Here is the code i used to create an Edice for microbit:
from microbit import *
import random
image1 = Image("00000:"
"00000:"
"00900:"
"00000:"
"00000")
image2 = Image("90000:"
"00000:"
"00000:"
"00000:"
"00009")
image3 = Image("90000:"
"00000:"
"00900:"
"00000:"
"00009")
image4 = Image("90009:"
"00000:"
"00000:"
"00000:"
"90009")
image5 = Image("90009:"
"00000:"
"00900:"
"00000:"
"90009")
image6 = Image("90009:"
"00000:"
"90009:"
"00000:"
"90009")
images=[image1, image2, image3, image4, image5, image6]
while True:
if button_a.is_pressed():
for i in range(0, 16):
display.show(images)
display.show(random.randint.(1, 6))
sleep(20)
display.clear
display.show(image(random.randint(1, 6)))
display.show(random.randint.(1, 6)) seems to be registered as a synatax error.
May I know what is the problem and how i can improve on the code
There is an extra .
You wrote: display.show(random.randint.(1, 6))
It should be: display.show(random.randint(1, 6))
Related
import cv2
import mediapipe as mp
import numpy as np
import sys
mp_drawing = mp.solutions.drawing_utils
mp_pose = mp.solutions.pose
mp_drawing_styles = mp.solutions.drawing_styles
#min_Tracking_confidence = 1 for higher accuracy
pose = mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=1)
#Import Video and Set codec
cap = cv2.VideoCapture(sys.argv[1])
# print("cap :", cap.shape)
fourcc = cv2.VideoWriter_fourcc(*'MP4V')
if cap.isOpened() == False:
print("Error opening video stream or file")
raise TypeError
frame_width = int(cap.get(3))
frame_height = int(cap.get(4))
outdir, inputflnm = sys.argv[1][:sys.argv[1].rfind(
'/')+1], sys.argv[1][sys.argv[1].rfind('/')+1:]
inflnm, inflext = inputflnm.split('.')
out_filename = f'{outdir}{inflnm}_annotated.{inflext}'
# out = cv2.VideoWriter(out_filename, cv2.VideoWriter_fourcc(
# 'M', 'J', 'P', 'G'), 10, (frame_width, frame_height))
out = cv2.VideoWriter(out_filename, fourcc, 30, (frame_width, frame_height))
while cap.isOpened():
ret, image = cap.read()
if not ret:
break
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image.flags.writeable = False
results = pose.process(image) #core
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# Render detections
mp_drawing.draw_landmarks(
image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
out.write(image)
mp_drawing.plot_landmarks(
results.pose_world_landmarks, mp_pose.POSE_CONNECTIONS)
pose.close()
cap.release()
out.release()
Hello,
I would like to extract skeleton without skeleton+video.
I changed the code to using input video instead of original image in Mediapipe code.
and the result was success.
the result was the video with skeleton
plus I want to see only skeleton without video.
I tired to remove the video but i could not.
I appreciate to you if you give me any help!
I'm struggling with the map tilt. I would like help to change the tilt of the following map. Thanks!
The first map is my result, the second map is how I would like the slope to be.
library(usmap)
library (ggplot2)
read.table("NY_data.txt", header = T)->NY_data
NY1 <- plot_usmap(regions = "county", include = c("NY"), data = NY_data, values = "YEAR_2010") +
labs(title = "New York by county", subtitle = "2010") +
theme(plot.title = element_text(face="bold", size=18, hjust = 0.5),
plot.subtitle = element_text(face="bold", size=16)) +
scale_fill_continuous(low = "white", high = "#CB454A", limits=c(0, 35),
name = "Cumulative cases",
guide = guide_colourbar(barwidth = 27, barheight = 0.5,
title.position = "top"),
label = scales::comma) +
theme(legend.position = "bottom",
legend.title=element_text(size=12, face = "bold"),
legend.text=element_text(size=10))
NY1
map1
map2
In my script, I use pandas module. When I execute my file.py - everything works well. But I've converted my file.py to file.exe with auto-py-to-exe and got an error: AttributeError:'str' object has no attribute 'unique'. It's strange because it worked normally. The line where becomes an error: wells=list(file[0].unique()). Who knows this issue, please help.
import tkinter as tk
import tkinter.filedialog as fd
import pandas as pd
import os
import datetime
from datetime import datetime, date
import numpy as np
pd.set_option('display.notebook_repr_html', False)
pd.set_option('display.max_columns', 80)
pd.set_option('display.max_rows', 200)
pd.set_option('display.width', 800)
def resource_path(relative_path):
try:
base_path = sys._MEIPASS
except Exception:
base_path = os.path.abspath(".")
