fix python parsing, update deps
python parsing was broken & openai changed their internal APImaster
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@ -299,11 +299,11 @@
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},
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"revchatgpt": {
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"hashes": [
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"sha256:36860b0297d5e846172c2fcfcdf27b4f19b80eac299b4e00c93a5dccf27f18c1",
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"sha256:3fce7e348a8817e4335130a9ab2e523633c8c49cad1d2ca577571aeaa4a00115"
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"sha256:6217e51914300123bc01f1519de68eeece8bdca0aa68bca71e540d293cbbc23c",
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"sha256:fcebca9815761b6fcb5abbfb8b28bbee810d2a01fc148c19429066818a29d933"
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],
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"index": "pypi",
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"version": "==0.0.23.5"
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"version": "==0.0.30"
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},
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"six": {
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"hashes": [
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@ -1,9 +1,10 @@
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import json
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import yaml
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from yaml import CLoader, CDumper
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from revChatGPT.revChatGPT import Chatbot
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import os
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from sys import argv
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import re
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from parse import py
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# from argparse import ArgumentParser
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@ -23,39 +24,20 @@ infile = open(argv[1], "r")
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# print(infile)
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# top level functions only for now
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functions = []
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function_head = ""
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function_content = ""
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function_body_indent_level = 0
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for line in infile:
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curr_indent_level = len(line) - len(line.lstrip())
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function_found = re.search('^def(\s+)(.*)\(.*\)(\s*):$', line.strip())
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if function_found and len(function_head) == 0:
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function_head = re.search("(\s+)(.*)\(.*\)", line).string.replace('def', '').replace('):', ')').strip()
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function_content = line
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function_body_indent_level = curr_indent_level + 1
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elif len(function_head) > 0 and (curr_indent_level < function_body_indent_level):
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functions.append({
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"head": function_head,
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"content": function_content
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})
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if function_found:
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function_head = ""
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function_content = ""
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elif len(function_head) > 0 and curr_indent_level >= function_body_indent_level:
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function_content += line
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functions = py.find_toplevel_funcs(infile)
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print(f"Found {len(functions)} functions.")
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doc_prompt_head = "Explain what this function does in one short sentence, then give example code that uses the function:\n"
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# doc_prompt_example = "Return only example code using this function:\n"
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# for function in functions:
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# print(function["content"])
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# print("------------------")
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bot = Chatbot({
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'Authorization': config['Authorization'],
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'session_token': config['session_token'],
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# 'session': config['password']
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}, conversation_id=None)
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bot.refresh_session()
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@ -1,58 +1,101 @@
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# Documentation for `example_code.py`
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# Documentation for `example/example_code.py`
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## `remove_dirt(image)`
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This function removes small dirt and noise from a binary image by closing small holes and removing small objects.
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This function removes small elements from an image using area closing morphological operation.
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Here is an example of how to use the function:
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Example:
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```
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import skimage.morphology as morphology
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from skimage import data
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# Import the required module
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from skimage import morphology
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# Load a binary image
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image = data.coins() > 100
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# Load the image
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image = skimage.io.imread('image.jpg')
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# Remove dirt from the image
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cleaned_image = remove_dirt(image)
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# Apply the function to remove small elements from the image
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image = remove_dirt(image)
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# Show the result
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skimage.io.imshow(image)
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```
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## `calculate_area(countour)`
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This function calculates the area of a contour in an image.
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Example:
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```
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# Import the required modules
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import cv2 as cv
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import numpy as np
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# Load the image and find the contours
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image = cv.imread('image.jpg')
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contours, _ = cv.findContours(image, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
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# Iterate over the contours and calculate their areas
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for contour in contours:
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area = calculate_area(contour)
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print('Area of contour:', area)
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```
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## `center_of_mass(X)`
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This function calculates the center of mass of a 2D shape defined by a set of points.
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This function calculates the center of mass of a set of points.
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Here is an example of how to use the function:
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Example:
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```
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import numpy as np
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# Define a set of points that define a shape
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X = np.array([[0, 0], [0, 1], [1, 1], [1, 0]])
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# Define a set of points
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X = np.array([[1,2], [3,4], [5,6]])
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# Calculate the center of mass of the shape
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center_of_mass = center_of_mass(X)
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# Calculate the center of mass of the points
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center = center_of_mass(X)
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# Print the center of mass
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print(center_of_mass)
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# Print the result
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print('Center of mass:', center)
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```
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The output will be `[0.5, 0.5]`, which is the coordinates of the center of the square defined by the points `X`.
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The output will be `Center of mass: [3. 4.]`.
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## `center_of_mass(X)`
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This function calculates the center of mass of a 2D shape defined by a set of points.
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This function calculates the center of mass of a set of points.
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Here is an example of how to use the function:
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Example:
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```
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import numpy as np
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# Define a set of points that define a shape
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X = np.array([[0, 0], [0, 1], [1, 1], [1, 0]])
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# Define a set of points
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X = np.array([[1,2], [3,4], [5,6]])
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# Calculate the center of mass of the shape
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center_of_mass = center_of_mass(X)
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# Calculate the center of mass of the points
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center = center_of_mass(X)
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# Print the center of mass
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print(center_of_mass)
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# Print the result
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print('Center of mass:', center)
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```
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The output will be `[0.5, 0.5]`, which is the coordinates of the center of the square defined by the points `X`.
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The output will be `Center of mass: [3. 4.]`.
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## `rg_ratio_normalize(imgarr)`
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This function normalizes the temperature values in an image array using the RG ratio and a pyrometry calibration formula.
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Example:
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```
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# Import the required modules
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import numpy as np
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# Load the image array
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imgarr = np.array(...)
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# Normalize the temperature values in the image
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imgnew, tmin, tmax = rg_ratio_normalize(imgarr)
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# Print the resulting minimum and maximum temperature values
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print('Minimum temperature:', tmin)
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print('Maximum temperature:', tmax)
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```
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@ -4,12 +4,14 @@ def remove_dirt(image):
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return image
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def calculate_area(countour):
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c = np.expand_dims(countour.astype(np.float32), 1)
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c = cv.UMat(c)
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return cv.contourArea(c)
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def center_of_mass(X):
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x = X[:,0]
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y = X[:,1]
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@ -22,6 +24,7 @@ def center_of_mass(X):
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img = remove_dirt(thresh_gray)
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def rg_ratio_normalize(imgarr):
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# set max & min to most extreme values,
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# work up & down respectively from there
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@ -0,0 +1,30 @@
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import re
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def find_toplevel_funcs(lines):
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functions = []
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function_head = ""
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function_content = ""
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function_body_indent_level = 0
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for line in lines:
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curr_indent_level = len(line) - len(line.lstrip())
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function_found = re.search('^def(\s+)(.*)\(.*\)(\s*):(\s*)$', line.strip())
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if len(function_head.strip()) > 0 and (curr_indent_level < function_body_indent_level):
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functions.append({
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"head": function_head,
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"content": function_content
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})
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if function_found:
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function_head = ""
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function_content = ""
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if function_found and len(function_head) == 0:
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function_head = re.search("(\s+)(.*)\(.*\)", line).string.replace('def', '').replace('):', ')').strip()
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function_content = line
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function_body_indent_level = curr_indent_level + 1
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elif not function_found and len(function_head.strip()) > 0 and curr_indent_level >= function_body_indent_level:
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function_content += line
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return functions
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