Here at Typ.io, we're revealing designers' decisions for all to see; peeking under the hood of beautiful websites to find out what fonts they're using and how they're using them.If you come across a site you likedrop us an emailabout it. You can also find us on Twitter and Pinterest.
Typography plays a strong supporting role in most logos. In rare instances, a highly stylized font can be matched well with an icon, but most often a logo icon and a decorative font tend to appear at odds with each other. So if you really love a script or calligraphy typeface, and the style of it speaks to your business brand, then you may be a candidate for a font-only logo with no logomark.
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A font foundry is a company that designs and distributes typefaces. Many of their typefaces are often designed by the same font designer and especially created to complement each other. My all-time favorite foundry is Hoefler & Co. Another one of my favorites is Vllg Fonts, which is co-op of multiple type foundries.
Our wordmark is a combination of our name and open shield element. The open shield represents openness, welcoming unique perspectives, unwritten history, and revolutionizing tradition. Breaking the tradition of center alignment often seen in academic marks, our open shield anchors our name sitting at the left-hand corner. Our name is set in Copernicus Bold, a modern typeface rooted in tradition.
Our short-hand version of the master wordmark. Our monogram is shorthand for the master wordmark and can be used in its place when working with internal audiences. For external use, the monogram should be accompanied by the master wordmark or exist in the context of Wesleyan already.
The Athletics Cardinal marks and wordmarks are custom-designed for use by the Wesleyan Athletics coaches, teams and departments. The updated Cardinal has been refined, adding more feathering to give an appearance of a cardinal in flight and a wider eye to evoke our attitude of remaining focused on the goals we set to achieve both on and off the field. The Athletic fonts were customized with extended lines and angles to convey forward motion and energy.
Our type family consists of two typefaces. Copernicus, our serif typeface, is used in our master wordmark and as body copy in print and on the website. Copernicus gives an academic, editorial, and professional feel. It may also be used in bolder applications when working on more expressive materials such as posters and flyers. Replica, our sans serif typeface, is used for web headers, for print headlines, and call-out treatments.
The primary focus of Wesleyan lifestyle photography is to capture faculty, students, staff and alumni in a candid fashion. Lifestyle photography is used to highlight the wide range and diversity of people, activities, studies, and ways of thinking that make Wesleyan unique. While the content of each photo may vary from shot to shot, the spirit and tone should remain consistent.
Wesleyan University makes every effort to ensure use of our colors, marks and imagery meet ADA Compliance standards. We utilize guidelines and tools such as WCAG 2.0 AA standards and WebAIM's Color Contrast Checker as part of our design process. For more information on Wesleyan's commitment to support all students in their academic and co-curricular endeavors, please visit our Accessibility Services website.
The Magics library was developed by ECMWF for plotting meteorological data.Magics allows you to create maps tailored to your needs, with options for plotting contour lines and fields, together with the possibility of customising legends, projections, titles, grids and labels.
In the CDS Toolbox, Magics maps of commonly used variables are styled automatically, which makes plotting a map quick and easy.This advanced guide explores how to customise a Magics map by going beyond the default styling.
However not all variables include automatic, full-colour styling of contours and legends.Maps that appear with blue contour lines, such as the plot below showing 2m dewpoint temperature, do not have a predefined style:
Each of the sub-dictionaries title, projection, contour, legend, background, foreground and width can be populated with relevant keywords which will be covered in the sections below.Only the keywords that we want to customise need to be specified.
In this guide, we group the map configuration in a single dictionary MAP_CONFIG, which we pass to ct.map.plot() as keyword arguments using the double asterisk notation **.We do this to make the call to ct.map.plot() more readable and to gather the entire map configuration in a single section of the code.We could also pass each configuration individually:
This workflow shows a global map of a climate anomaly from January 2020.The plotted data is the Near-Surface Air Temperature Anomaly variable from the Essential Climate Variables (ECV) dataset and initially the map simply uses the default settings.