return os.path.join(base_path, relative_path)
def open():
global file_excel, name
file_excel = fd.askopenfilename(initialdir='/Desktop', title='Открыть файл', filetypes = [("Excel", "*.xlsx")])
name = os.path.basename(file_excel)
name=os.path.splitext(name)[0]
file_excel=pd.read_excel(file_excel, skiprows=[0], header=None)
win.destroy()
return file_excel, name
win = tk.Tk()
path = resource_path("image.png")
photo = tk.PhotoImage(file=path)
win.iconphoto(False, photo)
win.config(bg='#FFC')
win.title('Конвертация в формат .ev')
win.geometry('400x130+500+500')
win.resizable(False, False)
label_1 = tk.Label(win, text = 'Выберите файл с испытаниями скважин:',
bg = '#FFC',
font=('Arial', 10, 'bold'),
padx=20,
pady=10).pack()
btn_1 = tk.Button(win, text = 'Выбрать Excel',
command = open,
activebackground = '#6F6',
font=('Arial', 12, 'bold'),
padx=20,
pady=10,
relief = tk.RAISED,
bd=2).pack()
win.mainloop()
wells=list(file_excel[0].unique())
file_excel[1] = pd.to_datetime(file_excel[1], errors='coerce').dt.strftime("%d/%m/%Y")
file_excel[4] = np.where(file_excel[1].str, 'Perforation', np.nan)
file_excel.iloc[:,[2,3]]=file_excel.iloc[:,[2,3]].abs()
col_list = list(file_excel)
col_list[4], col_list[2] = col_list[2], col_list[4]
file_excel.columns = col_list
Perforation=pd.DataFrame(data=None)
for i in wells:
well_name=pd.DataFrame({'WELLNAME '+i}, columns=[1])
Perforation=Perforation.append(well_name)
Perforation=Perforation.append(file_excel.iloc[:,[1,2,3,4]][file_excel.iloc[:,0]==i])
Perforation=Perforation.append(pd.Series(dtype = 'object'), ignore_index=True)
def SaveFile():
Save=fd.asksaveasfile(mode='w',defaultextension=".ev", initialfile=name)
Save.write(Perforation.to_string(index=False, header=False, na_rep=' '))
win.destroy()
win = tk.Tk()
path = resource_path("image.png")
photo = tk.PhotoImage(file=path)
win.iconphoto(False, photo)
win.config(bg='#FFC')
win.title('Конвертация в формат .ev')
win.geometry('400x130+500+500')
win.resizable(False, False)
label_1 = tk.Label(win, text = 'Сохранение:',
bg = '#FFC',
font=('Arial', 10, 'bold'),
padx=20,
pady=10).pack()
btn_1 = tk.Button(win, text = 'Сохранить как',
command = SaveFile,
activebackground = '#6F6',
font=('Arial', 12, 'bold'),
padx=20,
pady=10,
relief = tk.RAISED,
bd=2).pack()
win.mainloop()
type of file[0]
Error screen
When I created virtual env I should have added openpyxl module. And I made it and everything is fine now
I've got a rough and ready function that can be used to compare two sets of values using histograms:
I want to set the individual edge colors of each of the histograms in the top plot (much as how I set the individual sets of values used for each histogram). How could this be done?
import os
import datavision
import matplotlib.pyplot
import numpy
import shijian
def main():
a = numpy.random.normal(2, 2, size = 120)
b = numpy.random.normal(2, 2, size = 120)
save_histogram_comparison_matplotlib(
values_1 = a,
values_2 = b,
label_1 = "a",
label_2 = "b",
normalize = True,
label_ratio_x = "measurement",
label_y = "",
title = "comparison of a and b",
filename = "histogram_comparison_1.png"
)
def save_histogram_comparison_matplotlib(
values_1 = None,
values_2 = None,
filename = None,
directory = ".",
number_of_bins = None,
normalize = True,
label_x = "",
label_y = None,
label_ratio_x = None,
label_ratio_y = "ratio",
title = "comparison",
label_1 = "1",
label_2 = "2",
overwrite = True,
LaTeX = False,
#aspect = None,
font_size = 20,
color_1 = "#3861AA",
color_2 = "#00FF00",
color_3 = "#7FDADC",
color_edge_1 = "#3861AA", # |<---------- insert magic for these
color_edge_2 = "#00FF00", # |
alpha = 0.5,
width_line = 1
):
matplotlib.pyplot.ioff()
if LaTeX is True:
matplotlib.pyplot.rc("text", usetex = True)
matplotlib.pyplot.rc("font", family = "serif")
if number_of_bins is None:
number_of_bins_1 = datavision.propose_number_of_bins(values_1)
number_of_bins_2 = datavision.propose_number_of_bins(values_2)
number_of_bins = int((number_of_bins_1 + number_of_bins_2) / 2)
if filename is None:
if title is None:
filename = "histogram_comparison.png"
else:
filename = shijian.propose_filename(
filename = title + ".png",
overwrite = overwrite
)
else:
filename = shijian.propose_filename(
