||
:param file_adr: file address
|
||||
:type file_adr: str
|
||||
:return: result as a dict
|
||||
"""
|
||||
return save_config_file(self, file_adr)
|
||||
|
||||
def __del__(self):
|
||||
"""
|
||||
Destructor.
|
||||
|
||||
:return:None
|
||||
"""
|
||||
def __del__(self) -> None:
|
||||
"""Destructor."""
|
||||
try:
|
||||
del self.data1
|
||||
del self.data2
|
||||
|
|
|
|||
Ładowanie…
Reference in New Issue