""" This is a basic example of how to use the library to create a boxplot in Python """ from graphy2.core import Graphy from graphy2.StyleSheet import BLUE_ON_WHITE_GRID import seaborn as sns if __name__ == "__main__": # Load an example dataset from seaborn as the sample dataset data = sns.load_dataset("tips") # Modify a default style to have a smaller image size for a Non-print online only figure BLUE_ON_WHITE_GRID["dpi"] = 72 # Call graphy2 to produce a box plot Graphy(data, "Box Plot", BLUE_ON_WHITE_GRID).box_plot(x_var="day", y_var="total_bill")
from graphy2.core import Graphy if __name__ == '__main__': # Set the directory where your images are stored data = r"Path\To\Images" # Set the size to bound your images too, and then the 3D position of the camera that will view your graph Graphy(data, "Stacking Images").image_stack_figure(down_sampling=10, elevation=15, rotation=30)
from graphy2.core import Graphy if __name__ == '__main__': # Load in a csv with Labels, Amount, Explode columns read_data = r"C:\Users\Samuel\PycharmProjects\graphy2\ExampleData\Pie.csv" # Create the pie chart Graphy(read_data, "Pie Plot").pie_chart(display_values='%1.1f%%')
if file_only: return [file for file in os.listdir(directory) if os.path.isfile(f"{directory}/{file}")] else: return [file for file in os.listdir(directory)] if __name__ == '__main__': # read_data = r"C:\Users\Samuel\PycharmProjects\graphy2\ExampleData\Binary_meta_event_total.csv" read_data = r"C:\Users\Samuel\PycharmProjects\AsthmaDisease\Testing" for index, file in enumerate(directory_iterator(read_data)): print(file) a = Path(read_data, file) if a.suffix == ".csv": Graphy(f"{read_data}/{file}", f"A{index}").forest_plot() # Graphy(f"{read_data}/base_forest.csv", "scarlet").forest_plot() # Graphy(f"{read_data}/sc_cont.csv", "sc_cont").forest_plot() # Graphy(f"{read_data}/sc_scarlet.csv", "sc_scarlet").forest_plot() # Graphy(f"{read_data}/sci_cont.csv", "sci_cont").forest_plot() # Graphy(f"{read_data}/sci_scarlet.csv", "sci_scarlet").forest_plot() # Graphy(f"{read_data}/sci_int.csv", "sci_int").forest_plot() # Graphy(f"{read_data}/sr_risk.csv", "sr_risk").forest_plot() # Graphy(f"{read_data}/sr_scarlet.csv", "sr_scarlet").forest_plot() # Graphy(f"{read_data}/sri_int.csv", "sri_int").forest_plot() # Graphy(f"{read_data}/sri_scarlet.csv", "sri_scarlet").forest_plot() # Graphy(f"{read_data}/sri_risk.csv", "sri_risk").forest_plot() # # Graphy(f"{read_data}/.csv", "AVbase_Forest").forest_plot()
""" This is a basic example of how to use the library to create a violinplot in Python """ from graphy2.core import Graphy if __name__ == "__main__": import seaborn as sns import os # Load an example dataset from seaborn as the sample dataset data = sns.load_dataset("tips") # Get the path for the directory of this file, and save output to new sub-directory 'plots' write_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "plots") # Call graphy2 to produce a box plot Graphy(data, write_dir).violin_plot(x_var="day", y_var="total_bill", gradient_variable="sex")
from graphy2 import sys from graphy2.core import Graphy if __name__ == '__main__': # Rgraphy2 Null args don't get passed as system arguments, but False will be passed as a string rather than as a # bool so args needs formatting so that a False String returns a None type args = [] for arg in sys.argv: if "FALSE" in arg: args.append(None) else: args.append(arg) try: function_name = args[1] except IndexError as e: raise Exception("No arguments passed to graphy_call.py") from e try: class_args = [args[i] for i in range(2, 6)] except IndexError as e: raise Exception("Not enough arguments passed to graphy_call.py for the class args. Args should be:\n" "[0]Script_name\n[1]class_method_name\n[2]path_to_data_file\n[3]write_directory\n" "[4]figure_name\n[5]style_sheet\n[6+]args for class_method_name") method_args = [args[i] for i in range(6, len(args))] getattr(Graphy(*class_args), str(function_name))(*method_args)
""" This is a basic example of how to use the library to create a lineplot in Python """ from graphy2.core import Graphy import seaborn as sns if __name__ == "__main__": # Load an example dataset from seaborn as the sample dataset data = sns.load_dataset("fmri") # Call graphy2 to produce a line plot Graphy(data, "Line Plot").line_plot(x_var="timepoint", y_var="signal")
""" This is a basic example of how to use the library to create a kdeplot in Python """ from graphy2.core import Graphy import numpy as np np.random.seed(10) import pandas as pd if __name__ == "__main__": import seaborn as sns import os # Load an example dataset from seaborn as the sample dataset mean, cov = [0, 2], [(1, .5), (.5, 1)] x, y = np.random.multivariate_normal(mean, cov, size=50).T data = pd.DataFrame({'X': x, 'Y': y}, columns=['X', 'Y']) # Get the path for the directory of this file, and save output to new sub-directory 'plots' write_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "plots") # Call graphy2 to produce a box plot Graphy(data, write_dir).kde_plot()
""" This is a basic example of how to use the library natively in python. """ from graphy2.core import Graphy if __name__ == "__main__": # Set the file path csv_path = "./Path/to/your/file.csv" # Set where to save your file write_dir = "./Save/Directory" # Call graphy2's Graphy for the graph you want Graphy(csv_path, write_dir).scatter_plot("carat", "price", "clarity", "depth")
""" This is a basic example of how to use the library to create a barplot in Python """ from graphy2.core import Graphy if __name__ == "__main__": import seaborn as sns import os # Load an example dataset from seaborn as the sample dataset data = sns.load_dataset("tips") # Get the path for the directory of this file, and save output to new sub-directory 'plots' write_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "plots") # Call graphy2 to produce a box plot Graphy(data, write_dir).bar_plot(x_var="sex", y_var="total_bill", gradient_variable="smoker")