Use of the VPython library to create a small table in a simulated 3D space
this is what I've got
top = box(pos=vector(-1,4,4),
axis=vector(-1.5,0,-1.5),
size=vector(18,0.29,10),
up=vector(5,25,5),
color = color.blue)
leg1 = cylinder(pos=(-3,-3,0),
axis=vector(0,7,0), radius=0.45,
color = color.green )
leg2 = cylinder(pos=vector(3.5,-5,3),
axis=vector(0,9,0), radius=0.45,
color = color.green )
leg3 = cylinder(pos=vector(10.5,-3.9,2),
axis=vector(0,9,0), radius=0.45,
color = color.green )
leg4 = cylinder(pos=vector(-11.5,-6.5,-2.2),
axis=vector(0,11,0), radius=0.45,
color = color.green )
The first image is what I got and the second image is what I want, but turned upside down as a table would
Try drawing out the table top and legs on paper
The up of the table top should be default
The legs should have the same "length"
To have the legs point downwards use a negative y
If the center of your table is 0,0,0 then the legs will reflect each other's positions in reference to that.
Related
I want to make a bar plot in ggplors where the value below zero is in red color. However, I got this graph instead of red color below zero value. Can anyone help me to solve the problem above? I have tried following some manual code but could not find the answers still.
Greatly appreciate for your help.
I tried this code:
Central_Java %>%
mutate(Category = factor(Category, levels = c("Minimum", "Medium", "Slightly Ideal", "Ideal"))) %>%
ggplot(aes(Province, Above_Below_Required_Staff, fill = Available_Staff, color=ifelse(Above_Below_Required_Staff>0, "red", "blue"))) +
xlab ("MPAs in Central Java\n(n=1)") + ylab ("Percent of Required Staff")+
ylim(-100,100)+
facet_wrap(~Category, ncol = 4)+
geom_bar(stat="identity")+
geom_hline(yintercept = 0, colour = "black") +
theme_light(base_size = 20) +
theme_bw()+
theme(text=element_text(size=19))+
ggtitle("Level of MPA Staff Capacity")+ theme(plot.title = element_text(hjust = 0.5))+
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank()
)
'''
Best,
[enter image description here] (https://i.stack.imgur.com/HPvZe.png)
I am very new to using plotly in rstudio and have come up against a problem with mapping discrete colours (stored as hex codes in the field color) to each of the slices in my ids field.
I have included my code below:
df %>%
plot_ly(
color = I("black"),
marker = list(colors = ~color)) %>%
add_trace(ids = df$ids,
labels = df$labels,
parents = df$parents,
type = 'sunburst',
maxdepth = -1,
domain = list(column = 0)) %>%
layout(sunburstcolorway = df$color)
This is the resulting sunburst diagram I get using this code, which is obviously not ideal:
Ideally the first four levels would have the same colour, and then different hex colour codes are used for slices that are labelled "Poor","Moderate","GwC" or "Good".
A csv file of my data frame used above is available here.
I finally managed to nut out how to map my colour field to the background colours on the sunburst chart - have updated the code in original post. All that was required was to insert the following code segment:
plot_ly(
marker = list(colors = ~color))
Below is the output chart:
I have a scatter plot centered around an origin. I want to draw the origin grid lines (one horizontal line, one vertical) in bold to make it easier to see where the origin is.
I can make two separate rule charts, each with one line in them, and lay them under my scatter plot, but that's annoying. Is there an easier way?
extent = 1.0
scale = alt.Scale(domain=(-extent, extent))
base = alt.Chart(pd.DataFrame([[0, -extent, extent]])).mark_rule()
xaxis = base.encode(
alt.Y('0:Q', scale=scale),
alt.X('1:Q'),
alt.X2('2:Q'),
)
yaxis = base.encode(
alt.X('0:Q', scale=scale),
alt.Y('1:Q'),
alt.Y2('2:Q'),
)
xaxis + yaxis + scatter
domainWidth in the configure_axisX or configure_axisY sets the thickness of the 'axis line':
import altair as alt
from vega_datasets import data
source = data.cars()
alt.Chart(source).mark_circle(size=60, clip=False).transform_calculate(
x = alt.datum.Horsepower-100,
y = alt.datum.Miles_per_Gallon - 25
).encode(
x=alt.X('x:Q', axis=alt.Axis(offset=-150)),
y=alt.Y('y:Q', axis=alt.Axis(offset=-190)),
color='Origin',
).configure_axisX(
domainWidth =3
).configure_axisY(
domainWidth =3
)
I am using Bokeh to create a series of pie charts with bokeh.charts.Donut. The charts are based off of subsets of the same DataFrame, and all have the same category labels. I want to ensure that the same categories are displayed in the same colors across the various charts, but I haven't been able to figure out a consistent way of controlling the colors.