The default title of the map is set by the long_name of the variable.To change the title of the map, we need to define the properties of 'title'.We can do so by passing a string, a list of strings or a dictionary to the 'title' kwarg.
If a list of strings is passed to 'title' instead, the first element in the list is plotted as the text for the main title, the second element as the text for the subtitle on the next line, the third as a further subtitle, and so on.Take a look at this example:
If a dictionary is passed to 'title', additional properties such as text justification, font size and text colour can be customised.In that case we use a different kwarg for the text of the title, 'text_lines', which is within the dictionary passed to 'title'.
We can use HTML tags within the list of strings in 'text_lines' to change the height of individual sections of text relative to the default.The example application sets the font size of the subtitle to be slightly smaller than the main title.The subtitle is defined as 'January 2020'.
'text_colour' sets the default colour for all titles and subtitles within 'text_lines'.The example application sets the text colour to 'charcoal'.We can change the text colour with a standard set of colour names or RGB values.
The 'cylindrical' and 'polar_stereographic' projections allow us to change the vertical and horizontal bounds of the map, otherwise known as the viewport.The viewport is controlled by setting the values of the corresponding longitudes and latitudes at each corner of the map.The following table shows the default values for these kwargs:
The quickest way to customise the contours is to pass a string to the main 'contour' kwarg that specifies the style library or style to be used.The available style libraries are 'cds', 'ecmwf', or 'ecchart'.If a style library is selected, the exact style is set based on the data variable name.The default option is 'cds'.We can pass in a different style library name as follows:
Selecting a specific style name in this way gives us more control over the appearance, whereas if we simply set the style library, the style is automatically determined according to the variable we are plotting.
If we want to apply several contour styles to the data (for example, for a heat map and contour line) we can pass the styles as a list.The list can include a combination of library names, style names and dictionaries.The styles are applied in the order in which they are passed to the list, one on top of the other.Given that the different styles overlay each other, we normally specify a contour shade style followed by a contour line style.If we were to pass the contour line style before the contour shade style, the contour lines would be underneath and therefore hidden.
To fully customise the style, we pass in a dictionary to the main 'contour' kwarg.Note that within this dictionary, there is a secondary contour kwarg which turns contour lines on or off.In the following sections, we will go through each secondary kwarg to describe what it does. Here is the complete code for the main 'contour' kwarg:
This Gallery example shows how to pass a list of dictionaries to the 'contour' kwarg.The list contains two dictionaries that contain properties for the heatmap (heatmap_contour) and the contour lines (line_contour) respectively.
If 'contour_shade' is turned on, the contour intervals will be filled with colours like a heatmap, whereas if 'contour' is turned on, the contour levels will be indicated with just lines and no colour between the lines.
If we choose the 'count' option for 'contour_level_selection_type', we can then specify the 'contour_level_count' kwarg to set the number of contour levels to be plotted.The example workflow has the number of levels set to 20:
As an example, let us consider the settings in the above code snippet applied to data with maximum and minimum values of 40 and -40 respectively.The divisions between the intervals will be as follows:
The 'contour_max_level' kwarg sets the highest data value to be included within the contour range.Conversely, the 'contour_min_level' kwarg sets the lowest data value to be included within the contour range.These can be specified for any of the contour methods: 'count', 'interval' or 'level_list'.If no specific values are given, the minimum and maximum levels are read from the data.
Specifying 'contour_max_level' and 'contour_min_level' will override other settings, (whether automatic or manual) for the contour limits.For example, if we choose 'level_list' as the contour method, the levels we manually create are still used but are limited within the maximum and minimum bounds determined by contour_max_level and contour_min_level.
To adapt the minimum and maximum contour level to the data, we modify the MAP_CONFIG dictionary inside the application function.This step is necessary because we need to be able to access the data once retrieved.If we were to reference data from outside the application function, we would encounter an error message because the data object has not yet been defined at that point. 152ee80cbc
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