filename = filename,
overwrite = overwrite
)
values = []
values.append(values_1)
values.append(values_2)
bar_width = 0.8
figure, (axis_1, axis_2) = matplotlib.pyplot.subplots(
nrows = 2,
gridspec_kw = {"height_ratios": (2, 1)}
)
ns, bins, patches = axis_1.hist(
values,
color = [
color_1,
color_2
],
normed = normalize,
histtype = "stepfilled",
bins = number_of_bins,
alpha = alpha,
label = [label_1, label_2],
rwidth = bar_width,
linewidth = width_line,
#edgecolor = [color_edge_1, color_edge_2] <---------- magic here? dunno
)
axis_1.legend(
loc = "best"
)
bars = axis_2.bar(
bins[:-1],
ns[0] / ns[1],
alpha = 1,
linewidth = 0, #width_line
width = bins[1] - bins[0]
)
for bar in bars:
bar.set_color(color_3)
axis_1.set_xlabel(label_x, fontsize = font_size)
axis_1.set_ylabel(label_y, fontsize = font_size)
axis_2.set_xlabel(label_ratio_x, fontsize = font_size)
axis_2.set_ylabel(label_ratio_y, fontsize = font_size)
#axis_1.xticks(fontsize = font_size)
#axis_1.yticks(fontsize = font_size)
#axis_2.xticks(fontsize = font_size)
#axis_2.yticks(fontsize = font_size)
matplotlib.pyplot.suptitle(title, fontsize = font_size)
if not os.path.exists(directory):
os.makedirs(directory)
#if aspect is None:
# matplotlib.pyplot.axes().set_aspect(
# 1 / matplotlib.pyplot.axes().get_data_ratio()
# )
#else:
# matplotlib.pyplot.axes().set_aspect(aspect)
figure.tight_layout()
matplotlib.pyplot.subplots_adjust(top = 0.9)
matplotlib.pyplot.savefig(
directory + "/" + filename,
dpi = 700
)
matplotlib.pyplot.close()
if __name__ == "__main__":
main()
You may simply plot two different histograms but share the bins.
import numpy as np; np.random.seed(3)
import matplotlib.pyplot as plt
a = np.random.normal(size=(89,2))
kws = dict(histtype= "stepfilled",alpha= 0.5, linewidth = 2)
hist, edges,_ = plt.hist(a[:,0], bins = 6,color="lightseagreen", label = "A", edgecolor="k", **kws)
plt.hist(a[:,1], bins = edges,color="gold", label = "B", edgecolor="crimson", **kws)
plt.show()
Use the lists of Patches objects returned by the hist() function.
In your case, you have two datasets, so your variable patches will be a list containing two lists, each with the Patches objects used to draw the bars on your plot.
You can easily set the properties on all of these objects using the setp() function. For example:
a = np.random.normal(size=(100,))
b = np.random.normal(size=(100,))
c,d,e = plt.hist([a,b], color=['r','g'])
plt.setp(e[0], edgecolor='k', lw=2)
plt.setp(e[1], edgecolor='b', lw=3)
I have the code below that is a combination of two boxplots and dot plots in one. It is a representation of barring density in 4 different species. The grey depicts the males and the tan the females.
data<-read.csv("C:/Users/Jeremy/Documents/A_Trogon rufus/Black-and-White/BARDATA_boxplots_M.csv")
datF<-read.csv("C:/Users/Jeremy/Documents/A_Trogon rufus/FEMALES_BW&Morphom.csv")
cleandataM<-subset(data, data$Age=="Adult" & data$White!="NA", select=(OTU:Density))
cleandatF<-subset(datF, datF$Age=="Adult", select=(OTU:Density))
dataM<- as.data.frame(cleandataM)
dataF<- as.data.frame(cleandatF)
library(ggplot2)
ggplot(dataM, aes(factor(OTU), Density))+
geom_boxplot(data=dataF,aes(factor(OTU),Density), fill="AntiqueWhite")+
geom_boxplot(fill="lightgrey", alpha=0.5)+
geom_point(data=dataF,position = position_jitter(width = 0.1), colour="tan")+
geom_point(data=dataM, position = position_jitter(width = 0.1), color="DimGrey")+ scale_x_discrete(name="",limits=order)+
scale_y_continuous(name="Bar Density (bars/cm)")+
theme(panel.background = element_blank(),panel.grid.minor=element_blank(),
panel.grid.major=element_blank(),axis.line = element_line(colour = "black"),
axis.title.y = element_text(colour="black", size=14),
axis.text.y = element_text(colour="black", size=12),
axis.text.x = element_text(colour="black", size=14))
This works just fine.
However, when I try to add a legend as:
legend("topright", inset=.01, bty="n", cex=.75, title="Sex",
c("Male", "Female"), fill=c("lightgrey", "black")
It returns the following Error:
Error in strwidth(legend, units = "user", cex = cex, font = text.font) :
plot.new has not been called yet
Please, is there someone who could suggest how to correct this?