Currently I am sorting my input DataFrames by the label, and passing the same array of colors to the palette property of Donut. This still does not work as intended. Code is as follows:
main_colors = ['#10A400','#DB5E11','#C8C500','#CF102E','#00AFA8','#82BC00','#A40D7A','#FF7100','#1349BB']
#split out youth health problems
for_youth_health = detailed_assessment_safety.loc[detailed_assessment_safety.youth_health_prob.notnull()]
youth_health_issues = pd.DataFrame(for_youth_health.youth_health_prob.str.split(' ').tolist())
for col in youth_health_issues.columns:
newcol = 'youth_health_prob_' + str(col)
youth_health_issues = youth_health_issues.rename(columns={col:newcol})
youth_health_trans = pd.melt(youth_health_issues)
youth_health_trans = youth_health_trans.loc[youth_health_trans.value.notnull()]
youth_health_trans['issue_text'] = youth_health_trans.value.map(map_health_issues)
youth_health_trans.drop('value',axis=1,inplace=True)
youth_health_trans.sort_values(by='issue_text',ascending=True,inplace=True)
#pie of youth health issues
youth_health_issues = Donut(youth_health_trans,label='issue_text',
values='variable',agg='count',plot_width=plot_width,
plot_height=plot_height,title='Reported Youth Health Issues',
color=main_colors)
hover = HoverTool(point_policy='follow_mouse')
hover.tooltips = [('Number Reported','#values'),('Health Issue','#issue_text')]
youth_health_issues.add_tools(hover)
#split out adult health problems
for_adult_health = detailed_assessment_safety.loc[detailed_assessment_safety.adult_health_prob.notnull()]
adult_health_issues = pd.DataFrame(for_adult_health.adult_health_prob.str.split(' ').tolist())
for col in adult_health_issues.columns:
newcol = 'adult_health_prob_' + str(col)
adult_health_issues = adult_health_issues.rename(columns={col:newcol})
adult_health_trans = pd.melt(adult_health_issues)
adult_health_trans = adult_health_trans.loc[adult_health_trans.value.notnull()]
adult_health_trans['issue_text'] = adult_health_trans.value.map(map_health_issues)
adult_health_trans.drop('value',axis=1,inplace=True)
adult_health_trans.sort_values(by='issue_text',ascending=True,inplace=True)
#pie of adult health issues
adult_health_issues = Donut(adult_health_trans,label='issue_text',
values='variable',agg='count',plot_width=plot_width,
plot_height=plot_height,title='Reported Adult Health Issues',
palette=main_colors)
hover = HoverTool(point_policy='follow_mouse')
hover.tooltips = [('Number Reported','#values'),('Health Issue','#issue_text')]
adult_health_issues.add_tools(hover)
What's the proper way to map the same categories of Donut charts to colors across multiple charts? The other idea that I had was inserting a column into the DataFrame that mapped label values to colors, and then passing that column as an argument to Donut, but I couldn't make that work either. Any help is much appreciated.
After some experimentation, it turns out that when you pass an array of colors to the palette argument of Donut, the colors are associated with the donut slices based on an alphabetical sort of the slice name. So, the first color in your array of palette colors will be associated with the slice with the alphabetically first name, etc.
Here is the breakdown: I load a model from an obj file and store into buffers as follows :vbo for vertexes, ibo for indexes , vao for state and num_indices an int with total indices number. To get the model color I exported a separate off file and extracted color information per vertex and I have an array with 4 values for each vertex so the size of the array is vertexno*4. My draw function looks like this.
glUniformMatrix4fv(location_model_matrix,1,false,glm::value_ptr(model_matrix));
glUniformMatrix4fv(location_view_matrix,1,false,glm::value_ptr(view_matrix));
glUniformMatrix4fv(location_projection_matrix,1,false,glm::value_ptr(projection_matrix));
//glUniform4f(location_object_color,1,1,1,1);
glBindVertexArray(mesh_vao);
glEnableClientState( GL_COLOR_ARRAY );
glEnableClientState( GL_VERTEX_ARRAY );
glColorPointer( 4, GL_FLOAT, 0, colors );
glDrawElements(GL_TRIANGLES,mesh_num_indices,GL_UNSIGNED_INT,0);
And the model renders black. I also have some cubes drawn in the draw function which I color using glUniform4f(location_object_color,rgba) and if I uncomment then the loaded mesh will take the same color as the last drawn cube.
In my constructor I have something like this:
glClearColor(0.5,0.5,0.5,1);
glClearDepth(1);
glEnable(GL_DEPTH_TEST);
gl_program_shader = lab::loadShader("shadere\\shader_vertex.glsl", "shadere\\shader_fragment.glsl");
location_model_matrix = glGetUniformLocation(gl_program_shader, "model_matrix");
location_view_matrix = glGetUniformLocation(gl_program_shader, "view_matrix");
location_projection_matrix = glGetUniformLocation(gl_program_shader, "projection_matrix");
location_object_color = glGetUniformLocation(gl_program_shader, "object_color");
If need be I can provide my shader_vertex and shader_fragment , I considered it to be a problem but im not so sure so if anyone knows why my model isn't being colored please throw a hand.